IMA++: ISIC Archive Multi-Annotator Dermoscopic Skin Lesion Segmentation Dataset
Analysis
This article introduces a new dataset for skin lesion segmentation, focusing on multi-annotator data. This suggests an effort to improve the robustness and reliability of AI models trained on this data by accounting for inter-annotator variability. The use of the ISIC archive indicates a focus on a well-established and widely used dataset, which could facilitate comparison with existing methods. The focus on dermoscopic images suggests a medical application.
Key Takeaways
- •New dataset for skin lesion segmentation.
- •Focus on multi-annotator data to improve model robustness.
- •Utilizes the ISIC archive, facilitating comparison with existing methods.
- •Application in medical imaging (dermoscopy).
Reference
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