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 …
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
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 …
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
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 …
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
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 …
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 …
(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
Chest computed tomography (CT) imaging has become indispensable for staging and
managing coronavirus disease 2019 (COVID-19), and current evaluation of anomalies …
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
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 …
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
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 …
(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
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 …
become the urgent need to control the spread of the epidemic. In clinical settings, lung …
Lightweight salient object detection via hierarchical visual perception learning
Recently, salient object detection (SOD) has witnessed vast progress with the rapid
development of convolutional neural networks (CNNs). However, the improvement of SOD …
development of convolutional neural networks (CNNs). However, the improvement of SOD …