OBJECTIVE: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical practice. We aimed to compare the accuracy of CR interpretation a...
INTRODUCTION: Despite a growing interest in lung MRI, its broader use in a clinical setting remains challenging. Several factors limit the image quality of lung MRI, such as the extremely short T2 and T2* relaxation times of the lung parenchyma and c...
Today, as in every life-threatening disease, early diagnosis of brain tumors plays a life-saving role. The brain tumor is formed by the transformation of brain cells from their normal structures into abnormal cell structures. These formed abnormal ce...
PURPOSE: To develop a deep learning-based method for rapid liver proton-density fat fraction (PDFF) and R * quantification with built-in uncertainty estimation using self-gated free-breathing stack-of-radial MRI.
The purpose of the current study was to develop a deep learning technique called Golden-angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast-enhanced 4D MRI acquired with golden-angle radial k-space trajectories...
PURPOSE: Subject-tailored parallel transmission pulses for ultra-high fields body applications are typically calculated based on subject-specific -maps of all transmit channels, which require lengthy adjustment times. This study investigates the fea...
Cardiovascular magnetic resonance (CMR) can measure ventricular volumes for the quantitative assessment of cardiac function in clinical cardiology. Conventionally, CMR volumetric measurements require image reconstruction and segmentation. There are l...
Journal of voice : official journal of the Voice Foundation
Sep 23, 2022
OBJECTIVE: Adductor spasmodic dysphonia (AdSD) is a neurogenic dystonia, which causes spasms of the laryngeal muscles. This disorder mainly affects production of connected speech. To understand how AdSD affects vocal fold (VF) movements and hence, th...
Deep learning (DL) enables the creation of computational models comprising multiple processing layers that learn data representations at multiple levels of abstraction. In the recent past, the use of deep learning has been proliferating, yielding pro...
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