TTCNN: A breast cancer detection and classification towards computer-aided diagnosis using digital mammography in early stages
Breast cancer is a major research area in the medical image analysis field; it is a dangerous
disease and a major cause of death among women. Early and accurate diagnosis of breast …
disease and a major cause of death among women. Early and accurate diagnosis of breast …
Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare
S Maqsood, R Damaševičius - Neural networks, 2023 - Elsevier
Background: The idea of smart healthcare has gradually gained attention as a result of the
information technology industry's rapid development. Smart healthcare uses next-generation …
information technology industry's rapid development. Smart healthcare uses next-generation …
A novel deep transfer learning based computerized diagnostic Systems for Multi-class imbalanced diabetic retinopathy severity classification
Diabetic Retinopathy (DR) is a retinal condition that leads to gradual degeneration of the
retina and eventual blindness, so early detection and evaluation of disease development …
retina and eventual blindness, so early detection and evaluation of disease development …
Lion based butterfly optimization with improved YOLO-v4 for heart disease prediction using IoMT
V Alamelu, S Thilagamani - Information Technology and Control, 2022 - itc.ktu.lt
Abstract The Internet of Medical Things (IoMT) has subsequently been used in healthcare
services to gather sensor data for the prediction and diagnosis of cardiac disease. Recently …
services to gather sensor data for the prediction and diagnosis of cardiac disease. Recently …
Efficient breast cancer diagnosis from complex mammographic images using deep convolutional neural network
Medical image analysis places a significant focus on breast cancer, which poses a
significant threat to women's health and contributes to many fatalities. An early and precise …
significant threat to women's health and contributes to many fatalities. An early and precise …
Segmentation of Retinal Blood Vessels Using U-Net++ Architecture and Disease Prediction
This study presents a segmentation method for the blood vessels and provides a method for
disease diagnosis in individuals based on retinal images. Blood vessel segmentation in …
disease diagnosis in individuals based on retinal images. Blood vessel segmentation in …
Deep learning enabled hemorrhage detection in retina with DPFE and splat segmentation in fundus images
LG Atlas, KP Arjun, KS Kumar, RK Dhanaraj… - … Signal Processing and …, 2024 - Elsevier
The range of diabetics, hypertension, occlusions in vascular are rapidly increasing in the
modern era. Adversarial effects of these diseases are the organ damage which is increasing …
modern era. Adversarial effects of these diseases are the organ damage which is increasing …
Development of preprocessing methods and revised EfficientNet for diabetic retinopathy detection
CL Lin, ZX Jiang - International Journal of Imaging Systems and …, 2023 - Wiley Online Library
The evolution of deep learning (DL) has made artificial intelligence image recognition a
mature technology. Recently, the use of DL to identify diabetic retinopathy (DR) has been …
mature technology. Recently, the use of DL to identify diabetic retinopathy (DR) has been …
ConjunctiveNet: an improved deep learning-based conjunctive-eyes segmentation and severity detection model
S Pahwa, A Kaur, P Dhiman… - International Journal of …, 2024 - emerald.com
Purpose The study aims to enhance the detection and classification of conjunctival eye
diseases' severity through the development of ConjunctiveNet, an innovative deep learning …
diseases' severity through the development of ConjunctiveNet, an innovative deep learning …
Csec-net: a novel deep features fusion and entropy-controlled firefly feature selection framework for leukemia classification
Leukemia, a life-threatening form of cancer, poses a significant global health challenge
affecting individuals of all age groups, including both children and adults. Currently, the …
affecting individuals of all age groups, including both children and adults. Currently, the …