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A Image Transformer-based Streaming Framework for Variable-Length Flap Perfusion Monitoring with Dynamic State Tracking

The paper presents FlapFlowNet, a Transformer-based streaming framework that achieves high-accuracy, real-time perfusion monitoring for variable-length flap surgery sequences by combining a lightweight CNN, temporal modeling, and a medical-optimized loss function to significantly reduce critical false-negative rates.

Original authors: Wenli Zhang, Gechang Cheng, Yiyu Peng, Hualin Zeng, Guoling Zhou, Lingli Peng

Published 2026-09-08
📖 1 min read☕ Coffee break read

Original authors: Wenli Zhang, Gechang Cheng, Yiyu Peng, Hualin Zeng, Guoling Zhou, Lingli Peng

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

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