Abstract book (pdf) - ICPR 2010

called 22q11.2 Deletion Syndrome. Genetic programming (GP) is used to learn the different 3D shape quantifications.
Experimental results show that the GP method achieves a higher classification rate than those of human experts and existing
computer algorithms.
09:00-11:10, Paper WeAT9.3
Identification of Ancestry Informative Markers from Chromosome-Wide Single Nucleotide Polymorphisms using Symmetrical
Uncertainty Ranking
Piroonratana, Theera, King Mongkut’s Univ. of Tech.
Wongseree, Waranyu, King Mongkut’s Univ. of Tech.
Usavanarong, Touchpong, King Mongkut’s Univ. of Tech.
Assawamakin, Anunchai, Mahidol Univ.
Limwongse, Chanin, Mahidol Univ.
Chaiyaratana, Nachol, King Mongkut’s Univ. of Tech.
Ancestry informative markers (AIMs) have been proven to contain necessary information for population classification. In
this article, round robin symmetrical uncertainty ranking for preliminary AIM screening is proposed. Each single nucleotide
polymorphism (SNP) is assigned a rank based on its ability to separate two populations from each other. In a multi-population
scenario, all possible population pairs are considered and the screened SNP set incorporates top-ranked SNPs from
every pair-wise comparison. After the preliminary screening, SNPs are further screened by a wrapper which is embedded
with a naive Bayes classifier. A classification model is subsequently constructed from the finally screened SNPs via a
naive Bayes classifier. The application of the proposed procedure to the Hap Map data indicates that AIM panels can be
found on all chromosomes. Each panel consists of 11 to 24 SNPs and can be used to completely classify the CEU, CHB,
JPT and YRI populations. Moreover, all panels are smaller than the AIM panels reported in previous studies.
09:00-11:10, Paper WeAT9.4
Evaluation of a New Point Clouds Registration Method based on Group Averaging Features
Temerinac-Ott, Maja, Univ. of Freiburg
Keuper, Margret, Univ. of Freiburg
Burkhardt, Hans, Univ. of Freiburg
Registration of point clouds is required in the processing of large biological data sets. The trade off between computation
time and accuracy of the registration is the main challenge in this task. We present a novel method for registering point
clouds in two and three dimensional space based on Group Averaging on the Euclidean transformation group. It is applied
on a set of neighboring points whose size directly controls computing time and accuracy. The method is evaluated regarding
dependencies of the computing time and the registration accuracy versus the point density assuming their random distribution.
Results are verified in two biological applications on 2D and 3D images.
09:00-11:10, Paper WeAT9.5
Cell Tracking in Video Microscopy using Bipartite Graph Matching
Chowdhury, Ananda, Jadavpur Univ.
Chatterjee, Rohit, Jadavpur Univ.
Ghosh, Mayukh, Jadavpur Univ.
Ray, Nilanjan, Univ. of Alberta
Automated visual tracking of cells from video microscopy has many important biomedical applications. In this paper, we
model the problem of cell tracking over pairs of video microscopy image frames as a minimum weight matching problem in
bipartite graphs. The bipartite matching essentially establishes one-to-one correspondences between the cells in different
frames. A key advantage of using bipartite matching is the inherent scalability, which arises from its polynomial time-complexity.
We propose two different tracking methods based on bipartite graph matching and properties of Gaussian distributions.
In both the methods, i) the centers of the cells appearing in two frames are treated as vertices of a bipartite graph and ii) the
weight matrix contains information about distance between the cells (in two frames) and cell velocity. In the first method,
we identify fast-moving cells based on distance and filter them out using Gaussian distributions before the matching is
applied. In the second method, we remove false matches using Gaussian distributions after the bipartite graph matching is
employed. Experimental results indicate that both the methods are promising while the second method has higher accuracy.
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