A dataset of 100K synthetic images of skin lesions, ground-truth (GT) segmentations of lesions and healthy skin, GT segmentations of seven body parts (head, torso, hips, legs, feet, arms and hands), and GT binary masks of non-skin regions in the texture maps of 215 scans from the 3DBodyTex.v1 dataset [2], [3] created using the framework described in [1]. The dataset is primarily intended to enable the development of skin lesion analysis methods. Synthetic image creation consisted of two main steps. First, skin lesions from the Fitzpatrick 17k dataset were blended onto skin regions of high-resolution three-dimensional human scans from the 3DBodyTex dataset [2], [3]. Second, two-dimensional renders of the modified scans were generated.

This data is the fruit of a collaboration between CVI2 and the Medical Image Analysis Labat the School of Computing Science of Simon Fraser University, Canada, which is represented by Prof. Dr. Ghassan Hamarneh.

Requesting the DermSynth3D Dataset

The 3DBodyTex.DermSynth3D dataset is available for use by external parties. Due to agreements signed by the volunteer models, a license agreement must be requested and signed by the recipient and the research administration office director of your institution before the data can be provided. To make a request for the data, please use the following contact form.


Conditions of Use

Use of the dataset, in part or in full, is conditional on citation of the following work: 

[1] Ashish Sinha, Jeremy Kawahara, Arezou Pakzad, Kumar Abhishek, Matthieu Ruthven, Enjie Ghorbel, Anis Kacem, Djamila Aouada, Ghassan Hamarneh, ‘DermSynth3D: Synthesis of in-the-wild annotated dermatology images’,  2023.  

[2] A. Saint, A. E. Rahman Shabayek, K. Cherenkova, G. Gusev, D. Aouada, and B. Ottersten, ‘Bodyfitr: Robust Automatic 3D Human Body Fitting’, in 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan: IEEE, Sep. 2019, pp. 484–488. doi: 10.1109/ICIP.2019.8803819. 

[3] A. Saint et al., ‘3DBodyTex: Textured 3D Body Dataset’, in 2018 International Conference on 3D Vision (3DV), Verona: IEEE, Sep. 2018, pp. 495–504. doi: 10.1109/3DV.2018.00063.

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