Disentangling chromosome overlaps by combining trainable shape models with classification evidence

IEEE Transactions on Signal Processing

Volumn 50, Issue 8, 2002, Pages 2080-2085

  Charters, Graham C ^a,b   Graham, Jim ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b IBM   (United Kingdom)

Author keywords

Biological cells; Evidence combination; Image segmentation; Occlusion; Shape modeling

Indexed keywords

CHROMOSOMES; COMPUTER SIMULATION; IMAGE ANALYSIS; MATHEMATICAL MODELS;

SHAPE MODELS;

IMAGE SEGMENTATION;

EID: 0036684709     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2002.800421     Document Type: Article

References (11)

1. Trainable grey level models for disentangling overlapping chromosomes
2. Decomposition of overlapping chromosomes
3. Geometric separation of partially overlapping nonrigid objects applied to automatic chromosome classification
4. Active shape models - Their training and application
5. Automatic karyotype analysis
6. Toward a knowledge-based chromosome analysis system
7. Improved chromosome classification using monotonic functions of Mahalanobis distance and the transportation method
8. Automatic karyotyping of metaphase cells with overlapping chromosomes
9. Resolution of composites in interactive karyotyping
10. A classification-driven partiaily occluded object segmentation (CPOOS) method with application to chromosome ahalysis
11. Homologue matching applications: Recognition of overlapped chromosomes