06689321

1786 IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 19, NO. 6, DECEMBER 2014

Conic-Spiraleur: A Miniature Distal Scanner forConfocal Microlaparoscope

Mustafa Suphi Erden, Member, IEEE, Benoıt Rosa, Student Member, IEEE, Nicolas Boularot, Brice Gayet,Guillaume Morel, Member, IEEE, and Jerome Szewczyk

Abstract—Confocal microlaparoscopy is a promising approachin minimally invasive surgery for replacing conventional biopsiesthat involve physical tissue sampling. However, the typical imagesacquired with this technique cover a very small area limited by thefield of view of the probe. This paper presents the mechanical de-sign of a distal scanner, the conic-spiraleur, to perform automatedspiral scan with the probe in order to construct a mosaic-image.The design of the conic-spiraleur is based on using a conic structurewith a particularly curved surface. The pieces of the design are sim-ple to manufacture and easy to assemble with conventional meth-ods to form a device that can be inserted through a conventional5-mm diameter trocar. We present the pieces, assembly, control,and precision test of the system. The system is tested in vivo in anexperimental pig operation. We present the first in vivo, large field-of-view (3 mm2 ) and high resolution (1.4-μm lateral and 10-μmaxial) images in confocal microscopy.

Index Terms—Imaging, laparoscopy, mechanical design, medi-cal robotics, mosaicking, scan, soft tissue.

I. INTRODUCTION

THIS paper presents the mechanical design of a distal scan-ner for mosaic-imaging of soft tissue in laparoscopy op-

erations with a probe based confocal microlaparoscope. Confo-cal microlaparoscopy is an imaging modality mostly used fordetecting cancer cells on the surface tissues of organs [1]. It re-quires placing the probe in contact with the tissue and providesreal-time images of micrometer resolution. This resolution issufficient to perform in vivo pathology in replacement to tis-

Manuscript received December 3, 2012; revised April 5, 2013 and Septem-ber 27, 2013; accepted October 30, 2013. Date of publication December 19,2013; date of current version June 13, 2014. Recommended by Technical Ed-itor S. Fatikow. This work was supported in part by the ISI Project PERSEE(I0911038 W) and in part by French state funds managed by the ANR withinthe Investissements d’Avenir programme (Labex CAMI) under reference ANR-11-LABX-0004.

M. S. Erden was with the Institute of Intelligent Systems and Robotics, Uni-versity Pierre and Marie Curie, 75005 Paris, France. He is now with the LASALaboratory, Ecole Polytechnique Federale de Lausanne, CH 1015, Switzerland(e-mail: [email protected]).

B. Rosa was with the Institute of Intelligent Systems and Robotics, Uni-versity Pierre and Marie Curie, 75005 Paris, France. He is now with the Me-chanical Engineering Department, KU Leuven, 3001 Leuven, Belgium (e-mail:[email protected]).

G. Morel and J. Szewczyk are with the Institute of Intelligent Systems andRobotics, University Pierre and Marie Curie, 75005 Paris, France (e-mail:[email protected]; [email protected]).

N. Boularot is with Mauna Kea Technologies, 75010 Paris, France(e-mail: [email protected]).

B. Gayet is with L’Institut Mutualiste Montsouris, 75014 Paris, France(e-mail: [email protected]).

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TMECH.2013.2293519

sue biopsy preventing from physically sampling the tissue andsending it to a pathologist. This is of particular interest forextemporaneous biopsies, during which a patient is receivingsurgery in an operating room while the surgeon is waiting forthe results of the pathology analysis in order to orient the pro-cedure. Current extemporaneous tissue biopsy practice requiresa minimum of 20 min for the tissue sample to be sent to thepathologist laboratory, prepared for microscope examination,and be analyzed, whereas real-time confocal microlaparoscopycould save time and limit tissue damage.

A main drawback of current confocal microlaparoscopy forreplacing extemporaneous biopsies is the limitation of the im-age field of view. For microlaparoscopy [1]–[3], closely relatedmicroendoscopy [4]–[8], and functional fluorescence imagingsystems [9], the images are with micrometer resolution and typ-ically cover a circular area of 240 μm in diameter. This makes itpossible to perform analysis of a cell, or a few cells. However,pathologists need not only to analyze the cells by themselvesbut also their relative organization from a larger field of view.State-of-the-art techniques require a total surface of typically3 mm2 , which is within a circle with 1 mm diameter.

A solution to obtain such large scale images is to scan theregion of interest by sweeping the optical head on the tissue andto merge the images by mosaicking algorithms [10], [11]. Theresearch in [3] demonstrates the applicability of this approachin vivo on human patients by manually passing the miniprobeover the region of interest and using the mosaicking algorithmin [12]. With manual sweeping, it is difficult to obtain the preci-sion required for an actual tissue scan. An assistive handheld in-strument is presented for micropositioning for intraocular lasersurgery [13], but it is large to be used in minimally invasivesurgery and not intended for a few minutes long manipulationtypical for a scan. The motorized surgical microscope presentedin [14] enables the surgeon to control the movement of the mi-croscope by index finger movements with a remote controller.Although, this is a semiautomated system, it would be tediousfor a surgeon to make the probe follow a proper scan path byfinger movements. Indeed, mosaicking requires proper overlap-ping between images with a rather constant speed.

The study [15] on automated scanning demonstrates image-mosaicking on human hand skin using a MEMS based scannerdesign and the mosaicking algorithm in [16]. The MEMS scan-ner is batch fabricated on silicon wafers with four deep-reactive-ion-etching steps. In this paper, we present a lower-cost solutionfor the scanning problem.

