8/6/2019 O'Leary Patterson Garway-Heath Crabb ARVO Poster 2006

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This work is supported in part by an unrestricted educational grant from

Heidelberg Engineering and the Moorfields NHS Special Trustees

Mean Pixel Height Standard Deviation (MPHSD) is a metric tomeasure the quality of alignment of single topographies composing a

Heidelberg Retinal Tomography (HRT) Mean Topography (MT) image.

This measure is frequently the main factor in deciding if a MT image is

to be included in studies and/or if further scans should be taken to

improve the image quality.

This study used HRT patient data and computer simulation to assess:

The sensitivity of MPHSD of HRT MT images to the qualitativestructure of the constituent single topographies

The sensitivity of other metrics, such as the Median of PHSD of HRTMT images

Heidelberg Engineering have published guidelines for interpretingMPHSD

and these have been used for inclusion/exclusion criteria in severalstudies e.g. 3.

INTRODUCTION RESULTS

METHODS

CONCLUSIONS

Investigating Mean Pixel Height Standard Deviation: An Image QualityMetric Used in Scanning Laser Tomography

N OLeary,1 AJ Patterson,1 DF Garway-Heath,2 DP Crabb1

1Department of Optometry and Visual Science, City University London, London, UK2Glaucoma Research Unit, Moorfields Eye Hospital, London, UK

Author disclosure block: N OLeary: None; AJ Patterson: None; DF Garway-Heath: Carl Zeiss MeditecInc.: F, Talia Technologies Ltd: F, Heidelberg Engineering: F, R ; DP Crabb: None.

RATING perfect very good good acceptabletry to

improvenot evaluable

MPHS (m) < 10 10-20 20-30 30-40 40-50 > 50

Developed by Patterson et al2 to provide realistic virtual patients toaid in developing and testing measurement methodsCarefully engineered to produce MPHSD values consistent with thedistribution of those obtained clinically Uses real patient data (single topographies) and simulatedmisalignment noise to generate MTs For a series of 74 single topographies identical misalignment noisewas used to produce 74 MTs (Figure 1) In total 10 MTs, each with different noise, were generated for each ofthe 74 single topographies along with the associated MPHSD values. Individual PHSD values were examined in order to examine the pixel-

wise distribution of standard deviations.

Generated Mean Topography:Simulation generates 3 single topographies from one original singletopography, then averaged at a pixel level to produce a new MT.

Calculating MPHSD:At each pixel in a MT a Pixel Height Standard Deviation (PHSD) iscalculated over the 3 constituent Single Topography pixels. Thearithmetic meanover all PHSD in the MT is the MPHSD.

Program # 3353

z-axis

x-axis

y-axis

Figure 2. HRT topography images (with reflectance images) giving minimum(left) and maximum (right) MPHSD values (image structures to which MPHSD isleast and most sensitive, respectively, of the 74 images when uniform noise isadded)

The range of MPHSD Values for generated MTs (averaged over 10 simulations)was very large (15 to 114m) for identical misalignment noise sets

PHSD values for generated MTs were not Normally distributed (Figures 3 and 4)

and were positively skewed with larger tails in ONH structures with higher

topographic height differences between the bottom of the cup and the rim

As a consequence, MPHSD is sensitive to misalignment in images with more

prominent anatomical features, primarily a higher degree of cupping

The median of PHSD is less sensitive to these effects of ONH structure (Figure 4)

Qualitative observations of images reveals also that the MPHSD is most sensitive

to high frequency spatial variability in topographic images (Figure 5)

The range of MPHSD values varied considerably despite identical misalignment

movement being applied to generate all mean topographies

As the distribution of pixel height standard deviation values is skewed, the mean

may not be an appropriate summary measure to characterise the data

The median of PHSD is less sensitive to misalignment of topographies with highanatomical structural variability

Both MPHSD and median of PHSD are sensitive to misalignment of topographies

with local high frequency variability

FURTHER WORK

1 2 3 73 74

Generated SingleTopographies

Generated MeanTopographies

Figure 1. Schematic of single series simulation (as applied to 74 distinct singletopographies)with noise set visualisation (randomly generated translations in,and rotations about, the x, y, z axes, with pixel-wise Gaussian noise added2)

Original Single

Topography Series

We plan to evaluate other metrics to summarise the repeatability of topography

images and compare them with image quality measures derived from expert

observers

Figure 3. 2-D and 1-D distributions of PHSD for generated MTs of thosegiving minimum (left) and maximum (right) MPHSD values

Higher PHSD

Topography Topography

Figure 5. Cross-section of topographies representing low-frequency spatial variabilityand high-frequency spatial variability.

Cross section of Topographiesgiving 3 minimum MPHSD values

Cross section of Topographiesgiving 3 maximum MPHSD values

1. Strouthidis et al: Br. J. Ophthalmol. 2005; 89; 1427-1437 2. Patterson et al: IOVS; 2005; 46; 1657-16673. Hawker et al: IOVS; 2005; 46; 4153-4158

Identical

Noise Sets

Simulation Methodology

74 Single Topographies from

real patient data1

3 Noise Sets

74 Generated MeanTopographies

74 Associated MPHSDValues

Board # B886

Figure 4. 2-D and 1-D distributions of PHSD for generated MTs of thosegiving MPHSD values of 36 (left) and 27m (right) but Median of PHSD valuesboth of 22m. Note the longer tail in the left distribution to which thearithmetic mean is more sensitive than the median.