U-net and its variants for medical image segmentation: A review of theory and applications
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …
tasks. These traits provide U-net with a high utility within the medical imaging community …
Medical Image Segmentation based on U-Net: A Review.
Medical image analysis is performed by analyzing images obtained by medical imaging
systems to solve clinical problems. The purpose is to extract effective information and …
systems to solve clinical problems. The purpose is to extract effective information and …
Transfuse: Fusing transformers and cnns for medical image segmentation
Medical image segmentation-the prerequisite of numerous clinical needs-has been
significantly prospered by recent advances in convolutional neural networks (CNNs) …
significantly prospered by recent advances in convolutional neural networks (CNNs) …
[HTML][HTML] An enhanced technique of skin cancer classification using deep convolutional neural network with transfer learning models
Skin cancer is one of the top three perilous types of cancer caused by damaged DNA that
can cause death. This damaged DNA begins cells to grow uncontrollably and nowadays it is …
can cause death. This damaged DNA begins cells to grow uncontrollably and nowadays it is …
Detection of skin cancer based on skin lesion images using deep learning
An increasing number of genetic and metabolic anomalies have been determined to lead to
cancer, generally fatal. Cancerous cells may spread to any body part, where they can be life …
cancer, generally fatal. Cancerous cells may spread to any body part, where they can be life …
Deep learning techniques for skin lesion analysis and melanoma cancer detection: a survey of state-of-the-art
Abstract Analysis of skin lesion images via visual inspection and manual examination to
diagnose skin cancer has always been cumbersome. This manual examination of skin …
diagnose skin cancer has always been cumbersome. This manual examination of skin …
Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms
MA Al-Antari, SM Han, TS Kim - Computer methods and programs in …, 2020 - Elsevier
Abstract Background and Objective Deep learning detection and classification from medical
imagery are key components for computer-aided diagnosis (CAD) systems to efficiently …
imagery are key components for computer-aided diagnosis (CAD) systems to efficiently …
Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification
Background and objective Computer automated diagnosis of various skin lesions through
medical dermoscopy images remains a challenging task. Methods In this work, we propose …
medical dermoscopy images remains a challenging task. Methods In this work, we propose …
Ms RED: A novel multi-scale residual encoding and decoding network for skin lesion segmentation
Abstract Computer-Aided Diagnosis (CAD) for dermatological diseases offers one of the
most notable showcases where deep learning technologies display their impressive …
most notable showcases where deep learning technologies display their impressive …
TTCNN: A breast cancer detection and classification towards computer-aided diagnosis using digital mammography in early stages
S Maqsood, R Damaševičius, R Maskeliūnas - Applied Sciences, 2022 - mdpi.com
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 …