DERMA-OCTA: A Comprehensive Dataset and Preprocessing Pipeline for Dermatological OCTA Vessel Segmentation.

Journal: Scientific data
Published Date:

Abstract

Optical coherence tomography angiography (OCTA) has emerged as a promising tool for non-invasive vascular imaging in dermatology. However, the field lacks standardized methods for processing and analyzing these complex images, as well as sufficient annotated datasets for developing automated analysis tools. We present DERMA-OCTA, the first open-access dermatological OCTA dataset, comprising 330 volumetric scans from 74 subjects with various skin conditions. The dataset contains the original 2D and 3D OCTA acquisitions, as well as versions processed with five different preprocessing methods, and the reference 2D and 3D segmentations. For each version, segmentation labels are provided, generated using the U-Net architecture as 2D and 3D segmentation approaches. By providing high-resolution, annotated OCTA data across a range of skin pathologies, this dataset offers a valuable resource for training deep learning models, benchmarking segmentation algorithms, and facilitating research into non-invasive skin imaging. The DERMA-OCTA dataset is freely downloadable.

Authors

  • Giulia Rotunno
    Biolab, PolitoBIOMedLab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.
  • Massimo Salvi
  • Julia Deinsberger
    Department of Dermatology, Medical University of Vienna, Vienna, Austria.
  • Lisa Krainz
    Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
  • Benedikt Weber
    Department of Dermatology, Medical University of Vienna, Vienna, Austria.
  • Christoph Sinz
    ViDIR Group, Department of Dermatology, Medical University of Vienna, Vienna, Austria. Electronic address: christoph.sinz@meduniwien.at.at.
  • Harald Kittler
    ViDIR Group, Department of Dermatology, Medical University of Vienna, Vienna, Austria. Electronic address: harald.kittler@meduniwien.at.at.
  • Leopold Schmetterer
    Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
  • Wolfgang Drexler
    Center for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, Austria.
  • Mengyang Liu
    School of Pharmacy, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.
  • Kristen M Meiburger
    Department of Electronics and Telecommunications, Politecnico di Torino, Italy.