Convolutional neural networks in medical image understanding: a survey
Imaging techniques are used to capture anomalies of the human body. The captured images
must be understood for diagnosis, prognosis and treatment planning of the anomalies …
must be understood for diagnosis, prognosis and treatment planning of the anomalies …
A survey on deep learning in medical image analysis
Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …
methodology of choice for analyzing medical images. This paper reviews the major deep …
Joint optic disc and cup segmentation based on multi-label deep network and polar transformation
Glaucoma is a chronic eye disease that leads to irreversible vision loss. The cup to disc ratio
(CDR) plays an important role in the screening and diagnosis of glaucoma. Thus, the …
(CDR) plays an important role in the screening and diagnosis of glaucoma. Thus, the …
Thoracic disease identification and localization with limited supervision
Accurate identification and localization of abnormalities from radiology images play an
integral part in clinical diagnosis and treatment planning. Building a highly accurate …
integral part in clinical diagnosis and treatment planning. Building a highly accurate …
Optic disc and cup segmentation methods for glaucoma detection with modification of U-Net convolutional neural network
Glaucoma is the second leading cause of blindness all over the world, with approximately
60 million cases reported worldwide in 2010. If undiagnosed in time, glaucoma causes …
60 million cases reported worldwide in 2010. If undiagnosed in time, glaucoma causes …
Recent trends and advances in fundus image analysis: A review
Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey
Diabetic retinopathy (DR) results in vision loss if not treated early. A computer-aided
diagnosis (CAD) system based on retinal fundus images is an efficient and effective method …
diagnosis (CAD) system based on retinal fundus images is an efficient and effective method …
A large-scale database and a CNN model for attention-based glaucoma detection
Glaucoma is one of the leading causes of irreversible vision loss. Many approaches have
recently been proposed for automatic glaucoma detection based on fundus images …
recently been proposed for automatic glaucoma detection based on fundus images …
Patch-based output space adversarial learning for joint optic disc and cup segmentation
Glaucoma is a leading cause of irreversible blindness. Accurate segmentation of the optic
disc (OD) and optic cup (OC) from fundus images is beneficial to glaucoma screening and …
disc (OD) and optic cup (OC) from fundus images is beneficial to glaucoma screening and …
Attention based glaucoma detection: A large-scale database and CNN model
Recently, the attention mechanism has been successfully applied in convolutional neural
networks (CNNs), significantly boosting the performance of many computer vision tasks …
networks (CNNs), significantly boosting the performance of many computer vision tasks …