Barnes Michael,Chefd'hotel Christophe,Chukka Srinivas,Nguyen Kien
申请号：
US201715418632
公开号：
US2017140246(A1)
申请日:
2017.01.27
申请国别(地区):
美国
年份:
2017
代理人:
摘要：
Methods, systems, and apparatuses for automatically identifying glandular regions and tubule regions in a breast tissue sample are provided. An image of breast tissue is analyzed to detect nuclei and lumen candidates, identify tumor nuclei and true lumen from the candidates, and group tumor nuclei with neighboring tumor nuclei and lumina to define tubule glandular regions and non-tubule glandular regions of the image. Learnt supervised classifiers, such as random forest classifiers, can be applied to identify and classify the tumor nuclei and true lumina. Graph-cut methods can be applied to group the tumor nuclei and lumina and to define the tubule glandular regions and non-tubule glandular regions. The analysis can be applied to whole slide images and can resolve tubule areas with multiple layers of nuclei.
