12 datasets found

Segmentation is essential for medical image analysis to identify and localize diseases, monitor morphological changes, and extract discriminative features for further diagnosis....

The ISIC 2017 dataset is a collection of images of skin lesions, with annotations for segmentation.

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

ISIC-2016 and PH2 dataset contains 900 samples with lesion segmentations from dermoscopic images.

Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma.

ISIC 2018 dataset for skin lesion segmentation.

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

Skin Lesion Analysis dataset for melanoma detection

Skin lesion segmentation dataset for PH2

The proposed model, MobileGAN, is a lightweight and efficient GAN model for skin lesion segmentation. It combines 1-D kernel factorized networks, position and channel attention,...

Skin lesion segmentation dataset

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