The SLICE-3D dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection

The SLICE-3D dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection

AI image classification algorithms have shown promising results when applied to skin cancer detection. Most public skin cancer image datasets are comprised of dermoscopic photos and are limited by selection bias, lack of standardization, and lend themselves to development of algorithms that can only...

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Bibliographic Details
Published in:Scientific data Vol. 11; no. 1; pp. 884 - 11
Main Authors: Kurtansky, Nicholas R., D’Alessandro, Brian M., Gillis, Maura C., Betz-Stablein, Brigid, Cerminara, Sara E., Garcia, Rafael, Girundi, Marcela Alves, Goessinger, Elisabeth Victoria, Gottfrois, Philippe, Guitera, Pascale, Halpern, Allan C., Jakrot, Valerie, Kittler, Harald, Kose, Kivanc, Liopyris, Konstantinos, Malvehy, Josep, Mar, Victoria J., Martin, Linda K., Mathew, Thomas, Maul, Lara Valeska, Mothershaw, Adam, Mueller, Alina M., Mueller, Christoph, Navarini, Alexander A., Rajeswaran, Tarlia, Rajeswaran, Vin, Saha, Anup, Sashindranath, Maithili, Serra-García, Laura, Soyer, H. Peter, Theocharis, Georgios, Vos, Ayesha, Weber, Jochen, Rotemberg, Veronica
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 14-08-2024
Nature Publishing Group
Nature Portfolio
Subjects:
692/699/67/1813/1349
692/699/67/1813/1352
692/699/67/1813/1634
692/700/1421/2109
Algorithms
Crops
Data Descriptor
Datasets
Humanities and Social Sciences
Humans
Image processing
Imaging, Three-Dimensional
multidisciplinary
Primary care
Science
Science (multidisciplinary)
Skin - diagnostic imaging
Skin cancer
Skin diseases
Skin lesions
Skin Neoplasms - diagnostic imaging
Online Access:Get full text
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Description
Summary:AI image classification algorithms have shown promising results when applied to skin cancer detection. Most public skin cancer image datasets are comprised of dermoscopic photos and are limited by selection bias, lack of standardization, and lend themselves to development of algorithms that can only be used by skilled clinicians. The SLICE-3D (“Skin Lesion Image Crops Extracted from 3D TBP”) dataset described here addresses those concerns and contains images of over 400,000 distinct skin lesions from seven dermatologic centers from around the world. De-identified images were systematically extracted from sensitive 3D Total Body Photographs and are comparable in optical resolution to smartphone images. Algorithms trained on lower quality images could improve clinical workflows and detect skin cancers earlier if deployed in primary care or non-clinical settings, where photos are captured by non-expert physicians or patients. Such a tool could prompt individuals to visit a specialized dermatologist. This dataset circumvents many inherent limitations of prior datasets and may be used to build upon previous applications of skin imaging for cancer detection.
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-024-03743-w