U-net and its variants for medical image segmentation: A review of theory and applications
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …
tasks. These traits provide U-net with a high utility within the medical imaging community …
Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends
Semantic-based segmentation (Semseg) methods play an essential part in medical imaging
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
A general survey on attention mechanisms in deep learning
G Brauwers, F Frasincar - IEEE Transactions on Knowledge …, 2021 - ieeexplore.ieee.org
Attention is an important mechanism that can be employed for a variety of deep learning
models across many different domains and tasks. This survey provides an overview of the …
models across many different domains and tasks. This survey provides an overview of the …
Automated detection of COVID-19 cases using deep neural networks with X-ray images
Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of
China in December 2019, spread rapidly around the world and became a pandemic. It has …
China in December 2019, spread rapidly around the world and became a pandemic. It has …
[HTML][HTML] Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks
The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread
rapidly among people living in other countries and is approaching approximately …
rapidly among people living in other countries and is approaching approximately …
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 …
[HTML][HTML] A review of mathematical modeling, artificial intelligence and datasets used in the study, prediction and management of COVID-19
In the past few months, several works were published in regards to the dynamics and early
detection of COVID-19 via mathematical modeling and Artificial intelligence (AI). The aim of …
detection of COVID-19 via mathematical modeling and Artificial intelligence (AI). The aim of …
Transattunet: Multi-level attention-guided u-net with transformer for medical image segmentation
Accurate segmentation of organs or lesions from medical images is crucial for reliable
diagnosis of diseases and organ morphometry. In recent years, convolutional encoder …
diagnosis of diseases and organ morphometry. In recent years, convolutional encoder …
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 …
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 …