AIMC Topic:
Image Interpretation, Computer-Assisted
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Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI.
Radiology
Nov 13, 2018
Purpose To compare the diagnostic performance of radiomic analysis (RA) and a convolutional neural network (CNN) to radiologists for classification of contrast agent-enhancing lesions as benign or malignant at multiparametric breast MRI. Materials an...
A machine learning texture model for classifying lung cancer subtypes using preliminary bronchoscopic findings.
Medical physics
Nov 8, 2018
PURPOSE: Bronchoscopy is useful in lung cancer detection, but cannot be used to differentiate cancer types. A computer-aided diagnosis (CAD) system was proposed to distinguish malignant cancer types to achieve objective diagnoses.
A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using F-FDG PET of the Brain.
Radiology
Nov 6, 2018
Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or neither at fluorine 18 (F) fluorodeoxyglucose (FDG) PET of the brain and compare its performance to t...
Fundus images analysis using deep features for detection of exudates, hemorrhages and microaneurysms.
BMC ophthalmology
Nov 6, 2018
BACKGROUND: Convolution neural networks have been considered for automatic analysis of fundus images to detect signs of diabetic retinopathy but suffer from low sensitivity.
Artificial Intelligence in Radiology: Current Technology and Future Directions.
Seminars in musculoskeletal radiology
Nov 6, 2018
Artificial intelligence (AI) has been heralded as the next big wave in the computing revolution and touted as a transformative technology for many industries including health care. In radiology, considerable excitement and anxiety are associated with...
Visual attention mechanism and support vector machine based automatic image annotation.
PloS one
Nov 6, 2018
Automatic image annotation not only has the efficiency of text-based image retrieval but also achieves the accuracy of content-based image retrieval. Users of annotated images can locate images they want to search by providing keywords. Currently mos...
Unsupervised Feature Extraction via Deep Learning for Histopathological Classification of Colon Tissue Images.
IEEE transactions on medical imaging
Nov 2, 2018
Histopathological examination is today's gold standard for cancer diagnosis. However, this task is time consuming and prone to errors as it requires a detailed visual inspection and interpretation of a pathologist. Digital pathology aims at alleviati...
A graph-based lesion characterization and deep embedding approach for improved computer-aided diagnosis of nonmass breast MRI lesions.
Medical image analysis
Nov 2, 2018
Nonmass-like enhancements are a common but diagnostically challenging finding in breast MRI. Nonmass-like lesions can be described as clusters of spatially and temporally inter-connected regions of enhancements, so they can be modeled as networks and...
Learning-Based Quality Control for Cardiac MR Images.
IEEE transactions on medical imaging
Nov 1, 2018
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the potential occurrence of imaging artifacts, such as cardiac...
Direct Segmentation-Based Full Quantification for Left Ventricle via Deep Multi-Task Regression Learning Network.
IEEE journal of biomedical and health informatics
Nov 1, 2018
Quantitative analysis of the heart is extremely necessary and significant for detecting and diagnosing heart disease, yet there are still some challenges. In this study, we propose a new end-to-end segmentation-based deep multi-task regression learni...
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