PPOC-LL: Prototype Learning for Efficient Medical Landmark Localization
The PPOC-LL model, a novel parameter-economic approach for localizing medical landmarks, has been introduced to tackle the significant computational demands associated with multi-stage refinement techniques. This model utilizes progressive offset correction based on prototype learning to refine landmarks from coarse to fine. Additionally, it incorporates a multi-scale dynamic perception strategy for modeling patch-level feature pyramids and employs a similarity-driven prototype learning mechanism to manage anatomically similar patterns. The goal of this method is to reduce anatomical ambiguity and enhance practical use. Detailed findings are available in arXiv paper 2608.09182v2.
Key facts
- PPOC-LL is a parameter-economic model for landmark localization.
- It uses prototype learning-based progressive offset correction.
- The model introduces a multi-scale dynamic perception strategy.
- A similarity-driven prototype learning mechanism is designed.
- The approach addresses high computational costs of multi-stage refinement.
- It aims to mitigate anatomical ambiguity in single-stage predictions.
- The paper is available on arXiv with ID 2608.09182v2.
- The research focuses on medical image analysis.
Entities
Institutions
- arXiv