In a recent study [17], we demonstrate another design formicroimage scanning based on pneumatic balloon catheters ac-tuation, integrate this system with visual servoing [18], and

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ERDEN et al.: CONIC-SPIRALEUR: A MINIATURE DISTAL SCANNER FOR CONFOCAL MICROLAPAROSCOPE 1787

Fig. 1. Experimental setup for soft tissue scanning. (a) Left to right: the Staubli-Robot, the computer controlling the robot, and the computer performing theimage acquisition. (b) The soft tissue (beef liver) under the probe attached to the end effector of the robot.

perform ex vivo raster scans on soft tissue. In this system, thescan trajectory can be chosen arbitrarily; however the systemrequires an active control of the probe to follow that trajectory.Therefore, the performance is dependent on the quality of theactuation. In the present paper, we develop a distal scanningsystem which uses a simple motor actuation placed apart fromthe moving part and which generates the trajectory by puremechanical motion without active control. Consequently, thegeneration of the scan trajectory is more robust with the presentdesign compared to that of [18].

In [19], the authors present a wide-angle-view endoscopewhich uses two articulated wedge prisms that can be rotated bytwo motors. The prisms are 12 mm in diameter. For laparoscopyoperations, on the other hand, it is crucial to minimize the inva-sion diameter preferably to fit with 5-mm trocars.

Our research aims at developing a means for deploying aconfocal microlaparoscope probe in the abdomen through astandard 5-mm trocar in order to image tissues in replacementof extemporaneous biopsies. It targets a minimally invasive de-vice for the purpose of scanning the tissue with the probe. Thedeveloped system is able to automatically generate a probe mo-tion with respect to the tissue while being easily positioned andstabilized manually by the surgeon. Furthermore, the systemis easily driven from the distal end by using a single motor.The design makes use of a conic structure. This structure gen-erates a scan path following an Archimedean spiral, in otherwords a spiral where the radius increases proportionally withthe angle of turn. We use the mosaicking algorithm presentedin [12] and [20]. This is a correlation-function-based algorithm,designed to account for difficulties typical of in vivo tissue imag-ing, such as motion distortions, irregularly shaped frames, andnonrigid deformations. A preliminary version of this paper ispresented in [21], where a 5:1 scale rapid prototype of the me-chanical system here is implemented in plastic and tested byanalysis of video images.

In Section II, we demonstrate the superiority of a spiral scanover a raster scan on soft tissue. In Section III, we introduce ourconfocal microlaparoscopy system and summarize our observa-tions with ex vivo soft tissue scans with robot, which serve asthe requirements for our design. In Section IV, we explain theconceptual principle of generating a spiral motion by using aconic structure. In Section V, we present the calculation of the

conic surface and provide the SolidWorks design of the overallscanner. In Section VI, we present the actual system with thepieces, the process of assembly, and the control. In Section VII,we present the precision test of the conic-spiraleur by videorecording of the trajectory of a laser beam emitted from the tipof the optical head. In Section VIII, we present the in vivo test ofthe conic-spiraleur and we show the acquired mosaics. SectionIX concludes the paper.

II. SPIRAL VERSUS RASTER SCAN

The conic-spiraleur presented in this paper performs tissuescan by following an Archimedean spiral trajectory. The ratio-nale behind such a design is based on our observations thatspiral scanning outperforms the raster scan on soft tissue. Ourobservations consider the interaction between the probe and thetissue. For correlation-function-based mosaicking algorithms,it is stated in [11] that spiral scan is better than the raster scanalso from a computational point of view. In this section, wepresent our results comparing an Archimedean spiral path ver-sus a raster path with ex vivo soft-tissue scans.

Our in vivo and ex vivo imaging-experiments throughout thispaper make use of the Cellvizio imaging technology from theMauna Kea Technologies (Paris, France) [22]. This system per-forms confocal fluorescence imaging from a depth of 40 μm,records images in size 240-μm diameter with 1.4-μm lateral.and 10-μm axial resolution at a rate of 9 frames/sec. The sys-tem is equipped with a correlation based mosaicking algorithmpresented in [12], [20], [22]. It can construct a mosaic out ofsequentially collected images provided that there is only trans-lation between them, in other words there should be no rotationof images with respect to each other. The confocal probe of thesystem consists of a flexible bundle of optical fibers and an op-tical head hosting the microlenses, located at the tip. The outerdiameter of the flexible bundle is 1.4 mm. The optical head is acylinder 12-mm long with an outer diameter of 2.6 mm. In thispaper, we refer to the optical head by the word “probe”.

The ex vivo experiments in this section are performed witha Staubli-Robot (Staubli-TX40) on beef liver purchased fromthe supermarket (see Fig. 1). We maintain an indentation depthof 350 ± 50 μm. The robot is commanded to follow the rasterand spiral trajectories shown by the dashed (violet) curves in


Fig. 2. Sample raster scan on ex vivo beef liver. (a) Mosaic image; (b) x position; (c) y position; (d) x versus y positions; (e) speed in x direction; (f) speed in ydirection. Dark-solid (black): image trajectory; light-solid (green): probe trajectory; light-dashed (violet): commanded trajectory.

Fig. 3. Sample spiral scan on ex vivo beef liver. (a) Mosaic image; (b) x position; (c) y position; (d) x versus y positions; (e) speed in x direction; (f) speed in ydirection. Dark-solid (black): image trajectory; light-solid (green): probe trajectory; light-dashed (violet): commanded trajectory.

Figs. 2(d) and Fig. 3(d). These are named as the commandedtrajectory. The probe follows the light-solid (green) curves inthe same figures with respect to the global reference frame.We name these as the probe trajectory. In our experiments, thedeviation of the probe trajectory from the commanded trajectoryis never more than 50 μm.

The trajectory of the probe with respect to the tissue surfaceis named as the image trajectory. The image trajectory deviatesfrom the probe trajectory; because the tissue also moves underthe impact of the probe. The authors explain elsewhere the

nature of the slip/stick phenomenon in soft tissue scan [23], [24].The mosaicking algorithm we use [12], [23] captures the imagetrajectory by returning the position of sequential images as theyare placed in the resulting mosaic image. The dark-solid (black)lines in Figs. 2(d) and Fig. 3(d) show the image trajectories forthe raster and spiral scans, respectively.

The question we would like to answer is which of the rasterand spiral scans is better in the sense that the overall mo-saic is compact and focused on the target point. An inspec-tion of Fig. 2(d) reveals that with the raster scan, the image


trajectory cannot follow the sharp turns (at the corners) of theprobe trajectory. In Fig. 2(e) and (f), the speed of the imagetrajectory cannot catch up with the sudden rise of the speedof the probe trajectory. The resulting mosaic lacks the regionsaround the corner points.

