Transformers in medical imaging: A survey
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …
successfully applied to several computer vision problems, achieving state-of-the-art results …
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
SK Zhou, H Greenspan, C Davatzikos… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey
Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …
death cases and affected all sectors of human life. With gradual progression of time, COVID …
Imaging intact human organs with local resolution of cellular structures using hierarchical phase-contrast tomography
Imaging intact human organs from the organ to the cellular scale in three dimensions is a
goal of biomedical imaging. To meet this challenge, we developed hierarchical phase …
goal of biomedical imaging. To meet this challenge, we developed hierarchical phase …
Covid-19: automatic detection from x-ray images utilizing transfer learning with convolutional neural networks
ID Apostolopoulos, TA Mpesiana - Physical and engineering sciences in …, 2020 - Springer
In this study, a dataset of X-ray images from patients with common bacterial pneumonia,
confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection …
confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection …
[PDF][PDF] Detection of coronavirus disease (covid-19) based on deep features
The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner.
The coronavirus spread so quickly between people and approaches 100,000 people …
The coronavirus spread so quickly between people and approaches 100,000 people …
An overview of clinical decision support systems: benefits, risks, and strategies for success
RT Sutton, D Pincock, DC Baumgart… - NPJ digital …, 2020 - nature.com
Computerized clinical decision support systems, or CDSS, represent a paradigm shift in
healthcare today. CDSS are used to augment clinicians in their complex decision-making …
healthcare today. CDSS are used to augment clinicians in their complex decision-making …
Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization
Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and is one
of the top 10 leading causes of death. Accurate and early detection of TB is very important …
of the top 10 leading causes of death. Accurate and early detection of TB is very important …
Covidgan: data augmentation using auxiliary classifier gan for improved covid-19 detection
Coronavirus (COVID-19) is a viral disease caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect …
coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect …
Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation
This paper presents an automatic classification segmentation tool for helping screening
COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess …
COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess …