Abstract
We propose a technique for analyzing images of immunohistochemically
stained tissue samples for extracting features that correlate
with patient disease. We address the problem of quantifying tumor tissue
and segmenting and counting nuclei. Our method utilizes a flexible segmentation
technique trained from representative image samples. Nuclei
counting is based on a nucleus model that takes size, shape and nucleus
probability into account. We obtain the probability of a nucleus from
our segmentation procedure. Our method is experimentally validated on
images stained with nuclear markers for the Estrogen Receptor (ER)
and proliferation marker KI-67. In addition we qualitatively validate our
method for tumor tissue segmentation and we obtain state of the art
results on cell nuclei separation.
| Original language | English |
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| Title of host publication | Proceedings of the MICCAI workshop on Histopathology Image Analysis |
| Publication date | 2011 |
| Publication status | Published - 2011 |
| Event | MICCAI workshop on Histopathology Image Analysis : Clinical Challenges and Quantitative Image Analysis Solutions - Toronto, Canada Duration: 1 Jan 2011 → … |
Conference
| Conference | MICCAI workshop on Histopathology Image Analysis : Clinical Challenges and Quantitative Image Analysis Solutions |
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| City | Toronto, Canada |
| Period | 01/01/2011 → … |