Occlusion Detection in M-FISH Human Chromosome Images

Automation of Chromosome Analysis has long been considered a tedious task due to the partial occlusion of chromosomes. This calls for a non-trivial, dedicated procedure to segment chromosomes. In this paper, a new method is proposed which detects and separates occluded chromosomes, by separating out the chromosome cluster from the M-FISH image, followed by detecting the cut-points along which these clusters can be split into multiple regions. These regions are then combined into separate partial chromosomes based on difference matrix. After this stage the invisible regions due to occlusion is reconstructed based on the visibility in the five channels. The performance of the new proposal   was compared with the existing work and observed better performance in resolving occlusions. With 15 occluded  chromosome images tested, 90% accuracy was obtained

[1]  E. Zerbin-Rüdin.  [Genetics in medicine]. , 1969, Wiener medizinische Wochenschrift.

[2]  Jim Piper,et al.  Pre-processing of images in an automated chromosome analysis system , 1981, Pattern Recognit..

[3]  André Oosterlinck,et al.  Two-dimensional shape decomposition using fuzzy subset theory applied to automated chromosome analysis , 1981, Pattern Recognit..

[4]  Jean-Marc Chassery,et al.  An Iterative Segmentation Method Based on a Contextual Color and Shape Criterion , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Catherine Garbay,et al.  Image Structure Representation and Processing: A Discussion of Some Segmentation Methods in Cytology , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Liang Ji,et al.  Intelligent splitting in the chromosome domain , 1989, Pattern Recognit..

[7]  Kweku-Muata Osei-Bryson,et al.  An object location strategy using shape and grey-level models , 1989, Image Vis. Comput..

[8]  L. Ji.  Fully automatic chromosome segmentation. , 1994, Cytometry.

[9]  寛一 中川原.  Automation of Chromosome Analysis , 1998 .

[10]  Alan C. Bovik,et al.  Minimum entropy segmentation applied to multi-spectral chromosome images , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[11]  Alan C. Bovik,et al.  Entropy estimation for segmentation of multi-spectral chromosome images , 2002, Proceedings Fifth IEEE Southwest Symposium on Image Analysis and Interpretation.

[12]  K. Castleman,et al.  Joint segmentation and classification of M-FISH chromosome images , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[13]  Lei Wang,et al.  26th Annual International Conference of the IEEE EMBS , 2004 .

[14]  Dimitrios I. Fotiadis,et al.  Identifying touching and overlapping chromosomes using the watershed transform and gradient paths , 2010, Pattern Recognit. Lett..

[15]  Madhuri Joshi,et al.  Automated Karyotyping of Metaphase Cells with Touching Chromosomes , 2011 .

[16]  R. Vadivel,et al.  Energy Efficient With Secured Reliable Routing Protocol (EESRRP) For Mobile Ad-Hoc Networks , 2012 .