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 …
[HTML][HTML] Deep learning applications for IoT in health care: A systematic review
In machine learning, deep learning is the most popular topic having a wide range of
applications such as computer vision, natural language processing, speech recognition …
applications such as computer vision, natural language processing, speech recognition …
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 …
Skin lesions classification into eight classes for ISIC 2019 using deep convolutional neural network and transfer learning
Melanoma is a type of skin cancer with a high mortality rate. The different types of skin
lesions result in an inaccurate diagnosis due to their high similarity. Accurate classification of …
lesions result in an inaccurate diagnosis due to their high similarity. Accurate classification of …
Automatic skin lesion segmentation using deep fully convolutional networks with jaccard distance
Y Yuan, M Chao, YC Lo - IEEE transactions on medical …, 2017 - ieeexplore.ieee.org
Automatic skin lesion segmentation in dermoscopic images is a challenging task due to the
low contrast between lesion and the surrounding skin, the irregular and fuzzy lesion borders …
low contrast between lesion and the surrounding skin, the irregular and fuzzy lesion borders …
Skin lesion analysis towards melanoma detection using deep learning network
Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy
images significantly increases the survival rate. However, the accurate recognition of …
images significantly increases the survival rate. However, the accurate recognition of …
Deep‐learning‐based, computer‐aided classifier developed with a small dataset of clinical images surpasses board‐certified dermatologists in skin tumour diagnosis
Y Fujisawa, Y Otomo, Y Ogata… - British Journal of …, 2019 - academic.oup.com
Background Application of deep‐learning technology to skin cancer classification can
potentially improve the sensitivity and specificity of skin cancer screening, but the number of …
potentially improve the sensitivity and specificity of skin cancer screening, but the number of …
Dermoscopic image segmentation via multistage fully convolutional networks
Objective: Segmentation of skin lesions is an important step in the automated computer
aided diagnosis of melanoma. However, existing segmentation methods have a tendency to …
aided diagnosis of melanoma. However, existing segmentation methods have a tendency to …
[HTML][HTML] Dense-UNet: a novel multiphoton in vivo cellular image segmentation model based on a convolutional neural network
S Cai, Y Tian, H Lui, H Zeng, Y Wu… - Quantitative imaging in …, 2020 - ncbi.nlm.nih.gov
Background Multiphoton microscopy (MPM) offers a feasible approach for the biopsy in
clinical medicine, but it has not been used in clinical applications due to the lack of efficient …
clinical medicine, but it has not been used in clinical applications due to the lack of efficient …
Multi-class multi-level classification algorithm for skin lesions classification using machine learning techniques
Skin diseases remain a major cause of disability worldwide and contribute approximately
1.79% of the global burden of disease measured in disability-adjusted life years. In the …
1.79% of the global burden of disease measured in disability-adjusted life years. In the …