When machine learning meets medical world: Current status and future challenges
A Smiti - Computer Science Review, 2020 - Elsevier
Imagine the enormous amounts of data that can be generated in the medical field. Each
patient has his own medical record which contains valuable information like patient allergy …
patient has his own medical record which contains valuable information like patient allergy …
Automated computationally intelligent methods for ocular vessel segmentation and disease detection: a review
Ocular diseases are eventually increasing these days that cause partial or complete vision
loss even at an early age, the prominent reason behind this is cardiovascular diseases that …
loss even at an early age, the prominent reason behind this is cardiovascular diseases that …
Weakly supervised lesion detection from fundus images
Early diagnosis and continuous monitoring of patients suffering from eye diseases have
been major concerns in the computer-aided detection techniques. Detecting one or several …
been major concerns in the computer-aided detection techniques. Detecting one or several …
An efficient framework for automated screening of Clinically Significant Macular Edema
The present study proposes a new approach to automated screening of Clinically Significant
Macular Edema (CSME) and addresses two major challenges associated with such …
Macular Edema (CSME) and addresses two major challenges associated with such …
Change detection based on unsupervised sparse representation for fundus image pair
Detecting changes is an important issue for ophthalmology to compare longitudinal fundus
images at different stages and obtain change regions. Illumination variations bring …
images at different stages and obtain change regions. Illumination variations bring …
Abnormality detection in retinal image by individualized background learning
Computer-aided lesion detection (CAD) techniques, which provide potential for automatic
early screening of retinal pathologies, are widely studied in retinal image analysis. While …
early screening of retinal pathologies, are widely studied in retinal image analysis. While …
Anomaly detection in fundus images by self-adaptive decomposition via local and color based sparse coding
Y Du, L Wang, B Chen, C An, H Liu, Y Fan… - Biomedical Optics …, 2022 - opg.optica.org
Anomaly detection in color fundus images is challenging due to the diversity of anomalies.
The current studies detect anomalies from fundus images by learning their background …
The current studies detect anomalies from fundus images by learning their background …
Individualized statistical modeling of lesions in fundus images for anomaly detection
Anomaly detection in fundus images remains challenging due to the fact that fundus images
often contain diverse types of lesions with various properties in locations, sizes, shapes, and …
often contain diverse types of lesions with various properties in locations, sizes, shapes, and …
A review on recent developments for the retinal vessel segmentation methodologies and exudate detection in fundus images using deep learning algorithms
SA Kumar, J Satheesh Kumar - Computational Vision and Bio-Inspired …, 2020 - Springer
Retinal image analysis is considered as a well-known non-intrusive diagnosis technique in
modern opthalmology. The pathological changes which occurs due to hypertension, diabetic …
modern opthalmology. The pathological changes which occurs due to hypertension, diabetic …
Constrained Deep One-Class Feature Learning For Classifying Imbalanced Medical Images
L Gao, C Liu, D Arefan, A Panigrahy, S Wu - arxiv preprint arxiv …, 2021 - arxiv.org
Medical image data are usually imbalanced across different classes. One-class
classification has attracted increasing attention to address the data imbalance problem by …
classification has attracted increasing attention to address the data imbalance problem by …