AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Automatic Detection of Masses in Mammograms Using Quality Threshold Clustering, Correlogram Function, and SVM.

Journal of digital imaging
Breast cancer is the second most common type of cancer in the world. Several computer-aided detection and diagnosis systems have been used to assist health experts and to indicate suspect areas that would be difficult to perceive by the human eye; th...

Comparative analysis of breast cancer detection in mammograms and thermograms.

Biomedizinische Technik. Biomedical engineering
In this paper, we present a system based on feature extraction techniques for detecting abnormal patterns in digital mammograms and thermograms. A comparative study of texture-analysis methods is performed for three image groups: mammograms from the ...

On the Automated Segmentation of Epicardial and Mediastinal Cardiac Adipose Tissues Using Classification Algorithms.

Studies in health technology and informatics
The quantification of fat depots on the surroundings of the heart is an accurate procedure for evaluating health risk factors correlated with several diseases. However, this type of evaluation is not widely employed in clinical practice due to the re...

An Approach for Automatic Classification of Radiology Reports in Spanish.

Studies in health technology and informatics
Automatic detection of relevant terms in medical reports is useful for educational purposes and for clinical research. Natural language processing (NLP) techniques can be applied in order to identify them. In this work we present an approach to class...

Sampling from Determinantal Point Processes for Scalable Manifold Learning.

Information processing in medical imaging : proceedings of the ... conference
High computational costs of manifold learning prohibit its application for large datasets. A common strategy to overcome this problem is to perform dimensionality reduction on selected landmarks and to successively embed the entire dataset with the N...

Multi-scale Convolutional Neural Networks for Lung Nodule Classification.

Information processing in medical imaging : proceedings of the ... conference
We investigate the problem of diagnostic lung nodule classification using thoracic Computed Tomography (CT) screening. Unlike traditional studies primarily relying on nodule segmentation for regional analysis, we tackle a more challenging problem on ...