The spiral scan shown in Fig. 3(d) is free of sharp turns.The trajectories given in Fig. 3(e) and (f) reveal that there isno sudden rise of speed. The speed corresponding to the probetrajectory and the image trajectory closely match in shape. Theresulting mosaic is compact. The focus point remains almost atthe center of the image, well surrounded with a fully connectedview.

In order to quantify these observations, we perform calcu-lations to evaluate the mismatch between the probe and imagetrajectories for raster and spiral scans. As a measure of mis-match, we integrate the difference between the positions andvelocities of image and probe trajectories for each of raster andspiral scans and indicate the result with the parameters D andC in (1) and (2), respectively,

D =∫ tf

0

|pi (t) − pp (t)|tf

dt

Draster = 0.2363 mm

Dspiral = 0.2398 mm (1)

C =∫ tf

0

|vi (t) − vp (t)|tf

dt

Craster = 0.2321 mm/s

Cspiral = 0.1218 mm/s. (2)

In (1) and (2), pi and vi are the position and velocity cor-responding to the image trajectory, pp and vp are the onescorresponding to the probe trajectory, and tf is the final scantime. The position measure D does not distinguish between thetwo scans. This is because both of the image trajectories aredisplaced with respect to the probe trajectories. The velocitymeasure C clearly distinguishes between the raster and spiralscans. The velocity gives information about the changes in thedirection of the movement regardless of the position difference;therefore it better reveals the resemblance in shape. Accordingto the measure C, the mismatch between the speeds correspond-ing to the probe trajectory and the image trajectory is almostdouble for the raster scan in comparison to that of the spiralscan.

We also compute the ratio of the area covered by the mosaicto the intended area, with ten spiral and ten raster scans oneach of beef liver and chicken breast tissues. Chicken breast isa stiffer tissue than the beef liver. For the beef liver, the averageratio was 0.60 (standard deviation 0.14) for the raster scans and0.81 (standard deviation 0.07) for the spiral (t-test: statisticallysignificant with p < 0.02). For the chicken breast, the averageratio was 0.77 (standard deviation 0.04) for the raster scans and0.82 (standard deviation 0.04) for the spiral (t-test: statisticallysignificant with p < 0.01). These numbers are indicative of thesuperior performance of the spiral scan over the raster on twodifferent types of tissues.

Fig. 4. The concept of stabilizing tube: the part of the tissue covered by theedges of the tube slightly bends and gets into contact with the probe inside.(Adapted from [25] for the design in this paper.)

III. OBSERVATIONS FROM Ex Vivo EXPERIMENTS

The previous study of microimage scanning with ballooncatheters actuation [17], our ex vivo experiments with theStaubli-Robot on soft tissue, and our discussions with the sur-geons within our project meetings constitute the source of therequirements for the design presented in this paper. In this sec-tion, we explain the targets of our design by referring to theseobservations and experiences.

The scan on soft-tissue is affected by the indentation andthe friction between the probe and the tissue. We examined theimpact of friction in a previous study [23], [24]. In the designhere, we use a stabilizing tube, as shown in Fig. 4. Our scanmechanism is to be mounted in this tube, which is 3.5-cm longand has a standard inner diameter 5 mm for minimally invasivesurgery. For the usage of the system, the surgeon manuallybrings the tip of the tube to the locus of interest and slightlypresses on the tissue. The tube makes an indentation dependingon the amount of the force applied by the surgeon. The forceapplied by the surgeon is mainly countered by the reaction forceon the outer edge of the tube, rather than that on the probe.Therefore, the contact between the probe and the tissue is lessaffected by the pressure applied by the surgeon, compared to thecase where a probe is indented without a tube. Due to the reactionforce, friction occurs between the edge of the tube and the tissueand this friction provides the adherence and stabilization of thesystem over the region to be scanned. The tissue within thisregion slightly bends and gets into contact with the probe inside.The stabilizing tube brings the practical advantage that not theprobe itself, but the edge of the tube intrudes into the tissue.Furthermore, with stabilization of the region, the impact of thefriction between the probe and the tissue on tissue deformationis reduced [25].

In Fig. 4, one can see the part of the tissue inside the tube,which bends up and gets into contact with the probe. In thisfigure, d represents the distance between the tip of the probeand a hypothetical flat surface touching the outer edge of thetube. The contact between the probe and the tissue is mostlyaffected by this distance d.

The determination of the optimum value of d for a goodimaging has been the subject of an unpublished study carriedout with the Staubli-Robot (see Fig. 1) with ex vivo soft tissueexperiments. We made different scans where we used a 5-mmtube that pushed on the tissue and we actuated the probe inside


the stationary tube with the robot. We varied the depth and angleof tube indentation and the tissue type. We found that in mostsituations, the optimal value of d to get the best images wasbetween 200 and 300 μm. Outside this range, either the probesank into the tissue avoiding proper sliding or there was notenough contact for proper imaging. These experiments do notguarantee that the determined range is the best in all situations,but they show that it is the case in most of the experimentedsituations.

Some other experiments with different probe inclination withrespect to the tissue surface indicated that the angle between theprobe and the normal of the tissue surface should not exceedten degrees for an acceptable imaging; best performance wasachieved below five degrees. With the conic structure in ourdesign, which will be introduced in the following sections, theradius of scan is changed by inclination of the probe with re-spect to the tube, which means by inclination of the probe withrespect to the normal of the stabilized tissue surface. Therefore,the inclination angle and the value of d are variable. In our de-sign, we aim at maintaining a nominal d value of 200 μm andvarying it between 200 and 300 μm. As a result, the require-ments are that the inclination should not exceed five degreesand that it should not result in a change of d more than 100 μm(0.1 mm). Please note that the distance d in the design variesby mechanical manipulation; it has nothing to do with the forceapplied, indentation, or any other manual operation. Its valueis mechanically determined for any given position of the drivesystem.

