A review of deep-learning-based medical image segmentation methods
As an emerging biomedical image processing technology, medical image segmentation has
made great contributions to sustainable medical care. Now it has become an important …
made great contributions to sustainable medical care. Now it has become an important …
Deep semantic segmentation of natural and medical images: a review
The semantic image segmentation task consists of classifying each pixel of an image into an
instance, where each instance corresponds to a class. This task is a part of the concept of …
instance, where each instance corresponds to a class. This task is a part of the concept of …
Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
Glaucoma is one of the leading causes of irreversible but preventable blindness in working
age populations. Color fundus photography (CFP) is the most cost-effective imaging …
age populations. Color fundus photography (CFP) is the most cost-effective imaging …
Application of generative adversarial networks (GAN) for ophthalmology image domains: a survey
Background Recent advances in deep learning techniques have led to improved diagnostic
abilities in ophthalmology. A generative adversarial network (GAN), which consists of two …
abilities in ophthalmology. A generative adversarial network (GAN), which consists of two …
Generative adversarial network in medical imaging: A review
Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …
community due to their capability of data generation without explicitly modelling the …
Weighted res-unet for high-quality retina vessel segmentation
Retinal vessel segmentation is a key step towards the accurate visualization, diagnosis,
early treatment and surgery planning of ocular diseases. Recently, deep learning based …
early treatment and surgery planning of ocular diseases. Recently, deep learning based …
A review of deep learning based methods for medical image multi-organ segmentation
Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …
performance in many medical image segmentation tasks. Many deep learning-based …
Scs-net: A scale and context sensitive network for retinal vessel segmentation
Accurately segmenting retinal vessel from retinal images is essential for the detection and
diagnosis of many eye diseases. However, it remains a challenging task due to (1) the large …
diagnosis of many eye diseases. However, it remains a challenging task due to (1) the large …
GANs for medical image analysis
Generative adversarial networks (GANs) and their extensions have carved open many
exciting ways to tackle well known and challenging medical image analysis problems such …
exciting ways to tackle well known and challenging medical image analysis problems such …
Generative adversarial networks in medical image segmentation: A review
S Xun, D Li, H Zhu, M Chen, J Wang, J Li… - Computers in biology …, 2022 - Elsevier
Abstract Purpose Since Generative Adversarial Network (GAN) was introduced into the field
of deep learning in 2014, it has received extensive attention from academia and industry …
of deep learning in 2014, it has received extensive attention from academia and industry …