A survey of feature extraction in dermoscopy image analysis of skin cancer

C Barata, ME Celebi, JS Marques - IEEE journal of biomedical …, 2018 - ieeexplore.ieee.org
Dermoscopy image analysis (DIA) is a growing field, with works being published every
week. This makes it difficult not only to keep track of all the contributions, but also for new …

Semi-supervised learning for medical image classification using imbalanced training data

T Huynh, A Nibali, Z He - Computer methods and programs in biomedicine, 2022 - Elsevier
Background and objective Medical image classification is often challenging for two reasons:
a lack of labelled examples due to expensive and time-consuming annotation protocols, and …

[PDF][PDF] A machine learning model for skin disease classification using convolution neural network

VR Allugunti - … Journal of Computing, Programming and Database …, 2022 - researchgate.net
Melanoma is a skin disease that tends to be lethal. It occurs when melanocytes develop in
an uncontrolled manner. Melanoma goes under a few different names, including malignant …

Bcn20000: Dermoscopic lesions in the wild

M Combalia, NCF Codella, V Rotemberg… - arXiv preprint arXiv …, 2019 - arxiv.org
This article summarizes the BCN20000 dataset, composed of 19424 dermoscopic images of
skin lesions captured from 2010 to 2016 in the facilities of the Hospital Cl\'inic in Barcelona …

ResGANet: Residual group attention network for medical image classification and segmentation

J Cheng, S Tian, L Yu, C Gao, X Kang, X Ma, W Wu… - Medical Image …, 2022 - Elsevier
In recent years, deep learning technology has shown superior performance in different fields
of medical image analysis. Some deep learning architectures have been proposed and …

Attention residual learning for skin lesion classification

J Zhang, Y Xie, Y Xia, C Shen - IEEE transactions on medical …, 2019 - ieeexplore.ieee.org
Automated skin lesion classification in dermoscopy images is an essential way to improve
the diagnostic performance and reduce melanoma deaths. Although deep convolutional …

Transformation-consistent self-ensembling model for semisupervised medical image segmentation

X Li, L Yu, H Chen, CW Fu, L Xing… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
A common shortfall of supervised deep learning for medical imaging is the lack of labeled
data, which is often expensive and time consuming to collect. This article presents a new …

Medical image classification using synergic deep learning

J Zhang, Y Xie, Q Wu, Y Xia - Medical image analysis, 2019 - Elsevier
The classification of medical images is an essential task in computer-aided diagnosis,
medical image retrieval and mining. Although deep learning has shown proven advantages …

Notice of retraction: AI techniques for COVID-19

AA Hussain, O Bouachir, F Al-Turjman… - IEEE access, 2020 - ieeexplore.ieee.org
Notice of Retraction "AI Techniques for COVID-19," by Adedoyin Ahmed Hussain; Ouns
Bouachir; Fadi Al-Turjman; Moayad A Page 1 Notice of Retraction "AI Techniques for COVID-19," …

Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks

MA Al-Masni, MA Al-Antari, MT Choi, SM Han… - Computer methods and …, 2018 - Elsevier
Background and objective Automatic segmentation of skin lesions in dermoscopy images is
still a challenging task due to the large shape variations and indistinct boundaries of the …