AIMC Topic: Breast Neoplasms

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Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

Computational intelligence and neuroscience
Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonpara...

Disentangling multidimensional spatio-temporal data into their common and aberrant responses.

PloS one
With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidime...

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...

Cytotoxic response of platinum-coated gold nanorods in human breast cancer cells at very low exposure levels.

Environmental toxicology
Because of unique optical behavior gold nanorods (GNRs) have attracted attention for the application in biomedical field such as bio-sensing, bio-imaging and hyperthermia. However, toxicological response of GNRs is controversial due to their differen...

A novel technique for robot assisted latissimus dorsi flap harvest.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: A robotic surgery technique of harvesting the latissimus dorsi muscle flap has technical advantages over endoscopic harvest and cosmetic advantages over the open technique. The authors introduce a new transaxillary gasless technique using...

Robust phase-based texture descriptor for classification of breast ultrasound images.

Biomedical engineering online
BACKGROUND: Classification of breast ultrasound (BUS) images is an important step in the computer-aided diagnosis (CAD) system for breast cancer. In this paper, a novel phase-based texture descriptor is proposed for efficient and robust classifiers t...

Bio-optics based sensation imaging for breast tumor detection using tissue characterization.

Sensors (Basel, Switzerland)
The tissue inclusion parameter estimation method is proposed to measure the stiffness as well as geometric parameters. The estimation is performed based on the tactile data obtained at the surface of the tissue using an optical tactile sensation imag...

Applying under-sampling techniques and cost-sensitive learning methods on risk assessment of breast cancer.

Journal of medical systems
Breast cancer is one of the most common cause of cancer mortality. Early detection through mammography screening could significantly reduce mortality from breast cancer. However, most of screening methods may consume large amount of resources. We pro...

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 ...