Automated detection of mitosis in embryonic tissues

被引:6
作者
Siva, Parthipan [1 ]
Brodland, G. Wayne [2 ]
Clausi, David [1 ]
机构
[1] Univ Waterloo, VIP Lab, Waterloo, ON N2L 3G1, Canada
[2] Univ Waterloo, Embryo Biomech Grp, Waterloo, ON N2L 3G1, Canada
来源
FOURTH CANADIAN CONFERENCE ON COMPUTER AND ROBOT VISION, PROCEEDINGS | 2007年
关键词
D O I
10.1109/CRV.2007.11
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 time-lapse 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.
引用
收藏
页码:97 / +
页数:2
相关论文
共 15 条
[1]   Computer simulations of mitosis and interdependencies between mitosis orientation, cell shape and epithelia reshaping [J].
Brodland, GW ;
Veldhuis, JH .
JOURNAL OF BIOMECHANICS, 2002, 35 (05) :673-681
[2]  
CLAUSI DA, 1993, DEVELOPMENT, V118, P1013
[3]  
DOUGHERTY ER, 2003, HANDS MORPHOLOGICAL, P290
[4]   PHASE-BASED DISPARITY MEASUREMENT [J].
FLEET, DJ ;
JEPSON, AD ;
JENKIN, MRM .
CVGIP-IMAGE UNDERSTANDING, 1991, 53 (02) :198-210
[5]  
Grewal M. S., 2001, KALMAN FILTERING THE, V4
[6]  
ILES P, THESIS U WATERLOO WA
[7]  
KAMAN EJ, 1984, CYTOMETRY, V5, P244, DOI 10.1002/cyto.990050305
[8]   Machine learning for the detection of oil spills in satellite radar images [J].
Kubat, M ;
Holte, RC ;
Matwin, S .
MACHINE LEARNING, 1998, 30 (2-3) :195-215
[9]  
PILET J, 2005, IEEE COMP SOC C COMP, V1, P822
[10]  
Refai H, 2003, 2003 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL 2, PROCEEDINGS, P1101