A general framework for the segmentation of follicular lymphoma virtual slides.
Follicular lymphoma (FL) is one of the most common types of non-Hodgkin's lmphomas in the world. Diagnosis of FL is based on morphological and immunohistochemical characteristics found on tissue sections. Our project's aim is to develop computer-aided analysis tools on virtual slide images (VSI) of lymphoid tissues with the purpose of improving the FL grading performed in malignant follicles. In this paper, we focus on the first step of our work, an automated system for detecting follicles in VSI of lymphoid tissues. To mimic the human expert process, the system works on low-resolution CD20 images and maps the follicle boundaries on high-resolution H&E images.
Department of Biomedical Informatics, The Ohio State University, 3185 Graves Hall, 333W. 10th Avenue, Columbus, OH 43210, USA.
Myriam
M
Oger
Philippe
P
Belhomme
Metin N
MN
Gurcan
D000465:Algorithms; D001706:Biopsy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008224:Lymphoma, Follicular / Q000473:pathology*; D008853:Microscopy / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface