Cancer is a group of diseases involving abnormal cell growth with varying malignancy and extent across different patients. Cytological features like prominent nucleoli, nuclear enlargement, and hyperchromasia are important to the tumor pathologist in assessment of cancer malignancy from tissue biopsies. In a recent study, Yap et al.  proposed effective prominent nucleoli detectors in histopathological images and developed different feature generation methods.
Giron Danilo Medina
Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues.