Title | ||
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ChromSeg - Two-Stage Framework for Overlapping Chromosome Segmentation and Reconstruction. |
Abstract | ||
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Karyotyping is the most commonly used genetic tool for diagnosing diseases associated with chromosomal abnormalities. It generates images of the chromosomes of a patient in which quantity or shape discrepancies against normal chromosomes might suggest chromosomal abnormalities. However, the current methods are cumbersome and require manual or half-automatic separation of overlapping chromosomes, significantly limiting the productivity of clinical geneticists and cytologists. In this project, we implemented a fully automatic method, called ChromSeg, which efficiently separates crossing-overlap chromosomes. It uses a new neural network architecture called “region-guided UNet++” to accurately detect crossing-overlap chromosomes from metaphase cell images. A new heuristic algorithm, called “crossing-partition”, is then applied to splice and reconstruct the crossing-overlap chromosomes into single chromosomes. While there are a very limited number of publicly accessible annotations on overlapping chromosomes, we manually annotated 345 images for our model training and performance testing. Benchmarking results showed that our method achieved 99.1% overlap detection on crossing-overlap chromosomes and outperformed the second best method by 3.1%. Notably, this is the first tool to provide an image of the reconstructed chromosomes; other tools provide only segmentation suggestions, which are of less value to end-users. The source code of ChromSeg is available at https://github.com/HKU-BAL/ChromSeg, and the 345 annotated images are available at http://www.bio8.cs.hku.hk/bibm/. |
Year | DOI | Venue |
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2020 | 10.1109/BIBM49941.2020.9313458 | BIBM |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xu Cao | 1 | 5 | 8.07 |
Fangzhou Lan | 2 | 0 | 0.34 |
Chi-Man Liu | 3 | 96 | 7.06 |
Tak Wah Lam | 4 | 0 | 0.34 |
Ruibang Luo | 5 | 2 | 1.76 |