[HTML][HTML] A review on deep learning in medical image analysis
S Suganyadevi, V Seethalakshmi… - International Journal of …, 2022 - Springer
Ongoing improvements in AI, particularly concerning deep learning techniques, are
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …
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 …
Segment anything model for medical image analysis: an experimental study
Training segmentation models for medical images continues to be challenging due to the
limited availability of data annotations. Segment Anything Model (SAM) is a foundation …
limited availability of data annotations. Segment Anything Model (SAM) is a foundation …
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 …
Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools
Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
Diagnosing COVID-19 pneumonia from X-ray and CT images using deep learning and transfer learning algorithms
The novel coronavirus 2019 (COVID-19) first appeared in Wuhan province of China and
spread quickly around the globe and became a pandemic. The gold standard for confirming …
spread quickly around the globe and became a pandemic. The gold standard for confirming …
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 …
[HTML][HTML] VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations
Most of the existing chest X-ray datasets include labels from a list of findings without
specifying their locations on the radiographs. This limits the development of machine …
specifying their locations on the radiographs. This limits the development of machine …
A survey on video-based human action recognition: recent updates, datasets, challenges, and applications
Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …
A survey of deep learning and its applications: a new paradigm to machine learning
Nowadays, deep learning is a current and a stimulating field of machine learning. Deep
learning is the most effective, supervised, time and cost efficient machine learning approach …
learning is the most effective, supervised, time and cost efficient machine learning approach …