TEMPUS Summer School Projects
Image processing with applications in medicine and
robotics
1. Extraction of the brain (or part of the brain) from a 3-D
MR data set by region growing.
Input- a 3-D data set, for example MR brain.
Operation- given a seed point generated manually, and a
criteria defining 'edge' for example voxel must have
values between two limits, grow the region in 3-D to
extract the selected object.
Output- data set viewable with 3Dviewnix
Coding- in C or under PIP
Remarks- Difficulty easy. Manual editing could be added.
In competition with 2.
2. Extraction of the brain (or part of the brain) from a 3-D
MR data set by edge detection.
Input- a 3-D data set, for example MR brain.
Operation- By convolution with 3x3x3 operators, to
identify the 3-D edge and hence extract the object or
part of the object.
Output- data set viewable with 3Dviewnix
Coding- as desired (but not development of GUI)
Remarks- Difficulty medium. Could be extended by using
recursive operators. In competition with 1.
3. Block world line drawing generated from video input of
scene.
Input- 2-D Image of 3-d block world (or simulation) from
video camera.
Operation- Identification of lines and corners, linking
of this to extract model of scene.
Output- Line drawing of scene.
Coding- C
Remarks- Difficulty hard.
4. Simulation of beating heart data by creation of moving
ellipsoids, projection and blurring.
Input- set of parameters for ellipsoids as function of
time
Operation- generating 3-d scene and projecting for
various angles, adding noise, convolving with system
point function.
Output- Set of 2-d images of scene from surrounding
angles (raw tomogram) in Interfile.
Coding- Preferably in PIP.
Remarks- Difficulty mostly easy. This program is required
by COST B2. Generalization required. Output could be used
by 5.
5. 2-D edge detection using cost minimization.
Input- 2-D nuclear medicine data (or data from 4).
Operation- Define a transform, for example polar, a cost
function, for example circumference and gradient.
Minimize path in transformed data by cost
minimization.
Output- Algorithm to identify organ, for example left
ventricle of heart, without manual intervention.
Coding- In C or under PIP but in form which could be used
in package
Remarks- Difficulty medium. Problem is robustness
6. 2-D edge detection by linking set of points identified by
edge detection operator.
Input- 2-D CT or MR data after application of (for
example) Sobel operator to give edge strength and
direction maps.
Operation- To find an algorithm to link the points
identified on these map to give continuous enclosing
contours.
Output- Image with contour.
Coding- as desired (but not development of GUI)
Remarks- Difficulty medium.
7. Texture analysis using wavelet transform.
Input- MR (or radiology) 2-D image
Operation- Application of wavelet transform (see
Numerical recipes) to give regional texture
information
Output- Texture map.
Coding- as desired (but not development of GUI)
Remarks- Difficulty medium. Testing using simulated data
also required.
8. Registration of 2-D images using critical point matching.
Input- CT/MR images
Operation- extraction of contour, identification of
(geometrical) critical points (maximum gradient, 2nd
differential etc of contour), computation of
transformation to register two such images (e.g. by
SVD)
Output- Transformed image
Coding- as desired (but not GUI)
Remarks- Difficulty medium
9. Preprocessing, distortion removal and extraction of
quantitative data from electrophoresis gels.
Input- Set of gel electrophoresis images
Operation- Removal of background, identification of
tracks, correction of distortion e.g. smiles, extraction
of profiles, calibration of profiles.
Output- Set of peaks
Coding- under PIP
Remarks- Difficulty hard (A project team already
allocated)
10. Simulation of throwing dice (/input of real video images)
to generate image from which score determined.
Input- Simulation or video input of set of dice on
surface at random position
Operation- Identification of surfaces, counting of spots
on uppermost die surfaces automatically- No manual
intervention
Output- Score
Coding- in C
Remarks- Difficulty hard
11. User interface and game representation for 3-D
GO.
Input- none
Operation- Creation of 'game' including GUI and rules!
for extension of Japanese game GO to 3-D.
Output- playable game
Coding- as desired
Remarks- Difficulty depends on project team
12. Use of deformable model (snake) to identify structures on
CT/MR images.
Input- 2-d CT/MR images
Operation- Using a deformable snake, to fit the snake to
a target structure for example region of brain.
Output- Image with snake superimposed.
Coding- as desired (but not GUI)
Remarks- Difficulty medium
13. Implementation and testing of set of mathematical
morphology operations in set of reusable functions.
Input- mathematical morphology operators
Operation- to code them into set of functions for use by
other packages for example PIP and PICKIT
Output- set of validated functions
Coding- in C with constraints.
Remarks- Difficulty medium (validation essential)
14. 'XViewer' for DICOM image format data.
Input- DICOM read/write code for Oldendorf University
Operation- To read sample images in DICOM format and
display them with own X viewer (not XV).
Output- Images of DICOM input
Coding- C under Unix
Remarks- Difficulty hard (lots of other peoples code)
15. Automatic analysis of shape parameters to classify vocal
folds images.
Input- Images of vocal folds
Operation- Segmentation using manual assistance to
isolate vocal folds, computation of geometrical
characteristics.
Output- Output of geometrical characteristics to classify
vocal folds.
Coding- in C or under PIP
Remarks- Difficulty easy
16. Neural net to recognize small images of peoples faces from
video input.
Input- Images of peoples faces from video camera
Operation- Compression of data to say 16x16, generation
of neural net, training, and then use of neural net to
classify
Output- Classification of faces including identification
of errors (e.g. from translation)
Coding- as desired
Remarks- Difficulty medium (training is slow)