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arxiv: 2510.20087 · v2 · submitted 2025-10-23 · 💻 cs.CV

Endoshare: A Publicly Available, Surgeons-Friendly Solution to De-Identify and Manage Surgical Videos

Lorenzo Arboit , Dennis N. Schneider , Britty Baby , Vinkle Srivastav , Pietro Mascagni , Nicolas Padoy This is my paper

Pith reviewed 2026-05-18 05:28 UTC · model grok-4.3

classification 💻 cs.CV
keywords surgical video de-identificationendoscopic video managementusability evaluationprivacy-preserving toolsvideo standardizationsurgeon interface designopen source medical softwarevideo-based surgical assessment
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The pith

Endoshare provides a surgeon-friendly way to merge, standardize, and de-identify endoscopic videos.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces Endoshare as an open tool for managing surgical videos by merging files, converting formats, removing patient identifiers, and automating out-of-body segments. It was built using user-centered design with input from clinicians and computer scientists to meet real workflow needs. Surveys from internal and external users gave high marks for usability and usefulness, suggesting it can help overcome privacy and compatibility issues that hinder video use in surgery. This matters because wider video sharing could improve training, research, and quality control in operating rooms.

Core claim

Endoshare is a publicly available, surgeon-friendly solution to merge, standardize, and de-identify endoscopic videos. Development followed an iterative, user-centered software life cycle with privacy-by-design. Prototype testing showed high usability scores for clinicians and computer scientists, and external surgeon surveys reported high perceived usefulness, ease of use, and recommendation likelihood. Processing performance scales with video duration but is efficient in fast mode.

What carries the argument

The Endoshare application with its cross-platform privacy-by-design architecture that automates video merging, standardization, out-of-body removal, and filename pseudonymization through a streamlined user interface.

If this is right

  • Clinicians can share surgical videos more readily for educational and research purposes without violating privacy regulations.
  • Standardized video formats enable better interoperability for surgical data science applications.
  • Automated de-identification reduces the manual effort required to prepare videos for analysis.
  • High usability scores indicate the tool fits into existing surgical workflows with minimal training.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Integration with electronic health records could further automate the video management pipeline in hospitals.
  • Community contributions to the open-source code might extend support for new video formats or add AI-based analysis features.
  • Long-term use could contribute to larger shared datasets for developing better surgical AI models.

Load-bearing premise

Small-scale surveys with a handful of participants from specific groups accurately reflect the preferences and requirements of the global surgical community.

What would settle it

A field study tracking the number of videos processed and shared by surgeons using Endoshare over a year compared to current practices would show if adoption and impact are as high as the survey ratings suggest.

Figures

Figures reproduced from arXiv: 2510.20087 by Britty Baby, Dennis N. Schneider, Lorenzo Arboit, Nicolas Padoy, Pietro Mascagni, Vinkle Srivastav.

Figure 1
Figure 1. Figure 1: Endoshare architecture and interface. many seconds are required to process one minute of video. All analyses were conducted in Python using pandas, SciPy, and Statsmodels. 3. Results Endoshare is a publicly available application, freely down￾loadable from the following website. The source code is avail￾able at this GitHub repository. Thorough documentation is provided to support peer review, reproducibilit… view at source ↗
Figure 2
Figure 2. Figure 2: Overview of the Endoshare processing pipeline. A) Video merging and standardization combine disparate clips into a single, uniform file; B) File pseudonymization replaces patient identifiers with randomized tokens and strips all embedded metadata; C) AI-powered de-identification detects camera insertion frames, automatically blurs out-of-body scenes, and ensures any remaining identifiable content is masked… view at source ↗
Figure 3
Figure 3. Figure 3: Distribution of user practices in surgical video workflows across four domains. A) preferred recording methods; B) long-term storage locations; C) [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Radar chart summarizing usability evaluations across three domains: Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Heuristic Usability [PITH_FULL_IMAGE:figures/full_fig_p007_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Benchmarking Endoshare performance. Processing speed of En￾doshare across three hardware configurations (macOS laptop, Windows av￾erage desktop, Linux high-end desktop) for 1-, 30-, and 60-minute videos in both fast and advanced modes. Bars indicate geometric mean processing time relative to video duration. tionship between processing time and video length. Mean slope estimates were 9.22 s/min for fast mod… view at source ↗
Figure 6
Figure 6. Figure 6: Schematic overview of the Endoshare implementation within surgical practice. Endoscopic procedures are recorded and transferred via external storage to any computer with Endoshare installed; the platform then automates merging and de-identification, facilitating use and enabling privacy-preserving sharing of videos for education, multicenter research, and laboratory analysis. drawn from user feedback. Futu… view at source ↗
read the original abstract

