Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review

MA Kassem, KM Hosny, R Damaševičius, MM Eltoukhy - Diagnostics, 2021 - mdpi.com
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in developing computer-aided diagnosis …

[HTML][HTML] A survey, review, and future trends of skin lesion segmentation and classification

MK Hasan, MA Ahamad, CH Yap, G Yang - Computers in Biology and …, 2023 - Elsevier
Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

A survey on deep learning for skin lesion segmentation

Z Mirikharaji, K Abhishek, A Bissoto, C Barata… - Medical Image …, 2023 - Elsevier
Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

What can be transferred: Unsupervised domain adaptation for endoscopic lesions segmentation

J Dong, Y Cong, G Sun, B Zhong… - Proceedings of the …, 2020 - openaccess.thecvf.com
Unsupervised domain adaptation has attracted growing research attention on semantic
segmentation. However, 1) most existing models cannot be directly applied into lesions …

Skin lesion extraction using multiscale morphological local variance reconstruction based watershed transform and fast fuzzy C-means clustering

R Rout, P Parida, Y Alotaibi, S Alghamdi, OI Khalaf - Symmetry, 2021 - mdpi.com
Early identification of melanocytic skin lesions increases the survival rate for skin cancer
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …

Deep learning and optimization-based methods for skin lesions segmentation: a review

KM Hosny, D Elshoura, ER Mohamed… - IEEE …, 2023 - ieeexplore.ieee.org
Skin cancer is a senior public health issue that could profit from computer-aided diagnosis to
decrease the encumbrance of this widespread disease. Researchers have been more …

Intelligent skin cancer diagnosis using improved particle swarm optimization and deep learning models

TY Tan, L Zhang, CP Lim - Applied Soft Computing, 2019 - Elsevier
In this research, we propose an intelligent decision support system for skin cancer detection.
Since generating an effective lesion representation is a vital step to ensure the success of …

An integrated framework of skin lesion detection and recognition through saliency method and optimal deep neural network features selection

MA Khan, T Akram, M Sharif, K Javed, M Rashid… - Neural Computing and …, 2020 - Springer
Malignant melanoma, not belongs to a common type of skin cancers but most serious
because of its growth—affecting large number of people worldwide. Recent studies …

Automated skin lesion segmentation of dermoscopic images using GrabCut and k‐means algorithms

SM Jaisakthi, P Mirunalini, C Aravindan - IET Computer Vision, 2018 - Wiley Online Library
Skin cancer is the most common type of cancer in the world and the incidents of skin cancer
have been rising over the past decade. Even with a dermoscopic imaging system, which …

Skin lesion segmentation using k-mean and optimized fire fly algorithm

S Garg, B Jindal - Multimedia Tools and Applications, 2021 - Springer
Digital image processing is turning out to be increasingly more significant in the health care
field used to diagnose skin cancer. The death rate is increasing by 1% every year due to …