A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation
H Jiang, Z Diao, T Shi, Y Zhou, F Wang, W Hu… - Computers in Biology …, 2023 - Elsevier
Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …
processing with the advancement of deep learning in natural image classification, detection …
Computer aided diagnosis of diabetic macular edema in retinal fundus and OCT images: A review
KC Pavithra, P Kumar, M Geetha… - Biocybernetics and …, 2023 - Elsevier
Abstract Diabetic Macular Edema (DME) is a potentially blinding consequence of Diabetic
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …
Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture
LP Joseph, EA Joseph, R Prasad - Computers in Biology and Medicine, 2022 - Elsevier
Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
BARF: A new direct and cross-based binary residual feature fusion with uncertainty-aware module for medical image classification
Automatic medical image analysis (eg, medical image classification) is widely used in the
early diagnosis of various diseases. The computer-aided diagnosis (CAD) systems enable …
early diagnosis of various diseases. The computer-aided diagnosis (CAD) systems enable …
ExAID: A multimodal explanation framework for computer-aided diagnosis of skin lesions
Background and objectives: One principal impediment in the successful deployment of
Artificial Intelligence (AI) based Computer-Aided Diagnosis (CAD) systems in everyday …
Artificial Intelligence (AI) based Computer-Aided Diagnosis (CAD) systems in everyday …
CerCan· Net: Cervical cancer classification model via multi-layer feature ensembles of lightweight CNNs and transfer learning
O Attallah - Expert Systems with Applications, 2023 - Elsevier
Cervical cancer ranks among the most prevalent causes of fatality in women around the
world. Early diagnosis is essential for treating cervical cancer using pap smear slides, but it …
world. Early diagnosis is essential for treating cervical cancer using pap smear slides, but it …
Diagnosis of retinal diseases based on Bayesian optimization deep learning network using optical coherence tomography images
M Subramanian, MS Kumar… - Computational …, 2022 - Wiley Online Library
Retinal abnormalities have emerged as a serious public health concern in recent years and
can manifest gradually and without warning. These diseases can affect any part of the retina …
can manifest gradually and without warning. These diseases can affect any part of the retina …
Multilevel deep feature generation framework for automated detection of retinal abnormalities using OCT images
Optical coherence tomography (OCT) images coupled with many learning techniques have
been developed to diagnose retinal disorders. This work aims to develop a novel framework …
been developed to diagnose retinal disorders. This work aims to develop a novel framework …
Classification of retinal diseases in optical coherence tomography images using artificial intelligence and firefly algorithm
In recent years, the number of studies for the automatic diagnosis of biomedical diseases
has increased. Many of these studies have used Deep Learning, which gives extremely …
has increased. Many of these studies have used Deep Learning, which gives extremely …
A deep learning-based framework for retinal disease classification
This study addresses the problem of the automatic detection of disease states of the retina.
In order to solve the abovementioned problem, this study develops an artificially intelligent …
In order to solve the abovementioned problem, this study develops an artificially intelligent …