Retinal disease detection using deep learning techniques: a comprehensive review
S Muchuchuti, S Viriri - Journal of Imaging, 2023 - mdpi.com
Millions of people are affected by retinal abnormalities worldwide. Early detection and
treatment of these abnormalities could arrest further progression, saving multitudes from …
treatment of these abnormalities could arrest further progression, saving multitudes from …
Improving brain tumor classification performance with an effective approach based on new deep learning model named 3ACL from 3D MRI data
Many machine learning-based studies have been carried out in the literature for the
detection of brain tumors using MRI data and most of what has been done in the last 6 years …
detection of brain tumors using MRI data and most of what has been done in the last 6 years …
Combining convolutional neural networks and self-attention for fundus diseases identification
K Wang, C Xu, G Li, Y Zhang, Y Zheng, C Sun - Scientific Reports, 2023 - nature.com
Early detection of lesions is of great significance for treating fundus diseases. Fundus
photography is an effective and convenient screening technique by which common fundus …
photography is an effective and convenient screening technique by which common fundus …
Automated steel surface defect detection and classification using a new deep learning-based approach
In this study, a new deep learning-based approach has been developed that detects and
classifies surface defects that occur in the steel production process. The proposed …
classifies surface defects that occur in the steel production process. The proposed …
An accurate multiple sclerosis detection model based on exemplar multiple parameters local phase quantization: ExMPLPQ
Multiple sclerosis (MS) is a chronic demyelinating condition characterized by plaques in the
white matter of the central nervous system that can be detected using magnetic resonance …
white matter of the central nervous system that can be detected using magnetic resonance …
Grading diabetic retinopathy using multiresolution based CNN
Diabetic Retinopathy (DR) refers to a medical condition that affects the eye; it occurs due to
diabetes, and, if not detected early on, results in a reduction of visual capacity and may even …
diabetes, and, if not detected early on, results in a reduction of visual capacity and may even …
Comparative analysis of diabetic retinopathy classification approaches using machine learning and deep learning techniques
Diabetic retinopathy (DR) is an eye disease caused due to excess of sugar in retinal blood
vessels and obstructs vision. Regular and timely diagnosis can prevent the severity of …
vessels and obstructs vision. Regular and timely diagnosis can prevent the severity of …
Automated ischemic acute infarction detection using pre-trained CNN models' deep features
B Tasci - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract Background Cerebrovascular Diseases (CVD) constitute more than 50% of
neurological diseases requiring hospital treatment. Stroke is a type of disease that causes …
neurological diseases requiring hospital treatment. Stroke is a type of disease that causes …
Deep feature extraction based brain image classification model using preprocessed images: PDRNet
Background Stroke is a neurological condition that occurs when cerebral vessels become
blocked and have reduced blood flow. This research proposes a hybrid deep feature-based …
blocked and have reduced blood flow. This research proposes a hybrid deep feature-based …
Correlation-based feature selection using bio-inspired algorithms and optimized KELM classifier for glaucoma diagnosis
K Balasubramanian, NP Ananthamoorthy - Applied Soft Computing, 2022 - Elsevier
Reduced computational time and cost, reduced skilled professional resources, and
diagnostic accuracy have made medical diagnosis using computer aided systems (CAD) …
diagnostic accuracy have made medical diagnosis using computer aided systems (CAD) …