Magnetic resonance in chemistry : MRC
Sep 21, 2021
This paper presents a proof of concept of a method to identify substructures in 2D NMR spectra of mixtures using a bespoke image-based convolutional neural network application. This is done using HSQC and HMBC spectra separately and in combination. T...
PURPOSE: Supervised machine learning (ML) provides a compelling alternative to traditional model fitting for parameter mapping in quantitative MRI. The aim of this work is to demonstrate and quantify the effect of different training data distribution...
Background Patients who undergo surgery for cervical radiculopathy are at risk for developing adjacent segment disease (ASD). Identifying patients who will develop ASD remains challenging for clinicians. Purpose To develop and validate a deep learnin...
Seminars in musculoskeletal radiology
Sep 21, 2021
Computed tomography (CT) is most commonly used to produce three-dimensional (3D) models for evaluating bone and joint morphology in clinical practice. However, 3D models created from magnetic resonance imaging (MRI) data can be equally effective for ...
The purpose of this study is to investigate the robustness of a commonly used convolutional neural network for image segmentation with respect to nearly unnoticeable adversarial perturbations, and suggest new methods to make these networks more robus...
IEEE transactions on bio-medical engineering
Sep 20, 2021
OBJECTIVE: Cardiovascular diseases are the most common cause of global death. Endovascular interventions, in combination with advanced imaging technologies, are promising approaches for minimally invasive diagnosis and therapy. More recently, teleope...
MRI has helped clarify the relationship between pelvic anatomical structures and functional outcomes after robot-assisted radical prostatectomy (RARP). The objective of this study was to assess the impact of the bladder neck angle (BNA) measured by ...
The intra-voxel incoherent motion model of diffusion-weighted magnetic resonance imaging (IVIM-DWI) with a series of images with different-values has great potential as a tool for detecting, diagnosing, staging, and monitoring disease progression or ...
The aim of this study is to explore the clinical effect of deep learning-based MRI-assisted arthroscopy in the early treatment of knee meniscus sports injury. Based on convolutional neural network algorithm, Adam algorithm was introduced to optimize ...
It is likely that when using an artificially augmented hand with six fingers, the natural five plus a robotic one, corticospinal motor synergies controlling grasping actions might be different. However, no direct neurophysiological evidence for this ...
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