Medical images indexation and annotation

Abstract

Computer aided detection and diagnosis CADe/CADx systems, are an essential tools used by physicians to assist them in their daily clinical diagnosis. In cancers diseases, these systems have an important role to perform the early detection and diagnosis, this allows to provide early treatment before it will be too late. In this thesis, we present several methods to be uses in a computer aided diagnosis system in order to generate structured reports of liver lesions including cancer using Computed Tomography (CT) images. In addition, we propose different methods for computer aided detection of breast cancer, by treating breast density classification using mammography and breast lesion classification using histopathology images. At this context we present three distingue contributions, the first one is related to the annotation of liver CT images by using a medical ontology, in which we propose three methods. The second contribution is about breast density classification according to the standard Breast Imaging Reporting and Data System (BI-RADS). In addition to that, we propose an improved version of Synthetic Minority Over-Sampling Technique Algorithm (SMOTE) used to equilibrate the dataset. The last contribution is about breast lesions classification in the histopathology images. Precisely, we propose a method to distinct benignant and malignant lesions, as well to classify the normal cases, benign cases, in situ and invasive cancer cases.