AIMC Topic: Image Enhancement
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Deep principal dimension encoding for the classification of early neoplasia in Barrett's Esophagus with volumetric laser endomicroscopy.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 24, 2020
Barrett cancer is a treatable disease when detected at an early stage. However, current screening protocols are often not effective at finding the disease early. Volumetric Laser Endomicroscopy (VLE) is a promising new imaging tool for finding dyspla...
An improved deep network for tissue microstructure estimation with uncertainty quantification.
Medical image analysis
Jan 22, 2020
Deep learning based methods have improved the estimation of tissue microstructure from diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients. These methods learn the mapping from diffusion signals in ...
Super-resolution of cardiac magnetic resonance images using Laplacian Pyramid based on Generative Adversarial Networks.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 3, 2020
BACKGROUND AND OBJECTIVE: Cardiac magnetic resonance imaging (MRI) can assist in both functional and structural analysis of the heart, but due to hardware and physical limitations, high-resolution MRI scans is time consuming and peak signal-to-noise ...
A robust deep neural network for denoising task-based fMRI data: An application to working memory and episodic memory.
Medical image analysis
Nov 26, 2019
In this study, a deep neural network (DNN) is proposed to reduce the noise in task-based fMRI data without explicitly modeling noise. The DNN artificial neural network consists of one temporal convolutional layer, one long short-term memory (LSTM) la...
Optimizing MRF-ASL scan design for precise quantification of brain hemodynamics using neural network regression.
Magnetic resonance in medicine
Nov 21, 2019
PURPOSE: Arterial Spin Labeling (ASL) is a quantitative, non-invasive alternative for perfusion imaging that does not use contrast agents. The magnetic resonance fingerprinting (MRF) framework can be adapted to ASL to estimate multiple physiological ...
Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks.
Scientific reports
Nov 15, 2019
Labeled medical imaging data is scarce and expensive to generate. To achieve generalizable deep learning models large amounts of data are needed. Standard data augmentation is a method to increase generalizability and is routinely performed. Generati...
Assessment of ventricular tachyarrhythmia in patients with hypertrophic cardiomyopathy with machine learning-based texture analysis of late gadolinium enhancement cardiac MRI.
Diagnostic and interventional imaging
Nov 11, 2019
OBJECTIVE: To assess the diagnostic value of machine learning-based texture feature analysis of late gadolinium enhancement images on cardiac magnetic resonance imaging (MRI) for assessing the presence of ventricular tachyarrhythmia (VT) in patients ...
SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.
NeuroImage. Clinical
Nov 9, 2019
White matter hyperintensities (WMHs) of presumed vascular origin are frequently observed in magnetic resonance images (MRIs) of the elderly. Detection and quantification of WMHs is important to help doctors make diagnoses and evaluate prognosis of th...
Segmentation and quantification of infarction without contrast agents via spatiotemporal generative adversarial learning.
Medical image analysis
Oct 4, 2019
Accurate and simultaneous segmentation and full quantification (all indices are required in a clinical assessment) of the myocardial infarction (MI) area are crucial for early diagnosis and surgical planning. Current clinical methods remain subject t...
PV-LVNet: Direct left ventricle multitype indices estimation from 2D echocardiograms of paired apical views with deep neural networks.
Medical image analysis
Sep 10, 2019
Accurate direct estimation of the left ventricle (LV) multitype indices from two-dimensional (2D) echocardiograms of paired apical views, i.e., paired apical four-chamber (A4C) and two-chamber (A2C), is of great significance to clinically evaluate ca...
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