AI-based planning for DIEAP flap procedures: exploring foundation models for artery perforators analysis

Abstract

This study demonstrates the feasibility of an end-to-end, artificial intelligence (AI)-driven workflow for perforator mapping in DIEAP flap planning. The use of foundation models guided by anatomical priors and enhanced with topology-aware fine-tuning establishes a robust method for reducing manual annotation burden and improving consistency. This automated pipeline is a promising tool to support more efficient and reliable preoperative planning, ultimately poised to improve surgical outcomes.

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