TY - GEN
T1 - Towards building computerized image analysis framework for nucleus discrimination in microscopy images of diffuse glioma
AU - Kong, Jun
AU - Cooper, Lee
AU - Kurc, Tahsin
AU - Brat, Daniel
AU - Saltz, Joel
PY - 2011
Y1 - 2011
N2 - As an effort to build an automated and objective system for pathologic image analysis, we present, in this paper, a computerized image processing method for identifying nuclei, a basic biological unit of diagnostic utility, in microscopy images of glioma tissue samples. The complete analysis includes multiple processing steps, involving mode detection with color and spatial information for pixel clustering, background normalization leveraging morphological operations, boundary refinement with deformable models, and clumped nuclei separation using watershed. In aggregate, our validation dataset includes 220 nuclei from 11 distinct tissue regions selected at random by an experienced neuropathologist. Computerized nuclei detection results are in good concordance with human markups by both visual appraisement and quantitative measures. We compare the performance of the proposed analysis algorithm with that of CellProfiler, a classical analysis software for cell image process, and present the superiority of our method to CellProfiler.
AB - As an effort to build an automated and objective system for pathologic image analysis, we present, in this paper, a computerized image processing method for identifying nuclei, a basic biological unit of diagnostic utility, in microscopy images of glioma tissue samples. The complete analysis includes multiple processing steps, involving mode detection with color and spatial information for pixel clustering, background normalization leveraging morphological operations, boundary refinement with deformable models, and clumped nuclei separation using watershed. In aggregate, our validation dataset includes 220 nuclei from 11 distinct tissue regions selected at random by an experienced neuropathologist. Computerized nuclei detection results are in good concordance with human markups by both visual appraisement and quantitative measures. We compare the performance of the proposed analysis algorithm with that of CellProfiler, a classical analysis software for cell image process, and present the superiority of our method to CellProfiler.
UR - https://www.scopus.com/pages/publications/84864578666
U2 - 10.1109/IEMBS.2011.6091629
DO - 10.1109/IEMBS.2011.6091629
M3 - Conference contribution
C2 - 22255853
SN - 9781424441211
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 6605
EP - 6608
BT - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
T2 - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Y2 - 30 August 2011 through 3 September 2011
ER -