17 datasets found

DermaMNIST is a medical imaging dataset containing 7,000 images of skin lesions, each with a size of 224x224x3.

Automated medical image segmentation can assist doctors to diagnose faster and more accurate. Deep learning based models for medical image segmentation have made great progress...

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

Mpox Skin Lesion Dataset Version 2.0 (MSLD v2.0) is a publicly available dataset containing web-scraped images of patients with mpox and non-mpox cases, including chickenpox,...

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 PH2 dataset used for evaluation of the proposed deep learning model for automatic skin lesion segmentation on dermoscopic images.

ISIC 2018 dataset for skin lesion segmentation.

Four image datasets for medical image segmentation: thyroid nodule, liver and kidney, breast lesion, and skin lesion.

Skin lesion segmentation dataset

A dataset for dermoscopy images, used for testing the proposed DoubleU-Net architecture.

A dataset for skin lesion segmentation, used for testing the proposed DoubleU-Net architecture.

Skin lesion segmentation dataset for PH2

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

Skin lesion segmentation dataset

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

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

Polyp(CVC-ClinicDB and ETIS-LaribPolypDB), Skin(ISIC-2018 Skin lesion segmentation challenge dataset)