In order not to have a gap between the images, the limit forthe distance between two successive scan-lines is slightly lessthan the diameter of a single image (0.24 mm). We aim for adistance 0.15 mm, corresponding to 26% overlap of images insuccessive scan lines.

Our design is intended for automatic scan of an area 3-mm2

large on the soft tissue. This corresponds to a circular region ofapproximately 1-mm radius. Our ex vivo experiments showedthat the quality of mosaicking is influenced by the scan speed.Proper image mosaics are obtained when the speed is less than0.5 mm/s. Above 0.5 mm/s, the pushing effect of the probe ontissue is increased causing excessive deformations that avoidproper mosaicking. The surgeons, with whom we collaborate,state that the duration of scan should be less than 3 min. We targetat 2 min duration for a full spiral scan. Given the Archimedeanspiral with 0.15 mm line distance covering an area of 3 mm2 ,the duration of 2 min corresponds to a constant translation speedof approximately 0.19 mm/s.

With this speed, the rate of overlap between the successiveimages will be 89%. The mosaicking algorithm [12] requires atleast 30% overlap of an image with the mosaic to which it willbe integrated. With 89% overlap between successive images and26% overlap with the previous line, the algorithm is expected toeasily integrate each image to the accumulating mosaic.

IV. CONCEPTUAL DESIGN OF THE CONIC-SPIRALEUR

The requirement for the scanner is to generate a spiral motionat the tip point where the probe is located. The translation of

Fig. 5. The conic structure attached to the probe.

Fig. 6. Generation of the spiral motion at the tip point, P, of the probe. The cam(brown) is simultaneously rotated and translated on the conic surface (green).This motion results in the bending of the probe and translation of the tip.The cam is at its nominal position in (a) and iterated to its maximum in (b).(c) Zoomed view of bending of the conic structure.

the probe following an Archimedean spiral can be maintainedby bringing together two motions: a rotation around the focuspoint and a change of the radius in proportion to the angle ofrotation. It should be noted that the probe itself should onlytranslate through the Archimedean spiral without any rotationas required by the mosaicking algorithm. In our survey, we didnot come across any mechanical solution that transfers simplerotation into a translational motion following an Archimedeanspiral. The solution we propose here is using a conic structure asshown in Fig. 5. The conic part of this structure has an inclinedsurface. The outside curve obtained by a cross sectional cut canbe represented by the relation between the parameters f and s(see Fig. 5).

Fig. 6 illustrates how this conic structure generates the spiralmotion with a cam pushing and rotating on the conic surface. Inthese figures, the conic structure is fixed at the point O; it canmove around this point in two directions (pitch and yaw) butcannot turn around itself (no roll motion). This configurationis based on the assumption that for small inclination angles(θ < 10◦), a stiff cable will bend exactly at the point it is fixedand the other parts will remain linear. The optical fiber passesthrough the centerlines of the cam and the conic structure.

In Fig. 6(a), the guiding cam is at its nominal position (d =0); the center-lines of the cam and the conic structure coincide.In this situation, the tip point P is located at the center of the


region to be scanned. In Fig. 6(b), the guiding cam is rotated anddue to the screw at the rear, linking to an outer tube (not shownin the figure), it translates with a distance d. This causes theconic structure to incline with an angle θ; as a result, the pointP translates by a distance z = rsin(θ). Fig. 6(c) zooms the partof the conic structure where bending occurs. The amount of thetranslation of the cam (d) determines the amount of change inthe tip position (z). The tip of the cam pushes the conic surfaceand translates the tip of the probe, P, in xy dimensions along acircle with radius z. With changing the translation of the cam(d), the radius of this circle changes. In this way, a spiral motionis obtained.

V. CALCULATION FOR THE CONIC SURFACE AND GEOMETRIC

DESIGN IN SOLIDWORKS

The conceptual design in Fig. 6 generates a spiral mo-tion at the tip point. However, this spiral is not necessarilyArchimedean. With an Archimedean spiral, the radius is pro-portional to the angle of rotation. In our conceptual design, thiscorresponds to that the amount of deviation of the tip point Pfrom the center (z) should be proportional to the amount of it-eration of the cam (d). This can be achieved by a proper designof the curved profile of the surface of the conic structure.

The solution is based on writing the geometric equationsrelated to Fig. 6 and numerically solving these to find the co-efficients of a second-order polynomial representing the curveof the conic surface. A straightforward application of geometricand trigonometric relations leads to the equations (3)–(7). Here,the segments denoted by (k + d), (l), and (e) constitute a right-angled triangle (3). The angles γ and θ can be determined bythe trigonometric relations (4)–(5). The segments denoted by (s+ l), (k + f), and (e) constitute another right-angled triangle.One of the angles of this triangle is θ + γ, and this leads tofinding the value of s as in (6). Using the same triangle, f canbe determined as in (7). We want to achieve the proportionalrelation (8) by fitting the second-order polynomial (9) to thecurve of the conic surface

e =√

(d + k)2 + l2 (3)

γ = sin−1 l

e(4)

θ = sin−1 z

r(5)

s = e sin (θ + γ) − l (6)

f =√

e2 − (l + s)2 − k (7)

z =α

ηd (8)

f ′ = As2 + Bs + C. (9)

In our mechanical design, the lengths l, k, and r are fixed;α is desired to be fixed at 0.15 mm (distance between the scanlines); and η is determined to be 0.4 mm (distance of iterationof the cam in one rotation). Therefore, in our formulation, l, k,r, α, and η are constants; e, s, d, f, γ, θ, and z are variables.

TABLE IVALUES OF THE PARAMETERS IN THE FORMULATION AND SOLUTION

The mathematical problem is to minimize the error betweenthe geometrically calculated f in (7) and the curve fit, f ’, bymodifying the parameters A, B, and C in (9). The minimizationshould be performed in the range of z that covers the desiredarea of scan, let us say in the range [0, Z].

The problem statement isMinimize

E = (f ′ − f)2 (10)

subject to

(3)–(7) and 0 ≤ z ≤ Z

to determine

A,B,C.

