A survey of feature extraction in dermoscopy image analysis of skin cancer
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 …
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
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 …
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 …
an uncontrolled manner. Melanoma goes under a few different names, including malignant …
Bcn20000: Dermoscopic lesions in the wild
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 …
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
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 …
of medical image analysis. Some deep learning architectures have been proposed and …
Attention residual learning for skin lesion classification
Automated skin lesion classification in dermoscopy images is an essential way to improve
the diagnostic performance and reduce melanoma deaths. Although deep convolutional …
the diagnostic performance and reduce melanoma deaths. Although deep convolutional …
Transformation-consistent self-ensembling model for semisupervised medical image segmentation
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 …
data, which is often expensive and time consuming to collect. This article presents a new …
Medical image classification using synergic deep learning
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 …
medical image retrieval and mining. Although deep learning has shown proven advantages …
Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks
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 …
still a challenging task due to the large shape variations and indistinct boundaries of the …
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," …
Bouachir; Fadi Al-Turjman; Moayad A Page 1 Notice of Retraction "AI Techniques for COVID-19," …