COVID-19 image classification using deep learning: Advances, challenges and opportunities
Abstract Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
Contour-enhanced attention CNN for CT-based COVID-19 segmentation
Accurate detection of COVID-19 is one of the challenging research topics in today's
healthcare sector to control the coronavirus pandemic. Automatic data-powered insights for …
healthcare sector to control the coronavirus pandemic. Automatic data-powered insights for …
Early Diagnosis: End-to-End CNN–LSTM Models for Mass Spectrometry Data Classification
Liquid chromatography–mass spectrometry (LC–MS) is a powerful method for cell profiling.
The use of LC–MS technology is a tool of choice for cancer research since it provides …
The use of LC–MS technology is a tool of choice for cancer research since it provides …
APT-Net: Adaptive encoding and parallel decoding transformer for medical image segmentation
N Zhang, L Yu, D Zhang, W Wu, S Tian… - Computers in Biology and …, 2022 - Elsevier
There are limitations in the study of transformer-based medical image segmentation
networks for token position encoding and decoding of images. The position encoding …
networks for token position encoding and decoding of images. The position encoding …
[HTML][HTML] CTH-Net: A CNN and Transformer hybrid network for skin lesion segmentation
Y Ding, Z Yi, J Xiao, M Hu, Y Guo, Z Liao, Y Wang - Iscience, 2024 - cell.com
Automatically and accurately segmenting skin lesions can be challenging, due to factors
such as low contrast and fuzzy boundaries. This paper proposes a hybrid encoder-decoder …
such as low contrast and fuzzy boundaries. This paper proposes a hybrid encoder-decoder …
Deep learning‐based body part recognition algorithm for three‐dimensional medical images
Background The automatic recognition of human body parts in three‐dimensional medical
images is important in many clinical applications. However, methods presented in prior …
images is important in many clinical applications. However, methods presented in prior …
Feature‐guided attention network for medical image segmentation
Background U‐Net and its variations have achieved remarkable performances in medical
image segmentation. However, they have two limitations. First, the shallow layer feature of …
image segmentation. However, they have two limitations. First, the shallow layer feature of …
Automatic recognition of cephalometric landmarks via multi-scale sampling strategy
C Zhao, Z Yuan, S Luo, W Wang, Z Ren, X Yao, T Wu - Heliyon, 2023 - cell.com
The identification of head landmarks in cephalometric analysis significantly contributes in
the anatomical localization of maxillofacial tissues for orthodontic and orthognathic surgery …
the anatomical localization of maxillofacial tissues for orthodontic and orthognathic surgery …