TOWARDS AN INTELLIGENT APPROACH FOR THE DETECTION AND CLASSIFICATION OF CANCER OF THE LYMPHATIC SYSTEM

Abstract

Determiningcanceranditstypeisaverydifficulttaskthatrequireshighmedicalexpertiseandskills. With the development of image classification techniques, deep learning strategies haveoccupied the first positions in many medical image classification systems as part of computeraidedecision (CAD). Theaimofthisstudyistoaccuratelyclassifylymphomasubtypesusingdeeplearning.Adeeplearning framework has been proposed to classify three types of lymphomas as follicularlymphoma (FL), chronic lymphocytic lymphoma (CLL) and Mantle Cell Lymphoma (MCL) byfollowing pretrained CNN models (Transfer learning) such as Resnet and VGG and based onthe available dataset from the National Institute on Aging (NIA). The data Patching wasimplemented for the first step of data processing, where the achieved results show that theproposedmodels wereable toachievebetterresults comparedto CNNbuilt fromscratch.