IMAGE RECONSTRUCTION

ALGORITHM-A SET OF RULES OR DIRECTIONS FOR GETTING SPECIFIC OUTPUT

FROM SPECIFIC INPUT

ALGORITHM MUST TERMINATE AFTER FINATE

NUMBER OF STEPS

PRE-PROCESING

REFORMATTED RAW DATA

CONVOLUTION WITH FILTER

IMAGE RECONSTRUCTION ALGORITHM

RECONSTRUCTED IMAGE

IMAGE:IMAGE:

STORAGEDISPLAY

RECORDINGARCHIVING

DETECTORS

IMAGE RECONSTRUCTION PERFORMED BY:

• ARRAY PROCESSOR OR PROCESSORS

RECONSTRUCTION WHEN ONE OR MORE TECHNICAL FACTORS ARE MODIFIED IS

CALLED:

• RETROSPECTIVE RECONSTRUCTION

FACTORS THAT CAN BE CHANGED DURING RECONSTRUCTION

• DFOV

• MATRIX

• SLICE THICKNESS

• SLICE INCREMENTATION

• ANGLE

SFOV LARGE DFOV

SFOV SMALL DFOV

TARGETED (ZOOMED) RECON

SFOV VERY SMALL DFOVTARGETED (ZOOMED) RECON

DIFFERENT MATRICES

80 X 80 512 X 512

USUALLY MATRIX IS PERMANENTLY SET AT 512 X 512

SLICE THICKNESS

• RECONSTRUCTION IN DIFFERENT THICKNESS ONLY POSSIBLE IN THE MULTISLICE UNIT

SLICE INCREMENTATION

• RECONSTRUCTION IN DIFFERENT SLICE INCREMENTATION POSSIBLE IN SINGLE AND MULTISLICE UNITS

INCREMENTATION

2MM

2MM

SLICE

INCREMENT

2MM

1MM

SLICE

INCREMENT

CONTIGUOUS 50% OVERLAP

2MM

4MM

SLICE

INCREMENT

100% GAP

SLICE vs

RECONSTRUCTIONINCREMENTATION

• SLICE THICKNESS

• RECON INCREMENT

• IMAGE QUALITY

• IMAGE QUALITY

TOMO ANGLE 360º

TUBE

TOMO ANGLE 180º

TUBE

TOMO ANGLE

• ANGLE IMAGE QUALITY

TYPES OF DATA

• MEASUREMENT DATA

• RAW DATA

• CONVOLVED DATA

• IMAGE DATA

PREREQUISITE FOR DATA RECONSTRUCTION

• DATA AVAILABLERAW

MEASUREMENT DATA(SCAN DATA)

• DATA THAT ARISES FROM DETECTORS. IT NEEDS TO BE PREPROCESSED TO ELIMINATE ARTIFACTS.

RAW DATA

• IT’S THE RESULT OF SCAN DATA BEING PRE-PROCESSED

CONVOLVED DATA

• FILTERED BACKPROJECTION IS THE ALGORITHM USED BY MODERN CT.

• IT REQUIRES FILTERING AND THEN BACKPROJECTION. RAW DATA IS FILTERED USING MATHEMATICAL FILTER.(CONVOLUTION)

• IT REMOVES BLURR. CONVOLUTION CAN ONLY BE APPLIED TO RAW DATA.

MATHEMATICAL FILTER CAN ALSO BE CALLED:

• KERNEL

• ALGORITHM

• PASS FILTER

TYPES OF FILTERS

• SMOOTH

• STANDARD

• SHARP

• EXTRA SHARP

TYPES OF FILTERS (SIEMENS)

• B20 (SMOOTH)

• B40 (STANDARD)

• A80 (SHARP)• A91 (VERY SHARP)

SMOOTH SHARP

IMAGE DATA(RECONSTRUCTED DATA)

• CONVOLVED DATA THAT HAVE BEEN BACKPROJECTED INTO THE IMAGE MATRIX TO CREATE CT IMAGES DISPLAYED ON THE MONITOR.

