Follicular Lymphoma (FL) is a cancer arising from the lymphatic system. Originating from follicle center B cells, FL is
mainly comprised of centrocytes (usually middle-to-small sized cells) and centroblasts (relatively large malignant cells).
According to the World Health Organization's recommendations, there are three histological grades of FL characterized
by the number of centroblasts per high-power field (hpf) of area 0.159 mm2. In current practice, these cells are manually
counted from ten representative fields of follicles after visual examination of hematoxylin and eosin (H&E) stained
slides by pathologists. Several studies clearly demonstrate the poor reproducibility of this grading system with very low
inter-reader agreement. In this study, we are developing a computerized system to assist pathologists with this process. A
hybrid approach that combines information from several slides with different stains has been developed. Thus, follicles
are first detected from digitized microscopy images with immunohistochemistry (IHC) stains, (i.e., CD10 and CD20).
The average sensitivity and specificity of the follicle detection tested on 30 images at 2×, 4× and 8× magnifications are
85.5±9.8% and 92.5±4.0%, respectively. Since the centroblasts detection is carried out in the H&E-stained slides, the
follicles in the IHC-stained images are mapped to H&E-stained counterparts. To evaluate the centroblast differentiation
capabilities of the system, 11 hpf images have been marked by an experienced pathologist who identified 41 centroblast
cells and 53 non-centroblast cells. A non-supervised clustering process differentiates the centroblast cells from noncentroblast
cells, resulting in 92.68% sensitivity and 90.57% specificity.