BACKGROUND: Highly accurate detection of intracranial hemorrhages (ICH) on head computed tomography (HCT) scans can prove challenging at high-volume centers. This study aimed to determine the number of additional ICHs detected by an artificial intell...
Human action recognition (HAR) has gained significant attention recently as it can be adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task because of the variety of human actions in daily life. Various solutions b...
Recently, segmentation methods based on Convolutional Neural Networks (CNNs) showed promising performance in automatic Multiple Sclerosis (MS) lesions segmentation. These techniques have even outperformed human experts in controlled evaluation condit...
This study's purpose was to develop a direct MRI-based, deep-learning semantic segmentation approach for computing global longitudinal strain (GLS), a known metric for detecting left-ventricular (LV) cardiotoxicity in breast cancer. Displacement Enco...
Small (Weinheim an der Bergstrasse, Germany)
Nov 27, 2021
Atomic force microscopy (AFM) is one of the most popular imaging and characterizing methods applicable to a wide range of nanoscale material systems. However, high-resolution imaging using AFM generally suffers from a low scanning yield due to its me...
Journal of medical ultrasonics (2001)
Nov 27, 2021
PURPOSE: The purpose of this study was to detect two dimensional and sub-pixel displacement with high spatial resolution using an ultrasonic diagnostic apparatus. Conventional displacement detection methods assume neighborhood uniformity and cannot a...
The biggest challenge in the classification of plant water stress conditions is the similar appearance of different stress conditions. We introduce HortNet417v1 with 417 layers for rapid recognition, classification, and visualization of plant stress ...
Computational intelligence and neuroscience
Nov 27, 2021
Nowadays, ocean observation technology continues to progress, resulting in a huge increase in marine data volume and dimensionality. This volume of data provides a golden opportunity to train predictive models, as the more the data is, the better the...
PURPOSE: To improve the estimation of coil sensitivity functions from limited auto-calibration signals (ACS) in SENSE-based reconstruction for brain imaging.
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