AIMC Topic:
Image Interpretation, Computer-Assisted
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A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images.
Computer methods and programs in biomedicine
Mar 21, 2017
Accurately assessment of adipose tissue volume inside a human body plays an important role in predicting disease or cancer risk, diagnosis and prognosis. In order to overcome limitation of using only one subjectively selected CT image slice to estima...
Machine learning of the spatio-temporal characteristics of echocardiographic deformation curves for infarct classification.
The international journal of cardiovascular imaging
Mar 20, 2017
The aim of this study was to analyze the whole temporal profiles of the segmental deformation curves of the left ventricle (LV) and describe their interrelations to obtain more detailed information concerning global LV function in order to be able to...
Case-Control Studies
Diagnosis, Computer-Assisted
Time Factors
Biomechanical Phenomena
Ventricular Function, Left
Severity of Illness Index
Myocardial Infarction
Image Interpretation, Computer-Assisted
Observer Variation
Automation
Magnetic Resonance Imaging
Predictive Value of Tests
Principal Component Analysis
Machine Learning
Reproducibility of Results
Humans
Pattern Recognition, Automated
Echocardiography, Doppler, Color
Myocardial Contraction
Decision Support System for Detection of Papilledema through Fundus Retinal Images.
Journal of medical systems
Mar 10, 2017
A condition in which the optic nerve inside the eye is swelled due to increased intracranial pressure is known as papilledema. The abnormalities due to papilledema such as opacification of Retinal Nerve Fiber Layer (RNFL), dilated optic disc capillar...
Deep Learning in Medical Image Analysis.
Annual review of biomedical engineering
Mar 9, 2017
This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the ...
A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning.
Computers in biology and medicine
Mar 6, 2017
Breast cancer is a common cancer among women. With the development of modern medical science and information technology, medical imaging techniques have an increasingly important role in the early detection and diagnosis of breast cancer. In this pap...
An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.
Computers in biology and medicine
Feb 22, 2017
INTRODUCTION: Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture...
Analysis of facial expressions in parkinson's disease through video-based automatic methods.
Journal of neuroscience methods
Feb 20, 2017
BACKGROUND: The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson's disease (PD), which is a major motor sign of this neu...
Machine Learning for Medical Imaging.
Radiographics : a review publication of the Radiological Society of North America, Inc
Feb 17, 2017
Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine lear...
A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Feb 13, 2017
The treatment and management of early stage estrogen receptor positive (ER+) breast cancer is hindered by the difficulty in identifying patients who require adjuvant chemotherapy in contrast to those that will respond to hormonal therapy. To distingu...
An interactive medical image segmentation framework using iterative refinement.
Computers in biology and medicine
Feb 13, 2017
Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results...
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