Transformers in medical image segmentation: A review

H Xiao, L Li, Q Liu, X Zhu, Q Zhang - Biomedical Signal Processing and …, 2023 - Elsevier
Abstract Background and Objectives: Transformer is a model relying entirely on self-
attention which has a wide range of applications in the field of natural language processing …

Automated detection and forecasting of covid-19 using deep learning techniques: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Neurocomputing, 2024 - Elsevier
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …

Jcs: An explainable covid-19 diagnosis system by joint classification and segmentation

YH Wu, SH Gao, J Mei, J Xu, DP Fan… - … on Image Processing, 2021 - ieeexplore.ieee.org
Recently, the coronavirus disease 2019 (COVID-19) has caused a pandemic disease in
over 200 countries, influencing billions of humans. To control the infection, identifying and …

Automatic COVID-19 lung infected region segmentation and measurement using CT-scans images

A Oulefki, S Agaian, T Trongtirakul, AK Laouar - Pattern recognition, 2021 - Elsevier
History shows that the infectious disease (COVID-19) can stun the world quickly, causing
massive losses to health, resulting in a profound impact on the lives of billions of people …

Applications of artificial intelligence in battling against covid-19: A literature review

M Tayarani - Chaos, Solitons and Fractals, 2020 - researchprofiles.herts.ac.uk
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …

Anam-Net: Anamorphic depth embedding-based lightweight CNN for segmentation of anomalies in COVID-19 chest CT images

N Paluru, A Dayal, HB Jenssen… - … on Neural Networks …, 2021 - ieeexplore.ieee.org
Chest computed tomography (CT) imaging has become indispensable for staging and
managing coronavirus disease 2019 (COVID-19), and current evaluation of anomalies …

Impact of lung segmentation on the diagnosis and explanation of COVID-19 in chest X-ray images

LO Teixeira, RM Pereira, D Bertolini, LS Oliveira… - Sensors, 2021 - mdpi.com
COVID-19 frequently provokes pneumonia, which can be diagnosed using imaging exams.
Chest X-ray (CXR) is often useful because it is cheap, fast, widespread, and uses less …

Toward data‐efficient learning: A benchmark for COVID‐19 CT lung and infection segmentation

J Ma, Y Wang, X An, C Ge, Z Yu, J Chen, Q Zhu… - Medical …, 2021 - Wiley Online Library
Purpose Accurate segmentation of lung and infection in COVID‐19 computed tomography
(CT) scans plays an important role in the quantitative management of patients. Most of the …

COVID-19 lung infection segmentation with a novel two-stage cross-domain transfer learning framework

J Liu, B Dong, S Wang, H Cui, DP Fan, J Ma… - Medical image …, 2021 - Elsevier
With the global outbreak of COVID-19 in early 2020, rapid diagnosis of COVID-19 has
become the urgent need to control the spread of the epidemic. In clinical settings, lung …

Lightweight salient object detection via hierarchical visual perception learning

Y Liu, YC Gu, XY Zhang, W Wang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Recently, salient object detection (SOD) has witnessed vast progress with the rapid
development of convolutional neural networks (CNNs). However, the improvement of SOD …