WonDerM: Skin lesion classification with fine-tuned neural networks
As skin cancer is one of the most frequent cancers globally, accurate, non-invasive
dermoscopy-based diagnosis becomes essential and promising. A task of the Part 3 of the …
dermoscopy-based diagnosis becomes essential and promising. A task of the Part 3 of the …
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 …
Skin lesion classification via combining deep learning features and clinical criteria representations
Skin lesion is a severe disease globally. Early detection of melanoma in dermoscopy
images significantly increases the survival rate. However, the accurate recognition of skin …
images significantly increases the survival rate. However, the accurate recognition of skin …
Skin lesion classification using additional patient information
Q Sun, C Huang, M Chen, H Xu… - BioMed research …, 2021 - Wiley Online Library
In this paper, we describe our method for skin lesion classification. The goal is to classify
skin lesions based on dermoscopic images to several diagnoses' classes presented in the …
skin lesions based on dermoscopic images to several diagnoses' classes presented in the …
Transfer learning for melanoma detection: Participation in ISIC 2017 skin lesion classification challenge
DH Murphree, C Ngufor - arXiv preprint arXiv:1703.05235, 2017 - arxiv.org
This manuscript describes our participation in the International Skin Imaging Collaboration's
2017 Skin Lesion Analysis Towards Melanoma Detection competition. We participated in …
2017 Skin Lesion Analysis Towards Melanoma Detection competition. We participated in …
Skin lesion analysis toward accurate detection of melanoma using multistage fully connected residual network
I Razzak, G Shoukat, S Naz… - 2020 International Joint …, 2020 - ieeexplore.ieee.org
Automatic classification of skin disease is a challenging task due to high similarity among
them as well as complex nature of skin images ie hair, skin and nails and illumination …
them as well as complex nature of skin images ie hair, skin and nails and illumination …
Skin lesion classification with deep CNN ensembles
Early detection of skin cancer is vital when treatment is most likely to be successful.
However, diagnosis of skin lesions is a very challenging task due to the similarities between …
However, diagnosis of skin lesions is a very challenging task due to the similarities between …
Analysis of skin lesion images with deep learning
J Steppan, S Hanke - arXiv preprint arXiv:2101.03814, 2021 - arxiv.org
Skin cancer is the most common cancer worldwide, with melanoma being the deadliest form.
Dermoscopy is a skin imaging modality that has shown an improvement in the diagnosis of …
Dermoscopy is a skin imaging modality that has shown an improvement in the diagnosis of …
Automatic skin lesion classification using a new densely connected convolutional network with an SF module
P Shan, C Fu, L Dai, T Jia, M Tie, J Liu - Medical & Biological Engineering …, 2022 - Springer
The automatic classification of skin lesions in dermoscopy images remains challenging due
to the morphological diversity of skin lesions, the existence of intrinsic cutaneous features …
to the morphological diversity of skin lesions, the existence of intrinsic cutaneous features …
(De) Constructing bias on skin lesion datasets
Melanoma is the deadliest form of skin cancer. Automated skin lesion analysis plays an
important role for early detection. Nowadays, the ISIC Archive and the Atlas of Dermoscopy …
important role for early detection. Nowadays, the ISIC Archive and the Atlas of Dermoscopy …