Unsupervised Brain Tumor Segmentation with Image-based Prompts

Understand

Automated brain tumor segmentation based on deep learning (DL) has achieved promising performance.

• However, it generally relies on annotated images for model training, which is not always feasible in clinical settings.
• Therefore, the development of unsupervised DL-based brain tumor segmentation approaches without expert annotations is desired.
• Motivated by the success of prompt learning (PL) in natural language processing, we propose an approach to unsupervised brain tumor segmentation by designing image-based prompts that allow indication of brain tumors, and this approach is dubbed as PL-based Brain Tumor Segmentation (PL-BTS).