Breast Cancer Detection Using Combination Of Feature Extraction Models.

      Аннотация: The Chapter 1 discusses about the Breast Cancer and Oveview of the report. The Chapter 2 discusses about the existing works related to detection of breast cancer, Proposed work and System analysis. The Chapter 3 discusses about the enhancement methods used for extraction and feature extraction techniques. The Chapter 4 discusses about the implementation part, which compares the textual features of multiple mammogram images using textual parameters. The proposed system presents intelligibility mammogram enhancement method (IMEM) for obtaining the best quality of mammogram images. Proposed IMEM produces the high quality of mammogram images which are taken as sources of ROI segmentation for attaining of best segmented images. The Chapter 5 discusses about the result analysis classification of mammogram images were performed using feature extraction method . The Chapter 6 ends this book with conclusion followed by references.

Ключевые слова: breast cancer, cnr, Supervised Learning, unsupervised learning, Median filters and contrast stretching, Histogram of Oriented Gradients, ROI segmentation