Published March 8, 2023
| Version v2
Dataset
Open
Basal cell carcinoma diagnosis with fusion of deep learning and telangiectasia features
Authors/Creators
- 1. Missouri University of Science & Technology
- 2. Ford Motor Company
- 3. University of Missouri - Columbia
- 4. University of Missouri - Columbia
- 5. A.T. Still University of Health Sciences
- 6. University of Missouri - Kansas City
- 7. S&A Technologies
Description
Telangiectasia masks dataset created on a subset of the ISIC18, ISIC19 training datasets and the NIH study dataset R43 CA153927-01 and CA101639-02A2. All annotations are for Basal Cell Carcinoma lesions. This is an expanded dataset that was initially used in “A Deep Learning Approach to Detect Blood Vessels in Basal Cell Carcinoma”.
A sample lesion image and the corresponding mask is provided for preview. Lesion images and masks have been uploaded as separate zipped folders that can be downloaded.
Files
images.zip
Additional details
References
- 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
- NIH study dataset R43 CA153927-01 and CA101639-02A2