OBJECTIVE: To develop an automated, reproducible epithelial cell nuclear segmentation method to quantify cytologic features quickly and accurately from breast biopsy. STUDY DESIGN: The method, based on fuzzy c-mean clustering of the hue-band of color images and the watershed transform, was applied to 39 images from 3 histologic types (typical hyperplasia, atypical hyperplasia, and ductal carcinoma in situ [cribriform and solid]). RESULTS: The performance of the segmentation algorithm was evaluated by visually determining the percentage of badly segmented nuclei (approximately 25% for all types), the percentage of nuclei that remained in clumps (4.5-16.7%) and the percentage of missed nuclei (0.4-1.5%) for each image. CONCLUSION: The segmentation algorithm was sensitive in that a small percentage of nuclei were missed. However, the percentage of badly segmented nuclei was on the order of 25%, and the percentage of nuclei that remained in clumps was on the order of 10% of the total number of nuclei in the duct. Even so, > 600 nuclei per duct, on average, were segmented correctly; that was a sufficient number by which to calculate accurate quantitative, cytologic, morphometric measurements of epithelial cell nuclei in stained tissue sections of breast biopsy.
OBJECTIVE: To develop an automated, reproducible epithelial cell nuclear segmentation method to quantify cytologic features quickly and accurately from breast biopsy. STUDY DESIGN: The method, based on fuzzy c-mean clustering of the hue-band of color images and the watershed transform, was applied to 39 images from 3 histologic types (typical hyperplasia, atypical hyperplasia, and ductal carcinoma in situ [cribriform and solid]). RESULTS: The performance of the segmentation algorithm was evaluated by visually determining the percentage of badly segmented nuclei (approximately 25% for all types), the percentage of nuclei that remained in clumps (4.5-16.7%) and the percentage of missed nuclei (0.4-1.5%) for each image. CONCLUSION: The segmentation algorithm was sensitive in that a small percentage of nuclei were missed. However, the percentage of badly segmented nuclei was on the order of 25%, and the percentage of nuclei that remained in clumps was on the order of 10% of the total number of nuclei in the duct. Even so, > 600 nuclei per duct, on average, were segmented correctly; that was a sufficient number by which to calculate accurate quantitative, cytologic, morphometric measurements of epithelial cell nuclei in stained tissue sections of breast biopsy.
Authors: J C Sieren; J Weydert; A Bell; B De Young; A R Smith; J Thiesse; E Namati; Geoffrey McLennan Journal: Ann Biomed Eng Date: 2010-06-23 Impact factor: 3.934
Authors: Hang Chang; Ju Han; Alexander Borowsky; Leandro Loss; Joe W Gray; Paul T Spellman; Bahram Parvin Journal: IEEE Trans Med Imaging Date: 2012-12-04 Impact factor: 10.048
Authors: Hang Chang; Gerald V Fontenay; Ju Han; Ge Cong; Frederick L Baehner; Joe W Gray; Paul T Spellman; Bahram Parvin Journal: BMC Bioinformatics Date: 2011-12-20 Impact factor: 3.169
Authors: Stephan Wienert; Daniel Heim; Kai Saeger; Albrecht Stenzinger; Michael Beil; Peter Hufnagl; Manfred Dietel; Carsten Denkert; Frederick Klauschen Journal: Sci Rep Date: 2012-07-11 Impact factor: 4.379