[HTML][HTML] Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities

M Goyal, T Knackstedt, S Yan, S Hassanpour - Computers in biology and …, 2020‏ - Elsevier
Recently, there has been great interest in develo** Artificial Intelligence (AI) enabled
computer-aided diagnostics solutions for the diagnosis of skin cancer. With the increasing …

[HTML][HTML] All you need is data preparation: A systematic review of image harmonization techniques in Multi-center/device studies for medical support systems

S Seoni, A Shahini, KM Meiburger, F Marzola… - Computer Methods and …, 2024‏ - Elsevier
Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …

[HTML][HTML] Analysis of the ISIC image datasets: Usage, benchmarks and recommendations

B Cassidy, C Kendrick, A Brodzicki… - Medical image …, 2022‏ - Elsevier
Abstract The International Skin Imaging Collaboration (ISIC) datasets have become a
leading repository for researchers in machine learning for medical image analysis …

Skin lesion segmentation in dermoscopic images with ensemble deep learning methods

M Goyal, A Oakley, P Bansal, D Dancey, MH Yap - Ieee Access, 2019‏ - ieeexplore.ieee.org
Early detection of skin cancer, particularly melanoma, is crucial to enable advanced
treatment. Due to the rapid growth in the number of skin cancers, there is a growing need of …

[HTML][HTML] Deep learning in diabetic foot ulcers detection: a comprehensive evaluation

MH Yap, R Hachiuma, A Alavi, R Brüngel… - Computers in biology …, 2021‏ - Elsevier
There has been a substantial amount of research involving computer methods and
technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack …

Skin disease diagnosis with deep learning: A review

H Li, Y Pan, J Zhao, L Zhang - Neurocomputing, 2021‏ - Elsevier
Skin cancer is one of the most threatening diseases worldwide. However, diagnosing skin
cancer correctly is challenging. Recently, deep learning algorithms have emerged to …

A hierarchical three-step superpixels and deep learning framework for skin lesion classification

F Afza, M Sharif, M Mittal, MA Khan, DJ Hemanth - Methods, 2022‏ - Elsevier
Skin cancer is one of the most common and dangerous cancer that exists worldwide.
Malignant melanoma is one of the most dangerous skin cancer types has a high mortality …

Background selection schema on deep learning-based classification of dermatological disease

J Zhou, Z Wu, Z Jiang, K Huang, K Guo… - Computers in Biology and …, 2022‏ - Elsevier
Skin diseases are one of the most common ailments affecting humans. Artificial intelligence
based on deep learning can significantly improve the efficiency of identifying skin disorders …

DermoCC-GAN: A new approach for standardizing dermatological images using generative adversarial networks

M Salvi, F Branciforti, F Veronese, E Zavattaro… - Computer Methods and …, 2022‏ - Elsevier
Background and objective Dermatological images are typically diagnosed based on visual
analysis of the skin lesion acquired using a dermoscope. However, the final quality of the …

DUNEScan: a web server for uncertainty estimation in skin cancer detection with deep neural networks

B Mazoure, A Mazoure, J Bédard, V Makarenkov - Scientific Reports, 2022‏ - nature.com
Recent years have seen a steep rise in the number of skin cancer detection applications.
While modern advances in deep learning made possible reaching new heights in terms of …