ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1112.4164
108
69
v1v2v3v4v5 (latest)

A Geometric Approach For Fully Automatic Chromosome Segmentation

18 December 2011
Shervin Minaee
Mehran Fotouhi
B. Khalaj
ArXiv (abs)PDFHTML
Abstract

Chromosome segmentation is a fundamental task in human chromosome analysis. Most of previous methods for separation between touching chromosomes require human intervention. In this paper, a geometry based method is used for automatic chromosome segmentation. This method can be divided into two phases. In the first phase, chromosome clusters are detected using three geometric criteria and in the second phase chromosome clusters are separated using a proper cut line. However, most earlier methods do not work well with chromosome clusters that contain more than two chromosomes. Our method, on the other hand, has a high efficiency in separation of chromosome clusters in such scenarios. Another advantage of the proposed method is that it can easily apply to any type of images such as binary images. This is due to the fact that the proposed scheme uses the geometric features of chromosomes which are independent of the type of images. The performance of the proposed scheme is demonstrated on a database containing touching and partially overlapping chromosomes with a success rate of over 91%.

View on arXiv
Comments on this paper