What Are the Challenges of Automatic Segmentation in Cancer?
Despite its advantages, automatic segmentation faces several challenges. One major issue is the variability in medical imaging data across different machines and protocols, which can affect the performance of segmentation algorithms. Another challenge is the complexity and heterogeneity of tumors, which may vary widely in shape, size, and location. Additionally, the need for large, annotated datasets to train AI models can be a bottleneck, particularly for rare cancer types. Finally, regulatory and ethical concerns regarding the deployment of AI in clinical settings must be addressed.
