• DocumentCode
    1140573
  • Title

    Automatic Segmentation and Disentangling of Chromosomes in Q-Band Prometaphase Images

  • Author

    Grisan, Enrico ; Poletti, Enea ; Ruggeri, Alfredo

  • Author_Institution
    Dept. of Inf. Eng., Univ. of Padova, Padova, Italy
  • Volume
    13
  • Issue
    4
  • fYear
    2009
  • fDate
    7/1/2009 12:00:00 AM
  • Firstpage
    575
  • Lastpage
    581
  • Abstract
    Karyotype analysis is a widespread procedure in cytogenetics to assess the possible presence of genetics defects. The procedure is lengthy and repetitive, so that an automatic analysis would greatly help the cytogeneticist routine work. Still, automatic segmentation and full disentangling of chromosomes are open issues. We propose an automatic procedure to obtain the separated chromosomes, which are then ready for a subsequent classification step. The segmentation is carried out by means of a space-variant thresholding scheme, which proved to be successful even in presence of hyper- or hypofluorescent regions in the image. Then, the tree of choices to resolve touching and overlapping chromosomes is recursively explored, choosing the best combination of cuts and overlaps based on geometric evidence and image information. We show the effectiveness of the proposed method on routine data acquired with different microscope-camera setup at different laboratories: from 162 images of 117 cells totaling 6683 chromosomes, 94% of the chromosomes were correctly segmented, solving 90% of the overlaps and 90% of the touchings. In order to provide the scientific community with a public dataset, the data used in this paper are available for public download.
  • Keywords
    biomedical optical imaging; cellular biophysics; fluorescence; genetics; image classification; image segmentation; medical image processing; recursive estimation; Q-band prometaphase images; automatic segmentation procedure; chromosome disentanglement; cytogenetics; genetics defects; geometric evidence; hyperfluorescent regions; hypofluorescent regions; image classification; image information; karyotype analysis; microscope-camera setup; recursive estimation; space-variant thresholding scheme; Adjacent chromosomes; chromosome analysis; image segmentation; karyotyping; overlapping chromosomes; Algorithms; Chromosomes, Human; Cluster Analysis; Humans; Image Processing, Computer-Assisted; Karyotyping; Prometaphase;
  • fLanguage
    English
  • Journal_Title
    Information Technology in Biomedicine, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1089-7771
  • Type

    jour

  • DOI
    10.1109/TITB.2009.2014464
  • Filename
    4773198