We perform optimization by using six values equally dis-tributed in the range of interest z ∈ [0,1] mm. We numericallysolve this problem with the fsolve() function in the optimiza-tion toolbox of MATLAB. Table I presents the values of theconstant parameters, the values of z used for optimization andthe resulting values of the parameters of the polynomial.

In Fig. 7(a), we depict the relation between the spiral radiusand the translation of the cam: linearity is maintained withinthe region of interest, z ∈ [0,1] mm. In Fig. 7(b), we showthe resulting spiral for eight rotations. The region of interest,indicated by the dashed (red) circle, is covered in less than sevenrotations. Within this region, the radius is linearly proportionalto the angle of rotation: an Archimedean spiral is achieved.Outside the region of interest, the radius is not linear any more.

To verify the design requirements, we calculate the perpen-dicular distance and inclination of the tip of the probe from thenominal position, with respect to the radius of the spiral. At1-mm radius of the spiral, the perpendicular distance is0.025 mm and the inclination is 2.87 degrees. Both of the valuesremain in the acceptable range, less than 0.1 mm and less thanfive degrees, respectively. Therefore, our system guarantees thecontact of the probe with tissue throughout the spiral scan.

A geometric constraint for the design is that the probe shouldnot touch the inside surface of the tube. The minimum marginbetween the edge of the probe and the outer tube occurs whenthe cam is translated to its maximum, to the distal edge of theconic surface where f = m. At this point, the side margin, u, isgiven as in (11), where R = 2.5 mm is the inner radius of theouter tube and ρ = 1.3 mm is the radius of the probe.

u = R − (z + ρ. cos θ). (11)


Fig. 7. (a) The relation of the radius of the spiral to the translation of the cam on the conic surface: linearity is maintained in the region where the radius is lessthan 1 mm. (b) The spiral to be followed by the tip of the probe: it is an Archimedean spiral within the circle of 1-mm radius (dashed).

Fig. 8. (a) The relation of the margin between the edge of the probe and the inner surface of the tube: there is a positive margin when the spiral reaches 1-mmradius, namely the probe does not touch the tube. (b) The profile of the horizontal dimension of the conic surface with respect to the spiral radius. (c) The verticaland horizontal dimensions of the conic surface.

Fig. 8(a) depicts the side margin with respect to the spiralradius. It is observed that the margin remains positive when thespiral radius is 1 mm; therefore it is possible to fit such a conicstructure inside a 5-mm tube and generate the desired spiral.Fig. 8(b) shows the required value of the radial dimension ofthe conic surface, s, to reach a radius of 1 mm at the end of thespiral. Fig. 8(c) shows both dimensions of the curve of the conicsurface. The arrows indicate the limit dimensions for scanningthe region of interest (z ∈ [0,1] mm) and for maintaining a pos-itive side margin. The dimensions for the required scan are lessthan the limit dimensions for a positive side margin. We chooseto use the limit for scanning the region of interest, because withthis value the outer dimension of the conic structure does notexceed the radius of the probe (l = 0.85; s = 0.45; ρ = l + s =1.3 mm). This leads to the maximum value of f determined asm = 2.61 mm.

Fig. 9(a–c) show the SolidWorks design of the overall sys-tem. It consists of nine pieces: a conic structure (conic surfaceintegrated to the probe), a cam (front and rear), an outside tube,a support, a spur-gear, a shaft, the optical fiber, a juncture, anda handle. The handle is included only for manual drive of thesystem (not used in this paper). In Fig. 9(a), the conic structure,front part of the cam, support, optical fiber, spur-gear, shaft, andhandle are shown; in Fig. 9 (b), the rear part of the cam and thejuncture are added; in Fig. 9 (c), the outer tube is visible. Asshown in Fig. 9(d), the shaft is placed eccentric to the support.

It rotates the spur-gear located at the front part of the support.The spur-gear is coupled to the inner surface of the cam whichis designed as an internal-spur-gear. In this way, the rotation ofthe handle/motor is transferred to the cam. In Fig. 9(a), one canalso see the eccentric canal on the support in which the opticalfiber is placed. The optical fiber makes an S shape to locate atthe centerline of the support at the distal end (partially visible).

In Fig. 9(e), four front views of the design are given as facingto the scan surface in different phases of the scan. The blueline at the middle shows the desired spiral to be followed bythe tip of the probe represented by the green point. The systemsuccessfully translates the tip point along the desired spiral. Inthe rightmost figure, the tip point reaches the boundary of therange of interest and the probe still does not touch to the innersurface of the tube. This is a confirmation that the overall designis fitting to the tube with an inner diameter of 5 mm.

VI. MANUFACTURING, ASSEMBLY, AND CONTROL

In this section, we present the pieces of the system manu-factured in stainless steel and cobalt carbon alloy, the assem-bly of the overall system, and the control system driving theconic-spiraleur.

The pieces are ordered to be manufactured by external com-panies specialized in production of miniature pieces with highprecision. Among the pieces, the tube, juncture, front part of the


Fig. 9. The overall SolidWorks design of the conic-spiraleur. Visible parts in different colors: (a) optic-head (red), conic structure (green, gray), cam-front(brown), support (yellow), spur-gear (gray), optical fiber (blue), shaft (gray), handle (violet); (b) cam-rear (brown), juncture (light blue); (c) tube (green); (d) camrear, support (transparent), spur-gear, optical fiber. (e) The tip point of the probe is following the desired Archimedean spiral.

cam, and the conic surface are manufactured by conventionalmachining out of stainless steel (316 L). The support, rear partof the cam, and spur-gear have complex surfaces; therefore, theyare not suitable for conventional machining. These pieces areproduced by sintering technology out of cobalt chrome alloy andthen reworked manually by grinding and drilling. In Fig. 10(a),one can see the rear and front parts of the cam, shaft, opticalfiber, spur-gear, juncture, tube, support, and the conic structure,compared in size to a ten Euro cents coin.