DETECTORS

SCAN DATA PREPROCESSING RAW DATA

CONVOLUTION

CONVOLVED DATA DATA

BACKPROJECTION

BEAM GEOMETRIES AND DATA ACQUSITION

• PARALLEL –SLOW

• FAN -FASTER

Algorithms applicable to CT

Back projection Iterative methods Analytic methods

BACK PROJECTION

• ALSO CALLED SUMMATION METHOD OR LINEAR SUPERPOSITION METHOD

Example image of how a cube generates different projections depending on the angle of projection

ITERATIVE ALGORITHMS

• SIMULTANEOUS ITERATIVE RECONSTRUCTION TECHNIQUE

• ITERATIVE LEAST SQUARES TECHNIQUE

• ALGEBRAIC RECONSTRUCTION TECHNIQUE

ITERATIVE RECON DEFINITION

• IT STARTS WITH ASSUMPTION AND COMPARES THIS ASSUMPTION WITH A MEASURED VALUE, MAKES CORRECTIONS TO BRING THE TWO VALUES IN AGREEMENT. THIS PROCESS REPEATS OVER AND OVER.

ART USED BY HOUNSFIELD IN HIS FIRST EMI BRAIN

SCANNER

ITERATIVE TECHNIQUES ARE NOT USED IN TODAY’S

COMMERCIAL SCANNERS THEY ARE VERY SLOW

BETTER THAN FILTERED BACK PROJECTION IN METAL ARTIFACT

REDUCTION AND NOISE REDUCTION

ANALYTIC RECONSTRUCTION ALGORITHMS

• FOURIER RECONSTRUCTION

• FILTERED BACK PROJECTION

USED IN MODERN CT SCANNERS

FILTERED BACK-PROJECTIONCONVOLUTION METHOD

• PROJECTION PROFILE IS FILTERED OR CONVOLVED TO REMOVE THE TYPICAL STAR LIKE BLURRING THAT IS CHARACTERISTIC OF THE SIMPLE BACK PROJECTION.

STEPS IN FILTERED BACK PROJECTION

• ALL PROJECTION PROFILES ARE OBTAINED• THE LOGARITHM OF DATA IS OBTAINED• LOGARITHMIC VALUES ARE MULTIPLIED BY

DIGITAL FILTER• FILTERED PROFILES ARE BACKPROJECTED• THE FILTERED PROJECTIONS ARE SUMMED

AND THE NEGATIVE AND POSITIVE COMPONENTS ARE CANCELLED

FOURIER RECONSTRUCTION

• USED IN MRI

• NOT USED IN CT BECAUSE OF COMPLICATED MATHEMATICS

ALGORITHM (FILTER) vs NOISE

DETAIL

NOISE

STANDARD

SMOOTHING

EDGE-ENHANCEMENT

SHARP

HIGH PASS FILTER

LOW PASS FILTER

RECONSTRUCTION IN SPIRAL CT

• FILTERED BACK PROJECTION USED + INTERPOLATION BACAUSE OF THE CONTINUOUS MOVEMENT OF THE PATIENT IN THE Z-DIRECTION.

( TO ELIMINATE MOTION BLURR)

RECONSTRUCTION IN MULTISLICE SPIRAL CT

• INTERLACED SAMPLING

• LONGITUDINAL INTERPOLATION

• FAN BEAM RECONSTRUCTION

RECONSTRUCTION ALGORITHM COMPARISON

• ANALYTIC METHODS ARE FASTER THAN ITERATIVE ALGORITHMS.

• FILTERED BACK PROJECTION IS USED IN MODERN CT SCANNERS

• ITERETIVE METHODS ARE BETTER THAN FILTERED BACK PROJECTION IN METAL ARTIFACT REDUCTION AND NOISE REDUCTION

MPRMULTIPLANAR

RECONSTRUCTION(REFORMATTING)

IT USES DATAIMAGE

STACKS OF IMAGES ONLY IN ONE PLANE CAN BE USED

FOR ONE TYPE OF MPRDIFFERENT PLANE IMAGES

CAN NOT BE COMBINED

ONLY IMAGES IN ONE PLANE CAN BE COMBINED!

http://www.urmc.rochester.edu/smd/Rad/neuroimages/CTLspinecor.jpg

http://www.urmc.rochester.edu/smd/Rad/neuroimages/CTLspinecor.jpg

CURVED MPR

FOR BEST QUALITY IMAGES

• USE VOLUMETRIC DATA ACQUSITION• RECON YOUR ORIGINAL THICKER SLICES INTO

VERY THIN SLICES (2mm OR 1 mm)• SELECT RECON INCREMENT THAT WOULD CREATE

AT LEAST 50% OVERLAP BETWEEN SLICES

EXAMPLE:2 MM SLICE THICKNESS1 MM SLICE INCREMENT

STAIRCASE ARTIFACT

3-D

EXTRUSION

IS A MODELING TECHNIQUE THAT GENERATES A 3-D OBJECT FROM

A 2 –D PROFILE ON THE

COMPUTER SCREEN.

