PASuite: A preprocessing algorithm suite for cellular and molecular image classification in cancer diagnosis and treatment

We present a generalized tool to mark and preprocess cancerous regions in an image. Currently, tissue biopsies are analyzed and graded manually by expert pathologists and thus can be time consuming and challenging due to variations in tissue morphology, inconsistencies in preparation of tissue specimen and errors in the image acquisition process. Our tool is designed to automatically standardize the variations in different images due to changing illumination and experimental conditions. Segregating cancerous regions from non-cancerous areas is a mandatory step before extracting relevant information from cancer images such as the number and size of nuclei and subsequently using it for classification and quantitative analysis. We tested our tool for two completely different cancers: Head and Neck Cancer (HNC) and Renal Cell Carcinoma (RCC). The tool enables the user to successfully segment the cancerous areas for both types of cancers and our results match with the manual validation by a pathologist.