The conic structure is integrated with the probe and the opticalfiber by Mauna Kea Technologies, the company with which wecollaborate. It should be noted that this integration is delicateand requires high precision; because, the probe carries also theminiature optic lenses. Afterwards, the optical fiber is placedinto the channel on the support and fixed by gluing. In thisway, the conic structure, the optical fiber, and the support arefixed to each other. The conic structure can bend with respectto the support, because the connecting optical fiber in between(0.5 mm in length) is flexible [see Fig. 10(a)]. The carrier-tube,juncture, and the tube covering the scanner are passed ontothe optical fiber. The carrier-tube is a conventional tube with a5-mm inner diameter and 35-cm length. It is to be attached onone tip to the assembled mechanism and on the other tip tothe driving motor [see Fig. 10(d)]. The shaft passes through thecarrier-tube and reaches the mobile mechanism on the other end.The tube covering the mobile mechanism is a special one withan inner screw, has a 5-mm inner diameter and 3.35-cm length.The spur-gear, rear, and front parts of the cam are placed on thesupport. An elastic wire is rolled around the front part of the cam

and the conic structure [see Fig. 10(b)]. This is to ensure thatthe conic structure is pressed on the tip of the cam. Fig. 10(b)shows the assembly at this stage comparing its size with a oneEuro coin. The assembly is finished by gluing the carrier-tubeto the juncture. The assembled conic-spiraleur at the tip of thecarrier-tube is shown in Fig. 10(c) with a laser beam at the tip.

The conic-spiraleur is driven by a standard brushless mo-tor (Maxon DC motor; outer diameter: 16 mm; power: 3.2 W;nominal voltage 4.8 V; no load speed 5700 rev/min; nominaltorque: 5.55 mNm; weight 38 g), equipped with a gear box(Maxon planetary gearhead; diameter 16 mm; reduction ration:29; nominal torque 0.15 Nm), and an encoder (512 counts perturn). The motor is attached at the distal end of the carrier-tubeby an intermediary plastic module. Fig. 10(d) shows the entiresystem of conic-spiraleur with the motor attached. The overallsystem has 47-cm length, with an intrusive part of 35-cm length,and 5-mm diameter.

The motor is driven by a controller (Maxonmotor 4-Q-DCServo Control LSC 30/2) which enables to control the rotationspeed with an analogue signal. The communication to the com-puter is achieved using a standard data acquisition box (NI USB6008). A power supply feeds both the controller and the motor[see Fig. 10(e)]. The commands to the motor are generated inMATLAB environment. The MATLAB program communicateswith the custom made control panel shown on Fig. 10(f). Withthe two buttons on the panel, it is possible to command the pro-gram to scan (FW) or to rewind (BW) as well as to stop (STOP)and to run/rerun (RUN) while scanning or rewinding. The LEDson the panel indicate the state of operation. The computer


Fig. 10. (a) The manufactured pieces of the conic-spiraleur: the rear and frontparts of the cam, shaft, optical fiber, spur-gear, juncture, tube, support, and theconic-structure in comparison to a ten Euro cents coin. (b) A view of assemblybefore placing the tube on the cam and gluing the juncture to the carrier-tube.(c) A view of the assembled conic-spiraleur with a laser light beam at the tip ofthe probe. (d) The driving motor integrated to the carrier-tube. (e) The powersupply, motor controller, data acquisition box, and the control panel. (f) Closeview of the control panel used to give the commands for scan, rewind, run, andstop.

Fig. 11. The setup for the precision test: the conic-spiraleur, magnifier, andthe CMOS camera placed on the precision table.

communicates with this control panel via the same data ac-quisition box.

VII. MEASUREMENTS OF PRECISION

We performed measurement of the precision of the spiralby recording a laser beam emitted from the probe while beingmoved by the conic-spiraleur. Fig. 11 shows the experimentalsetup with the conic-spiraleur, the magnifier, and a high resolu-tion CMOS (complementary-metal-oxide-semiconductor) cam-era placed on a precision table. When the distal end of the opticalfiber is lighted with a laser beam, the light reaches the tip of theprobe at the other end. The confocal microscopy technologyof Cellvizio (Mauna Kea Technologies) allows to light a fewfibers within a bundle in order to obtain a very fine beam oflaser light at the tip of the probe. This laser beam is passedthrough a magnifying lens that is focused on the CMOS camerawith a double magnification. The CMOS camera has a nominalresolution of 5.2 × 5.2 μm2 area per pixel; with the double mag-nification, we obtain 2.6-μm resolution in both directions of theCartesian framework. In our setup, the images are recorded at4.7 frames/s. The conversion factor between the camera dis-tance and the actual distance at the tip of the probe is calibratedby manually displacing the conic-spiraleur (without driving themotor) on the precision table by a distance 500 μm. The factoris determined to be 500/915.

We want to perform a scan with constant velocity in 2 min;this corresponds to a linear velocity of 0.19 mm/s at the tip of theprobe. We calculate the rotational speed profile of the cam andthe driving motor. The gear ratio between the motor and the camis 11:24. Fig. 12(a) shows the speed profile for the cam in orderto achieve 0.19 mm/s linear speed at the tip. Fig. 12(b) showsthe oscillation of the cam. The cam makes approximately 6.4turns. As observed in Fig. 12(c), the radius of the spiral reaches1 mm in less than 120 s. After the completion of the spiral, themotor is rewound in order to bring the tip back to the center.


Fig. 12. (a) The commanded speed of rotation of the cam. (b) The oscillation of rotation of the cam. (c) The profile of the radius of the spiral throughout therotations.

Fig. 13. (a) The trajectory of the tip of the probe derived from the video-recorded trajectory of the laser light by the CMOS camera. (b) Comparison of thetrajectory of the tip of the probe with the ideal Archimedean spiral. (c) The speed profile of the movement of the tip of the probe. (c, d) The x and y positions ofthe tip of the probe.

This backward drive can be fast because it is free of imaging. Inour system, the rewinding takes around 40 s.

Fig. 13(a) shows the spiral followed by the laser light. Thediameter of the scanned region is approximately 2 mm, whichcovers an area of around 3 mm2 . The spiral is quite regularexcept for the beginning, at the center. We observe that theprobe is not located at the center at the beginning of the scan.The cause of this is that the winding that presses the probe on thetip of the cam is not strong enough to force the probe to touchthe cam at the starting position. After around two full rotations,this problem disappears and the probe follows a proper spiral.Due to this deficiency, we can expect a hole at the center of amosaic that would be generated with this scan.

