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 …
Experiments using deep learning for dermoscopy image analysis
CN Vasconcelos, BN Vasconcelos - Pattern Recognition Letters, 2020 - Elsevier
Skin cancer is a major public health problem, as is the most common type of cancer and
represents more than half of cancer diagnosed worldwide. Early detection influences the …
represents more than half of cancer diagnosed worldwide. Early detection influences the …
The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
Training of neural networks for automated diagnosis of pigmented skin lesions is hampered
by the small size and lack of diversity of available datasets of dermatoscopic images. We …
by the small size and lack of diversity of available datasets of dermatoscopic images. We …
Deep learning for skin cancer diagnosis with hierarchical architectures
C Barata, JS Marques - 2019 IEEE 16th International …, 2019 - ieeexplore.ieee.org
Skin lesions are organized in a hierarchical way, which is taken into account by
dermatologists when diagnosing them. However, automatic systems do not make use of this …
dermatologists when diagnosing them. However, automatic systems do not make use of this …
Automated skin lesion classification using ensemble of deep neural networks in isic 2018: Skin lesion analysis towards melanoma detection challenge
MAA Milton - arXiv preprint arXiv:1901.10802, 2019 - arxiv.org
In this paper, we studied extensively on different deep learning based methods to detect
melanoma and skin lesion cancers. Melanoma, a form of malignant skin cancer is very …
melanoma and skin lesion cancers. Melanoma, a form of malignant skin cancer is very …
[HTML][HTML] DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation
Abstract Background and Objective: Although automated Skin Lesion Classification (SLC) is
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (isic)
This work summarizes the results of the largest skin image analysis challenge in the world,
hosted by the International Skin Imaging Collaboration (ISIC), a global partnership that has …
hosted by the International Skin Imaging Collaboration (ISIC), a global partnership that has …
Machine learning and deep learning algorithms for skin cancer classification from dermoscopic images
S Bechelli, J Delhommelle - Bioengineering, 2022 - mdpi.com
We carry out a critical assessment of machine learning and deep learning models for the
classification of skin tumors. Machine learning (ML) algorithms tested in this work include …
classification of skin tumors. Machine learning (ML) algorithms tested in this work include …
Incorporating the knowledge of dermatologists to convolutional neural networks for the diagnosis of skin lesions
IG Díaz - arXiv preprint arXiv:1703.01976, 2017 - arxiv.org
This report describes our submission to the ISIC 2017 Challenge in Skin Lesion Analysis
Towards Melanoma Detection. We have participated in the Part 3: Lesion Classification with …
Towards Melanoma Detection. We have participated in the Part 3: Lesion Classification with …
Uncertainty estimation in deep neural networks for dermoscopic image classification
The high performance of machine learning algorithms for the task of skin lesion classification
has been proven over the past few years. However, real-world implementations are still …
has been proven over the past few years. However, real-world implementations are still …