| Project 1 | Project 2 | Project 3 | Project 4 |
| Project 5 | Project 6 | Project 7 | Project 8 |
| Project 9 | Project 10 | Project x1 | Project x2 |
Label the group photo- identify faces and label them. Try to generate atlas of photo from the group photo.
Remarks: Difficulty medium
Extraction of the brain (or part of the brain) from a 3-D MR data set by region growing/ edge detection.
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.
-or-
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: in C or under PIP
Remarks: Difficulty easy. Manual editing could be added. In competition with 2.
Block world line drawing generated from range image input of scene.
Input: 2-D Image of 3-d block world as a range image (pixel value function of distance)
Operation: Identification of lines and corners, linking of this to extract model of scene.
Output: Line drawing of scene. Rotation of object to create new scene.
Coding: C
Remarks: Difficulty hard.
Extraction of 'skeleton' from 3-D objects.
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
Motion correction
Given a set of images in time which are similar but not identical, derive a method for identifying the motion that has occurred (in 2d) between different images (shift and rotation) such that they can be adjusted and corrected.
Input: Starting from image sequence, identify features for example with skeleton, or determin regions of change by subtraction etc. Find significant changes
Output: image marked with regions of change
Coding: as desired
Remarks: Difficulty medium
Create a cine display of a sequence of objects using Borland C++ builder, with control over speed etc
Remarks: Difficulty: Who knows (problem is documentation)
Generate a compute based logo for IPMI, using bend of the river at Visegrad and the number 16.
Ouput: for exmaple a Java applet
Remarks: Difficulty: requires artictic ability
Texture analysis using wavelet transform.
Input: MR (or radiology) 2-D image
Operation: Application of wavelet transform (see Numerical recipes- which needs to be downloaded) to give regional texture information, or other code available
Output: Texture map.
Coding: as desired (but not development of GUI)
Remarks: Difficulty medium. Testing using simulated data also required.
Matched filter v. observer
2-D edge detection using cost minimization/ snakes.
Input: 2-D nuclear medicine data or vocal folds images.
Operation: Define a transform, for example polar, a cost function, for example circumference and gradient. Minimize path in transformed data by cost minimization.
-or-
Fit a snake for example using Greedy algorithm
-or-
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. 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
Match of fragment of coastline to map
Starting off with a segment of coastline from a map, of different scale and noise properties extracted from a (much) larger segment, perform a best fit to identify the section of coastline. One method that could be used would be by correlation of a chain code representation.
Creation of chain code or equivalent from map segment is part of project
Input: 2d map
Output: contour with match
Coding: as desired
Difficulty: quite easy