12 datasets found

The proposed approach for classifying skin lesions using smartphone-captured images and metadata.

The dataset used in the paper to evaluate the proposed two-stage approximately orthogonal training framework (TAOTF) for Deep Neural Networks (DNNs).

The ISIC_MSK2_1 dataset is a collection of dermoscopy images used for skin lesion classification. The dataset consists of 334 melanoma images, 3 seborrheic keratosis images, and...

The ISIC 2017 Skin Lesion Classification Challenge dataset is a collection of dermoscopy images used for skin lesion classification. The dataset consists of 2,000 images of skin...

The Dermatologist-level Classification of Skin Cancer dataset is a collection of dermoscopic images of skin lesions.

The BCN20000 dataset is a collection of dermoscopic images of skin lesions from Barcelona.

The International Skin Imaging Collaboration (ISIC) 2019 dataset is a multi-source dataset for dermoscopic lesion classification. It consists of 25,531 images corresponding to...

The ISIC 2017 skin lesion classification dataset contains 2000 training, 150 validation, and 600 test images.

The dataset used in this paper for multi-label skin lesion classification using dermoscopy and clinical images.

Medical image segmentation is vital to the area of imaging because it enables professionals to more accurately examine and understand the information offered by different...

Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (isic).

The dataset used in the paper is HAM10000, which is a dermoscopic image classification dataset. It contains 10,015 dermoscopic images categorized into 7 lesion types.