The purpose of this research was to implement a deep learning network to overcome two of the major bottlenecks in improved image reconstruction for clinical positron emission tomography (PET). These are the lack of an automated means for the optimiza...
A Fully Convolutional Network (FCN) based deep architecture called Dual Path U-Net (DPU-Net) is proposed for automatic segmentation of the lumen and media-adventitia in IntraVascular UltraSound (IVUS) frames, which is crucial for diagnosis of many ca...
Medical & biological engineering & computing
Mar 21, 2019
Laryngeal endoscopy is one of the primary diagnostic tools for laryngeal disorders. The main techniques are videostroboscopy and lately high-speed video endoscopy. Unfortunately, due to the restricting anatomy of the larynx and technical limitations ...
We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can enhance the resolution of both pixel size-limited and diffraction-lim...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 31, 2018
Radiomics - The extraction of quantitative features from radiologic images - shows increasing potential in contributing to modern personalized medicine approaches. MITK Phenotyping is an openly distributed radiomics framework implementing an exhausti...
Attention maps have been fused in the VggNet structure (EAC-Net) [1] and have shown significant improvement compared to that of the VggNet structure. However, in [1], E-Net was designed based on the facial action unit (AU) center and for facial AU de...
OBJECTIVE: The aim of this paper is to investigate the use of fully convolutional neural networks (FCNNs) to segment scar tissue in the left ventricle from cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) images.
Lens-free digital in-line holography (LDIH) is a promising microscopic tool that overcomes several drawbacks (e.g., limited field of view) of traditional lens-based microcopy. However, extensive computation is required to reconstruct object images fr...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 15, 2018
For myocardial infarction (MI) patients, delayed enhancement (DE) and T2-weighted cardiovascular magnetic resonance imaging (CMR) can play significant roles in diagnosis, prognosis and therapeutic strategy evaluation. However, the non-rigid registrat...
OBJECTIVE: To investigate the classification ability of quantitative radiomics features extracted on non-contrast-enhanced CT (NECT) image for discrimination of AVM-related hematomas from those caused by other etiologies.
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