A CAD System Framework for the Automatic Diagnosis and Annotation of Histological and Bone Marrow Images
Subject Areas : F.2.7. Optimization
1 - Department of Computer Science, Khoy Branch, Islamic Azad University, khoy, Iran
Keywords: CAD, supervised Learning, SVM Algorithm, Context Features,
Abstract :
Due to ever increasing of medical images data in the world’s medical centers and recent developments in hardware and technology of medical imaging, necessity of medical data software analysis is needed. Equipping medical science with intelligent tools in diagnosis and treatment of illnesses has resulted in reduction of physicians’ errors and physical and financial damages. In this article we propose a computer – aided diagnosis system framework in order to automatic classification and annotation of histological and bone marrow images. The proposed method has been tested on two data set including cytological and histological images. Images context features are used to train support vector machine classifier and the accuracy of classifier is 96%. Results show that the proposed framework can be a software model in order to classify and annotate microscopic images in clinical routine functions. Due to ever increasing of medical images data in the world’s medical centers and recent developments in hardware and technology of medical imaging, necessity of medical data software analysis is needed. Equipping medical science with intelligent tools in diagnosis and treatment of illnesses has resulted in reduction of physicians’ errors and physical and financial damages. In this article we propose a computer – aided diagnosis system framework in order to automatic classification and annotation of histological and bone marrow images.