[HTML][HTML] A comparative study of X-ray and CT images in COVID-19 detection using image processing and deep learning techniques
The deadly coronavirus has not just devastated the lives of millions but has put the entire
healthcare system under tremendous pressure. Early diagnosis of COVID-19 plays a …
healthcare system under tremendous pressure. Early diagnosis of COVID-19 plays a …
Joint learning of 3D lesion segmentation and classification for explainable COVID-19 diagnosis
Given the outbreak of COVID-19 pandemic and the shortage of medical resource, extensive
deep learning models have been proposed for automatic COVID-19 diagnosis, based on 3D …
deep learning models have been proposed for automatic COVID-19 diagnosis, based on 3D …
Learning from AI-generated annotations for medical image segmentation
Learning from AI-generated annotations is wellrecognized as a key advance of deep
learning techniques in medical image segmentation. Towards this direction, in this paper …
learning techniques in medical image segmentation. Towards this direction, in this paper …
S2C-DeLeNet: A parameter transfer based segmentation-classification integration for detecting skin cancer lesions from dermoscopic images
Dermoscopic images ideally depict pigmentation attributes on the skin surface which is
highly regarded in the medical community for detection of skin abnormality, disease or even …
highly regarded in the medical community for detection of skin abnormality, disease or even …
MultiR-net: a novel joint learning network for COVID-19 segmentation and classification
CF Li, YD Xu, XH Ding, JJ Zhao, RQ Du, LZ Wu… - Computers in Biology …, 2022 - Elsevier
The outbreak of COVID-19 has caused a severe shortage of healthcare resources. Ground
Glass Opacity (GGO) and consolidation of chest CT scans have been an essential basis for …
Glass Opacity (GGO) and consolidation of chest CT scans have been an essential basis for …
[HTML][HTML] A novel deep learning framework with a COVID-19 adjustment for electricity demand forecasting
Electricity demand forecasting is crucial for practical power system management. However,
during the COVID-19 pandemic, the electricity demand system deviated from normal system …
during the COVID-19 pandemic, the electricity demand system deviated from normal system …
SCOAT-Net: A novel network for segmenting COVID-19 lung opacification from CT images
S Zhao, Z Li, Y Chen, W Zhao, X **e, J Liu, D Zhao… - Pattern Recognition, 2021 - Elsevier
Automatic segmentation of lung opacification from computed tomography (CT) images
shows excellent potential for quickly and accurately quantifying the infection of Coronavirus …
shows excellent potential for quickly and accurately quantifying the infection of Coronavirus …
Multiview deep learning-based efficient medical data management for survival time forecasting
K Yu, L Quan, C Chakraborty, Y Shen… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
In recent years, data-driven remote medical management has received much attention,
especially in application of survival time forecasting. By monitoring the physical …
especially in application of survival time forecasting. By monitoring the physical …
SR-AttNet: An interpretable stretch–relax attention based deep neural network for polyp segmentation in colonoscopy images
Background: Colorectal polyp is a common structural gastrointestinal (GI) anomaly, which
can in certain cases turn malignant. Colonoscopic image inspection is, thereby, an important …
can in certain cases turn malignant. Colonoscopic image inspection is, thereby, an important …
RCTE: A reliable and consistent temporal-ensembling framework for semi-supervised segmentation of COVID-19 lesions
W Ding, M Abdel-Basset, H Hawash - Information sciences, 2021 - Elsevier
The segmentation of COVID-19 lesions from computed tomography (CT) scans is crucial to
develop an efficient automated diagnosis system. Deep learning (DL) has shown success in …
develop an efficient automated diagnosis system. Deep learning (DL) has shown success in …