Improving Automatic Melanoma Diagnosis using Deep Learn-ing-based Segmentation of Irregular Networks

Irregular masks dataset created on a subset of the ISIC19 training dataset. All annotations are for melanoma lesions. The filename indicates the ISIC19 image id along with suffix indicating annotator and/or verifier. This dataset was used in the publication "Improving Automatic Melanoma Diagnos...

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Hauptverfasser: Nambisan, Anand K, Akanksha Maurya, Norsang Lama, Phan, Thanh, Gehana Patel, Miller, Keith, Binita Lama, Hagerty, Jason, Stanley, Ronald J, Stoecker, William V
Format: Dataset
Sprache:eng
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Zusammenfassung:Irregular masks dataset created on a subset of the ISIC19 training dataset. All annotations are for melanoma lesions. The filename indicates the ISIC19 image id along with suffix indicating annotator and/or verifier. This dataset was used in the publication "Improving Automatic Melanoma Diagnosis using Deep Learn-ing-based Segmentation of Irregular Networks" to be submitted to the Cancers Journal. Please cite the corresponding article (to be published) if data is used in your work. The references for the ISIC19 dataset that this is built on is given below. BCN_20000 Dataset: (c) Department of Dermatology, Hospital Clínic de Barcelona HAM10000 Dataset: (c) by ViDIR Group, Department of Dermatology, Medical University of Vienna; https://doi.org/10.1038/sdata.2018.161 MSK Dataset: (c) Anonymous; https://arxiv.org/abs/1710.05006; https://arxiv.org/abs/1902.03368
DOI:10.5281/zenodo.7557346