AIMC Topic:
Image Interpretation, Computer-Assisted
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Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists.
European radiology
Jun 11, 2019
OBJECTIVE: The purpose of this study was: To test whether machine learning classifiers for transition zone (TZ) and peripheral zone (PZ) can correctly classify prostate tumors into those with/without a Gleason 4 component, and to compare the performa...
A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jun 11, 2019
INTRODUCTION: It is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease (AD) dementia.
A Smart Dental Health-IoT Platform Based on Intelligent Hardware, Deep Learning, and Mobile Terminal.
IEEE journal of biomedical and health informatics
Jun 7, 2019
The dental disease is a common disease for a human. Screening and visual diagnosis that are currently performed in clinics possibly cost a lot in various manners. Along with the progress of the Internet of Things (IoT) and artificial intelligence, th...
Automatic brain tissue segmentation in fetal MRI using convolutional neural networks.
Magnetic resonance imaging
Jun 7, 2019
MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in fetal MRI is segmentation of the fetal brain into different tissue classes. Manual segment...
Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow.
Medical image analysis
Jun 6, 2019
We propose a method to classify cardiac pathology based on a novel approach to extract image derived features to characterize the shape and motion of the heart. An original semi-supervised learning procedure, which makes efficient use of a large amou...
Dual-domain convolutional neural networks for improving structural information in 3 T MRI.
Magnetic resonance imaging
Jun 5, 2019
We propose a novel dual-domain convolutional neural network framework to improve structural information of routine 3 T images. We introduce a parameter-efficient butterfly network that involves two complementary domains: a spatial domain and a freque...
Machine learning in resting-state fMRI analysis.
Magnetic resonance imaging
Jun 5, 2019
Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI. W...
SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction.
Magnetic resonance in medicine
Jun 5, 2019
PURPOSE: To develop and evaluate a novel deep learning-based reconstruction framework called SANTIS (Sampling-Augmented Neural neTwork with Incoherent Structure) for efficient MR image reconstruction with improved robustness against sampling pattern ...
Machine Learning-Based Three-Dimensional Echocardiographic Quantification of Right Ventricular Size and Function: Validation Against Cardiac Magnetic Resonance.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Jun 4, 2019
BACKGROUND: Three-dimensional echocardiography (3DE) allows accurate and reproducible measurements of right ventricular (RV) size and function. However, widespread implementation of 3DE in routine clinical practice is limited because the existing sof...
Artificial Intelligence in Musculoskeletal Imaging: Review of Current Literature, Challenges, and Trends.
Seminars in musculoskeletal radiology
Jun 4, 2019
Artificial intelligence (AI) has gained major attention with a rapid increase in the number of published articles, mostly recently. This review provides a general understanding of how AI can or will be useful to the musculoskeletal radiologist. After...
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