Fourth Canadian Conference on Computer and Robot Vision (CRV '07)
Automated Detection of Mitosis in Embryonic Tissues
Montreal, Quebec, Canada
May 28-May 30
ISBN: 0-7695-2786-8
Characterization of mitosis is important for understanding the mechanisms of development in early stage embryos. In studies of cancer, another situation in which mitosis is of interest, the tissue is stained with contrast agents before mitosis characterization; an intervention that could lead to atypical development in live embryos. A new image processing algorithm that does not rely on the use of contrast agents was developed to detect mitosis in embryonic tissue. Unlike previous approaches that uses still images, the algorithm presented here uses temporal information from timelapse images to track the deformation of the embryonic tissue and then uses changes in intensity at tracked regions to identify the locations of mitosis. On a one hundred minute image sequence, consisting of twenty images, the algorithm successfully detected eighty-one out of the ninety-five mitosis. The performance of the algorithm is calculated using the geometric mean measure as 82%. Since no other method to count mitoses in live tissues is known, comparisons with the present results could not be made.
Citation:
Parthipan Siva, G. Wayne Brodland, David Clausi, "Automated Detection of Mitosis in Embryonic Tissues," crv, pp.97-104, Fourth Canadian Conference on Computer and Robot Vision (CRV '07), 2007