In Fig. 13(b), the spiral of the laser light (blue and red) iscompared with the ideal spiral path (green). The overlap be-tween the images of successive scan lines is guaranteed withina ± 45-μm deviation (150 + 2 × 45 = 240 μm, which is the

diameter of single image). In this figure, the blue parts of thelaser light (thickness ∼20 μm) touch the ideal spiral drawn ingreen (thickness ∼ 50 μm). This corresponds to following theideal spiral with a precision of approximately ± 35 μm. Thered parts deviate from the ideal spiral with more than ± 35-μmdistance. The blue parts in this figure correspond to the 474 mea-surement samples of the 592 in total. Based on these numbers,we can conclude that the conic-spiraleur follows the intendedspiral with a success rate of 80% within the error margin of ±35 μm.

In Fig. 13(c), the linear speed of scan is plotted. The speedhas an average value of 0.2 mm/s and except for the starting partthe values remain less than 0.5 mm/s. With this speed range, wecan expect to collect proper images for the overall scan.

The distance between the lines was expected to be 0.15 mm.In Fig. 13(d–e), the position of the probe tip is depicted in x andy directions. Here, we measure the distance between the extreme


points of each round of spiral along the x and y axes. We ignorethe first two turns because the spiral is obviously deficient atthe central part. In total, we make 12 measurements of distancesbetween the spiral branches. Among those, the minimum is0.11 mm, the maximum is 0.18 mm and the average is 0.15 mm.These numbers also indicate that the distance between the scanlines remains less than the limit 0.24 mm with an average of theintended distance 0.15 mm.

VIII. In Vivo VALIDATION WITH PIG EXPERIMENT

The conic-spiraleur is tested in vivo on a pig weighing around50–60 kg in an experimental operation performed at the animalexperimentation units of the Institut Mutualiste Montsouris inParis. In Fig. 14, one can observe the conic-spiraleur (a) in theoperation room, (b) while being installed into a 5-mm trocar,and (c) when its tip is pressed on the peritoneum of the pig fora scan. Although the surgeon for the first time saw the systemon the day, he could easily use it with success without anyprior trial. This is an indication that the usage of the conic-spiraleur, namely placing the tip on the tissue and holding itstationary during the scan, is quite easy to be managed withoutprior experience. The MATLAB program and the control panelwere operated by the first author during this in vivo experiment.When the surgeon indicated that he was ready for a scan, theconic-spiraleur was driven by turning on the switches on thepanel. After the completion of the scan, the conic-spiraleur wasrewound again using the control panel. At this moment, thesystem was ready for another scan. During all these processes,the MATLAB program continuously ran on the laptop computer.

In Fig. 15, we present the resulting mosaics obtained by scan-ning the surface of the peritoneum (a) and the liver (b) of the pig.Fig. 15(a) is a quite satisfactory mosaic without any significantgap, covering an area 2.67 mm2 . The ratio of the covered areawith respect to the intended area (3 mm2) is 0.89. Although theconic-spiraleur did not manage to cover the central part of thespiral [see Fig. 13(a)], in Fig. 15(a) the resulting image is full.There are two reasons for that. First, although the path does notfollow the ideal spiral, the abrupt movements at the start stillresult in collection of some images from the central part. Theseimages are still used in the resulting mosaic. The second causeis that to some extent the soft tissue sticks to and moves withthe tip of the probe. Therefore, whatever the actual path of theprobe, the path with respect to the tissue surface might result ina fully connected mosaic.

In Fig. 15(b), the mosaic covers an area of 2.80 mm2 . The ratioof the covered area with respect to the intended area (3 mm2)is 0.93. We observe a gap at the center. This is because theliver tissue is more slippery than the peritoneum; therefore thereis no enough sticking of tissue to compensate the abnormalityof the actual spiral in the central regions. On the other hand,because there is less sticking, the probe travels more distancewith respect to the tissue; therefore, the area covered by themosaic is slightly larger with the liver tissue.

We observe that there are also slight gaps on the outerbranches of both mosaics. The main cause is that in these partsthe distance between the scan lines is larger than the others.

These are perhaps the instances where the distance between thescan lines reaches 0.18 mm as observed in the measurements.When this affect is combined with tissue deformation the imagesdo not overlap enough for the mosaicking algorithm.

The rate of area covered by the mosaic with respect to theintended area is slightly larger with the in vivo mosaics (0.89 and0.93 in Fig. 15) compared to those with the ex vivo spiral mosaicsperformed with the Staubli-Robot in Section II (average ratio is0.81 for beef liver, 0.82 for chicken breast). This is an indicationthat there is less sticking and less deformation of tissue with thein vivo experiments. There might be two reasons for this. Thefirst is that the in vivo tissues are expected to be stiffer thanthe ex vivo tissues; therefore they stick less and deform less.The second reason is the stabilizing effect of the outer tubeof the conic-spiraleur (Fig. 4). Due to this stabilization, thetissue inside the borders of the edge of the tube moves less andtherefore deforms less during the scan.

The mosaics in Fig. 15, as interpreted by the biologists1 withwhom we collaborate, allow to see in white the structure ofnonoriented elastic and collagen fibers into the peritoneal con-nective tissue [see Fig. 15(a)] and the distribution of hepatocytesin normal liver lobule [see Fig. 15(b)]. The tissues are healthyand it is expected that the presence of carcinosis would easilybe visible as an heterogeneous distribution of cancerous cellswith atypia and potentially mucus secretion in the peritoneum.The artifacts on these images are very visible to human eye,especially the presence of abnormal “redundant structures”, inparticular repeating parallel lines are visible on the bottom rightof the liver image [see Fig. 15(b)].

The comments by the biologists confirm that the imagesare satisfactory for diagnosis purposes. We consider this asan accomplishment with the design and implementation of theconic-spiraleur.

