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In this paper, a novel automated method to recognize centroblast (CB) cells from non-centroblast (non-CB) cells in follicular lymphoma cases is developed and its performance is evaluated against consensus of 30 board-certified hematopathologists. Morphometric and color texture features are used in the training and testing of a supervised quadratic discriminate analysis (QDA) classifier. The novelty...
Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL has a variable clinical course, and important clinical treatment decisions for FL patients are based on histological grading, which is done by manually counting the large malignant cells called centroblasts (CB) in ten standard microscopic high-power fields from H&E-stained tissue sections. This method...
In this paper, a novel color texture classification approach is introduced and applied to computer-assisted grading of follicular lymphoma from whole-slide tissue samples. The digitized tissue samples of follicular lymphoma were classified into histological grades under a statistical framework. The proposed method classifies the image either into low or high grades based on the amount of cytological...
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