RT Journal Article
SR Electronic
T1 Centromere Detection of Human Metaphase Chromosome Images using a Candidate Based Method
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 032110
DO 10.1101/032110
A1 Akila Subasinghe
A1 Jagath Samarabandu
A1 Yanxin Li
A1 Ruth Wilkins
A1 Farrah Flegal
A1 Joan H. Knoll
A1 Peter K. Rogan
YR 2016
UL http://biorxiv.org/content/early/2016/01/09/032110.abstract
AB Accurate detection of the human metaphase chromosome centromere is an critical element of cytogenetic diagnostic techniques, including chromosome enumeration, karyotyping and radiation biodosimetry. Existing image processing methods can perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation, which can adversely affect centromere localization. We present a centromere detection algorithm that uses a novel profile thickness measurement technique on irregular chromosome structures defined by contour partitioning. Our algorithm generates a set of centromere candidates which are then evaluated based on a set of features derived from images of chromosomes. Our method also partitions the chromosome contour to isolate its telomere regions and then detects and corrects for sister chromatid separation. When tested with a chromosome database consisting of 1400 chromosomes collected from 40 metaphase cell images, the candidate based centromere detection algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%. We also introduce a Candidate Based Centromere Confidence (CBCC) metric which indicates an approximate confidence value of a given centromere detection and can be readily extended into other candidate related detection problems.