IX. CONCLUSION

In this paper, we address the problem of generating largefield-of-view images in confocal microlaparoscopy without sac-rificing the high resolution of a single shot image. The solutionwe develop is based on using a conic structure in order to scan asoft tissue by translating the optical head (probe) of the confocalmicroscope along a spiral path. We present a mechanical designwhere a rotating cam pushes on the conic surface attached to theprobe. Due to the rotation of the cam, the tip of the probe alsorotates; the radius of the rotation of the tip smoothly increaseswith the iteration of the cam on the conic surface. Simultaneousrotation and iteration result in generation of a spiral. A properdesign of the conic surface allows this spiral to be Archimedian:the radius linearly changes with the angle of rotation.

We present the manufacturing, assembly, and drive of theoverall conic-spiraleur and the results of our precision test witha high resolution camera. The measurements indicate that thedesign is successful to generate the desired Archimedean spiral.Our system has a slight implementation problem that the probe

1Dr. Muriel Abbaci and Dr. Corinne Laplace-Builhe, Institut Gustave Roussy,Imaging and Cytometry Platform, both specialists of cell imaging for pathologyanalysis.


Fig. 14. (a) The conic-spiraleur in the operation room. (b) The conic-spiraleur being installed into a 5-mm trocar. (c) The tip of the conic-spiraleur pressed onthe peritoneum of the pig while scanning.

Fig. 15. The mosaics obtained by scanning the surface of (a) the peritoneum and (b) the liver of the pig.

is not pressed enough on the cam at the central regions of thespiral; therefore there are some abrupt motions of the probeat the start and a gap in the central part of the spiral. Thisimplementation problem is to be overcome by using a strongerwire winding to ensure that the probe is properly pressed on thetip of the cam even at the central regions.

Our conic-spiraleur is tested in vivo in an experimental opera-tion performed on a pig. We performed scans on the peritoneumand liver. The mosaics demonstrate the success of the conic-spiraleur to scan the targeted region to generate high resolutionand wide field-of-view images. The mosaics are designated bythe biologists as suitable for diagnosis purposes. In one of thosemosaics, it is possible to observe the impact of abrupt motionsof the probe at the start of the spiral in the form of a hole at thecenter. It is also possible to observe slight gaps in some partsbetween the traced lines of images. In order to eliminate thesetwo problems, in the future generations of the conic-spiraleur,we will use a tighter wire winding as mentioned before and wewill aim for slightly less distance between the scan lines.

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Mustafa Suphi Erden (M’11) received the B.S.,M.S., and the Ph.D. degrees in electrical and elec-tronics engineering from Middle East Technical Uni-versity, Ankara, Turkey, in 1999, 2001, and 2006,respectively.

Between 1999 and 2006, he was a Research As-sistant with the Department of Electronics and En-gineering, Middle East Technical University. From2007 to 2012, he was a Postdoctoral Researcher, suc-cessively in Delft University of Technology, Delft, theNetherlands; in Ecole Nationale Superieure de Tech-

niques Avancees-ParisTech, France; in University Pierre & Marie Curie–Paris6, France. In 2012, he received the European Union Marie Curie IntraEuropeanFellowship. Since September 2012, he is with the Learning Algorithms andSystems Laboratory, Ecole Polytechnique Federale de Lausanne, Switzerland,with this fellowship. His research interests include human–robot interaction,assistive robotics, skill assistance, mechatronics design, medical robotics, walk-ing robots, and machine learning.

Benoıt Rosa (S’09) received the Engineering degreefrom the Ecole Centrale Paris, Chatenay-Malabry,France, and the Ph.D. degree in robotics from the Uni-versity Pierre and Marie Curie–Paris 6, Paris, France,in 2009 and 2013, respectively.

Since July 2013, he has been a Postdoctoral Re-searcher within the Robotic Assisted Surgery groupof the Mechanical Engineering Department, KU Leu-ven, Leuven, Belgium. His research interests includedesign and control of robotic and mechatronic de-vices for surgical operations, image-guided medical

interventions, and visual servo control.

Nicolas Boularot received the Engineering degreefrom the Ecole Nationale Superieure de Mecaniqueet des Microtechniques, Besancon, France, in 2004.

He is currently Manager of the Mechanical De-sign and Traceability Department, Mauna Kea Tech-nologies, Paris, France. He joined this company inFebruary 2005 and has designed innovative tools tovisualize and detect cellular abnormalities during en-doscopic procedures.

Brice Gayet, photograph and biography not available at the time of publication.

Guillaume Morel (M’97) received the Ph.D. degreein control engineering from the University Pierre andMarie Curie–Paris 6, Paris, France, in 1994.

He was a Postdoctoral Researcher at the Mas-sachusetts Institute of Technology, Cambridge, MA,USA, from 1995 to 1996. Back in France, he was suc-cessively a Research Engineer for the French Com-pany of Electricity and an Assistant Professor at theUniversity of Strasbourg, Strasbourg, France, from1997 to 2001. He is currently a Professor of Roboticsat the University Pierre and Marie Curie–Paris 6. His

research interests have been in the sensor-based control of robots, with a particu-lar focus on force feedback control and visual servoing. Since 2000, his researchtarget applications are assistance for surgery and, more recently, rehabilitationsystems. Today, within the Institute of Intelligent Systems and Robotics, heleads the research team AGATHE (Assistance to Gesture with Application toTHErapy), which develops the concept of comanipulation, where a robot and ahuman user share the control of the same object for the realization of a manip-ulation task.

Jerome Szewczyk received the M.S. degree inmechanical engineering from the University ofCompiegne, Compiegne, France, in 1994, and thePh.D. degree in robotics from the University Pierreand Marie Curie–Paris 6, Paris, Frace, in 1998.

Between 2000 and 2010, he was an AssistantProfessor at the University of Versailles, Versailles,France. Since 2011, he has been an Associate Pro-fessor at the University Pierre and Marie Curie–Paris6. His research activities at the Institut des SystemesIntelligents et de Robotique concern the design of

sensors and actuators for meso-robotics based on smart materials and the opti-mal design of robotic structures for surgical applications.

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