Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in develo** computer-aided diagnosis …
researchers have shown an increasing interest in develo** computer-aided diagnosis …
Malignant melanoma classification using deep learning: datasets, performance measurements, challenges and opportunities
Melanoma remains the most harmful form of skin cancer. Convolutional neural network
(CNN) based classifiers have become the best choice for melanoma detection in the recent …
(CNN) based classifiers have become the best choice for melanoma detection in the recent …
Advanced meta-heuristic algorithm based on Particle Swarm and Al-biruni Earth Radius optimization methods for oral cancer detection
Oral cancer is a deadly form of cancerous tumor that is widely spread in low and middle-
income countries. An early and affordable oral cancer diagnosis might be achieved by …
income countries. An early and affordable oral cancer diagnosis might be achieved by …
Transattunet: Multi-level attention-guided u-net with transformer for medical image segmentation
Accurate segmentation of organs or lesions from medical images is crucial for reliable
diagnosis of diseases and organ morphometry. In recent years, convolutional encoder …
diagnosis of diseases and organ morphometry. In recent years, convolutional encoder …
Skin lesion classification of dermoscopic images using machine learning and convolutional neural network
Detecting dangerous illnesses connected to the skin organ, particularly malignancy,
requires the identification of pigmented skin lesions. Image detection techniques and …
requires the identification of pigmented skin lesions. Image detection techniques and …
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 …
Skin-Net: a novel deep residual network for skin lesions classification using multilevel feature extraction and cross-channel correlation with detection of outlier
Human Skin cancer is commonly detected visually through clinical screening followed by a
dermoscopic examination. However, automated skin lesion classification remains …
dermoscopic examination. However, automated skin lesion classification remains …
Multiclass skin lesion classification using hybrid deep features selection and extreme learning machine
The variation in skin textures and injuries, as well as the detection and classification of skin
cancer, is a difficult task. Manually detecting skin lesions from dermoscopy images is a …
cancer, is a difficult task. Manually detecting skin lesions from dermoscopy images is a …
Modified U-net architecture for segmentation of skin lesion
Dermoscopy images can be classified more accurately if skin lesions or nodules are
segmented. Because of their fuzzy borders, irregular boundaries, inter-and intra-class …
segmented. Because of their fuzzy borders, irregular boundaries, inter-and intra-class …
A comprehensive analysis of dermoscopy images for melanoma detection via deep CNN features
Melanoma is the fastest growing and most lethal cancer among all forms of skin cancer.
Deep learning methods, mainly convolutional neural networks (CNNs) have recently …
Deep learning methods, mainly convolutional neural networks (CNNs) have recently …