AI Medical Compendium Topic:
Mammography

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Representation learning for mammography mass lesion classification with convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The automatic classification of breast imaging lesions is currently an unsolved problem. This paper describes an innovative representation learning framework for breast cancer diagnosis in mammography that integrates deep le...

Sample Selection for Training Cascade Detectors.

PloS one
Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represe...

Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution.

Computer methods and programs in biomedicine
Breast cancer is one of the most perilous diseases among women. Breast screening is a method of detecting breast cancer at a very early stage which can reduce the mortality rate. Mammography is a standard method for the early diagnosis of breast canc...

Robot guidance of an ultrasound probe toward a 3D region of interest detected through X-ray mammography.

International journal of computer assisted radiology and surgery
PURPOSE: This research is situated in the context of breast cancer detection where the standard procedure is the succession of an initial mammography (MX) examination and a supplementary ultrasound (US) scan. One major difficulty of this procedure re...

Assessment of a Four-View Mammographic Image Feature Based Fusion Model to Predict Near-Term Breast Cancer Risk.

Annals of biomedical engineering
The purpose of this study was to develop and assess a new quantitative four-view mammographic image feature based fusion model to predict the near-term breast cancer risk of the individual women after a negative screening mammography examination of i...

Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also ...

Using natural language processing to extract mammographic findings.

Journal of biomedical informatics
OBJECTIVE: Structured data on mammographic findings are difficult to obtain without manual review. We developed and evaluated a rule-based natural language processing (NLP) system to extract mammographic findings from free-text mammography reports.

An integrated breast cancer risk assessment and management model based on fuzzy cognitive maps.

Computer methods and programs in biomedicine
BACKGROUND: There is a growing demand for women to be classified into different risk groups of developing breast cancer (BC). The focus of the reported work is on the development of an integrated risk prediction model using a two-level fuzzy cognitiv...

Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.

Artificial intelligence in medicine
OBJECTIVE: This work addresses the theoretical description and experimental evaluation of a new feature selection method (named uFilter). The uFilter improves the Mann-Whitney U-test for reducing dimensionality and ranking features in binary classifi...