IT USES IMAGE DATA TO BUILD 3-D OBJECT

EXTRUSION

PIXEL AREA

A

B

A= WIDTH B= HEIGTH

AREA OF THE PIXEL = A x B

VOXEL VOLUME

A

B

C

A= WIDTH B= HEIGTH

C-DEPTH (SLICE THICKNESS)

VOLUME OF THE VOXEL = A x B x C

DATA ACQUSITION FOR 3-D

• CONVENTIONAL SLICE BY SLICE

• VOLUME DATA ACQUSITION

PROBLEMS WITH CONVENTIONAL SLICE BY SLICE ACQUISITION IN 3-D

GENERATION• MOTION - STAIR-STEP ARTIFACT

• MIREGISTRATION

STAIR-STEP ARTIFACT

SEVERE STAIR-STEP ARTIFACT

PROCESSING FOR 3-D

• SEGMENTATION

• TRESHOLDING

• OBJECT DELINEATION

• RENDERING

SEGMENTATION

• PROCESSING TECHNIQUE USED TO IDENTIFY THE STRUCTURE OF INTEREST IN A GIVEN IMAGE. IT DETERMINES WHICH VOXEL ARE PART OF THE OBJECT AND SHOULD BE DISPLAYED AND WHICH ARE NOT AND SHOULD BE DISCARDED.

SEGMENTATION

THRESHOLDING

• METHOD OF CLASSIFYING THE TYPES OF TISSUES REPRESENTED BY EACH OF THE VOXELS. CT NUMBER IS USED TO DETERMINE THIS.

TRESHOLDING (IN SEGMENTATION)

DELINEATION

• BOUNDARY EXTRACTION

• VOLUME EXTRACTION

DELINEATION

RENDERING TECHNIQUES

• SURFACE RENDERING – SHADED SURFACE DISPLAY (SSD)

• VOLUME RENDERING

SURFACE RENDERING-SSD

• SIMPLER OF THE TWO METHODS. DISPLAYS THE IMAGE ACCORDING TO ITS CALCULATIONS OF HOW THE LIGHT RAYS WOULD BE REFLECTED TO THE VIEWERS EYES.

• COMPUTER CREATES INTERNAL REPRESENTATION OF SURFACES

ADVANTAGE OF SSD

• NOT MUCH COMPUTING POWER REQUIRED

• ONLY CONTOUR IS USED

DISADVANTAGES OF SSD

• INFO OF STRUCTURES INSIDE OR BEHIND THE SURFACE IS NOT DISPLAYED!!

VOLUME RENDERING

• SOPHISTICATED TECHNIQUE. 3-D IMAGES HAVE BETTER QUALITY THAN IN SURFACE RENDERING. USES ENTIRE DATA SET FROM 3-D SPACE. IT REQUIRES MORE COMPUTING POWER.

ADVANTAGES OF VOLUME RENDERING (VR)

• UNLIKE SSD, VOLUME RENDERING ALLOWS SEEING THROUGH SURFACES. IT ALLOWS THE VIEWER TO SEE BOTH INTERNAL AND EXTERNAL STRUCTURES.

DISADVANTAGE/S

• IT REQUIRES GREAT COMPUTING POWER – SOPHISTICATED COMPUTER EQUIPMENT

MAXIMUM INTENSITY PROJECTION

• VOLUME RENDERING 3-D TECHNIQUE THAT IS NOW FREQUENTLY USED IN CTA ( CT ANGIO) IT USES LESS THAN 10% OF DATA IN 3-D SPACE. IT DOES NOT NEED SOPHISTICATED COMPUTING.

IT ORIGINATED IN MRA

MIP ALLOWS ONLY THE VOXEL WITH THE

BRIGHTEST VALUE TO BE SELECTED

VR vs MIP

ADVANTAGES OF MIP

• NO NEED FOR SOPHISTICATED COMPUTER HARDWARE- IT USES LESS THAN 10% OF DATA

DISADVANTAGE/S OF MIP

• ARTIFACT- STRING OF BEADS

• NO SUPERIMPOSED STRUCTURES DEMONSTRATION

ARTIFACTS

• SSD – MANY FALSE SURFACES

• MIP – MIP ARTIFACT

• VR - FEW