Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study

Czempiel, Tobias; Sharghi, Aidean; Paschali, Magdalini; Navab, Nassir; Mohareri, Omid

doi:10.1007/978-3-031-25066-8_32

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…Assessment of surgical workflow is critical for evaluating surgeon skill, case complexity and surgery variability. The scarcity of procedure‐specific annotated data hinders the quantitative analysis of surgical workflow, consequently limiting the ability to provide targeted feedback and objective insights 1 . Subjective operative reports are currently the primary source of information regarding surgical workflow.…”

Section: Introductionmentioning

confidence: 99%

Quantification of surgical workflow during robotic proctectomy

Gillani,

Rupji,

Devin

et al. 2024

Robotics Computer Surgery

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BackgroundSurgical workflow assessments offer insight regarding procedure variability. We utilised an objective method to evaluate workflow during robotic proctectomy (RP).MethodsWe annotated 31 RPs and used Spearman's correlation to measure the correlation of step time and step visit frequency with console time (CT) and total operative time (TOT).ResultsStrong correlations were seen with CT and step times for inferior mesenteric vein dissection and ligation (ρ = 0.60, ρ = 0.60), lateral‐to‐medial splenic flexure mobilisation (SFM) (ρ = 0.63), left rectal dissection (ρ = 0.64) and mesorectal division (ρ = 0.71). CT correlated strongly with medial‐to‐lateral (ρ = 0.75) and supracolic SFM visit frequency (ρ = 0.65). TOT correlated strongly with initial exposure time (ρ = 0.60), and medial‐to‐lateral (ρ = 0.67) and supracolic SFM visit frequency (ρ = 0.65).ConclusionThis study correlates surgical steps with CT and TOT through standardised annotation, providing an objective approach to quantify workflow.

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Section: Introductionmentioning

confidence: 99%

Quantification of surgical workflow during robotic proctectomy

Gillani,

Rupji,

Devin

et al. 2024

Robotics Computer Surgery

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“…All of these methods utilize what we refer to as latent temporality, which is a non-interpretable, hidden feature representation. While some works utilize twostage architectures, where the temporal stage uses precomputed features from a single timepoint neural network, others use 3D(2D + time) methods, directly considering multiple timepoints [3].…”

Section: Introductionmentioning

confidence: 99%

LABRAD-OR: Lightweight Memory Scene Graphs for Accurate Bimodal Reasoning in Dynamic Operating Rooms

Özsoy¹,

Czempiel²,

Holm³

et al. 2023

Preprint

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Modern surgeries are performed in complex and dynamic settings, including ever-changing interactions between medical staff, patients, and equipment. The holistic modeling of the operating room (OR) is, therefore, a challenging but essential task, with the potential to optimize the performance of surgical teams and aid in developing new surgical technologies to improve patient outcomes. The holistic representation of surgical scenes as semantic scene graphs (SGG), where entities are represented as nodes and relations between them as edges, is a promising direction for fine-grained semantic OR understanding. We propose, for the first time, the use of temporal information for more accurate and consistent holistic OR modeling. Specifically, we introduce memory scene graphs, where the scene graphs of previous time steps act as the temporal representation guiding the current prediction. We design an end-to-end architecture that intelligently fuses the temporal information of our lightweight memory scene graphs with the visual information from point clouds and images. We evaluate our method on the 4D-OR dataset and demonstrate that integrating temporality leads to more accurate and consistent results achieving an +5% increase and a new SOTA of 0.88 in macro F1. This work opens the path for representing the entire surgery history with memory scene graphs and improves the holistic understanding in the OR. Introducing scene graphs as memory representations can offer a valuable tool for many temporal understanding tasks.

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