TTDF: A Two-Stage Framework for Reliable Surgical Phase Transition Detection

📅 2026-09-13
📈 Citations: 0
Influential: 0
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🤖 AI Summary
为解决手术阶段转换检测的可靠性问题,提出两阶段过渡检测框架TTDF,通过过滤候选转换并验证来提高检测准确性。
📝 Abstract
Reliable workflow transition detection is important for context-aware surgical assistance and downstream decision support. However, online surgical phase recognizers primarily focus on frame-wise accuracy and temporal consistency, rather than the reliability of workflow transition events. Directly converting phase changes into events is unreliable: temporal jitter and workflow-illegal switches produce false or duplicate events, while persistent, workflow-consistent candidates may remain incorrect. To address this limitation, we formulate reliable workflow transition detection as a distinct event-level task operating on outputs of a frozen online phase recognizer. We propose the Two-Stage Transition Detection Framework (TTDF), a causal framework that progressively filters transition candidates. Transition Candidate Extraction (TCE) first applies a minimum-duration requirement and a workflow-graph constraint to remove false candidates caused by temporal jitter and phase transitions not allowed by the workflow graph. Specifically, a candidate is retained only if the predicted target phase persists for a minimum duration and the ordered phase pair belongs to the workflow graph's allowed transition set. TCE thereby produces a high-recall candidate set without additional training. Transition Candidate Verification (TCV) suppresses remaining false candidates using phase-posterior shifts and visual-change cues from frozen DINOv2 features. Events are assessed using a phase-pair-aware one-to-one matching protocol. Experiments on Cholec80 show that TTDF reduces false transition emissions while preserving recall and controlling decision delay.
Problem

Research questions and friction points this paper is trying to address.

surgical phase recognition
workflow transition detection
reliability
temporal jitter
false events
Innovation

Methods, ideas, or system contributions that make the work stand out.

Two-Stage Transition Detection Framework (TTDF)
Transition Candidate Extraction (TCE)
Transition Candidate Verification (TCV)
DINOv2 features
phase-pair-aware one-to-one matching protocol
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