Video-based assessment and surgical data science can advance surgical training, research, and quality improvement, yet adoption remains limited by heterogeneous recording formats and privacy concerns linked to video sharing. This work develops, evaluates, and publicly releases Endoshare, a surgeon-friendly application that merges, standardizes, and de-identifies endoscopic videos. Development followed an iterative, user-centered software life cycle. In the analysis phase, an internal survey of four clinicians and four computer scientists, based on 10 usability heuristics, identified early requirements and guided a cross-platform, privacy-by-design architecture. Prototype testing reported high usability for clinicians (4.68 +/- 0.40 out of 5) and for computer scientists (4.03 +/- 0.51 out of 5), with the lowest score (4.00 +/- 0.93 out of 5) relating to label clarity, prompting interface refinement to streamline case selection, video merging, automated out-of-body removal, and filename pseudonymization. In the testing phase, ten surgeons completed an external survey combining the same heuristics with Technology Acceptance Model constructs, reporting high perceived usefulness (5.07 +/- 1.75 out of 7), ease of use (5.15 +/- 1.71 out of 7), heuristic usability (4.38 +/- 0.48 out of 5), and strong recommendation likelihood (9.20 +/- 0.79 out of 10). A performance assessment across different hardware and configurations showed that processing time increased proportionally with video duration and was consistently lower in fast mode. Endoshare is a publicly available solution to manage surgical videos, with potential to support training, research, and quality improvement. Compliance certification and broader interoperability validation are needed to establish it as a reliable tool for surgical video management. The software is available at https://camma-public.github.io/Endoshare

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper presents Endoshare, a publicly available cross-platform application for merging, standardizing, and de-identifying endoscopic surgical videos using a privacy-by-design architecture. Development followed an iterative user-centered process: an internal survey of four clinicians and four computer scientists using 10 usability heuristics informed requirements; prototype testing showed high usability (clinicians 4.68 ± 0.40/5, computer scientists 4.03 ± 0.51/5), with refinements for case selection, video merging, automated out-of-body removal, and filename pseudonymization; an external survey of ten surgeons using the same heuristics plus Technology Acceptance Model constructs reported high perceived usefulness (5.07 ± 1.75/7), ease of use (5.15 ± 1.71/7), heuristic usability (4.38 ± 0.48/5), and recommendation likelihood (9.20 ± 0.79/10). Performance tests across hardware indicated processing time scales proportionally with video duration and is lower in fast mode. The software is released at https://camma-public.github.io/Endoshare, with notes on needed compliance certification and broader validation.

Significance. If the usability and acceptance findings hold more broadly, Endoshare offers a practical open-source tool that directly tackles format heterogeneity and privacy barriers in surgical video sharing, supporting advances in training, research, and quality improvement. Strengths include the public release, explicit performance scaling observations, user-centered iterative design, and self-acknowledgment of remaining validation needs. These elements enhance reproducibility and potential utility in surgical data science. The small participant pools in the key evaluation surveys, however, constrain how strongly the 'surgeon-friendly' characterization can be asserted at present.

major comments (2)
  1. [Testing phase] Testing phase, external survey paragraph: The acceptance claims rest on an external survey of only ten surgeons with no reported details on specialties, experience levels, geographic distribution, or institutional workflows. This small sample and unspecified diversity make the high perceived usefulness (5.07/7) and recommendation likelihood (9.20/10) scores susceptible to selection bias and weaken the generalizability of the 'surgeon-friendly' and high-acceptance conclusions to the broader surgical community.
  2. [Analysis phase] Analysis phase, internal survey description: The internal survey with four clinicians and four computer scientists is presented as identifying early requirements, yet the manuscript provides no quantitative comparison of usability scores before and after the interface refinements (e.g., label clarity improvements). This leaves the causal link between the survey findings and the reported prototype usability gains (4.68/5 and 4.03/5) under-supported.
minor comments (2)
  1. [Abstract] Abstract and conclusion: The statement that 'Compliance certification and broader interoperability validation are needed' is appropriate but could specify relevant standards (e.g., HIPAA, GDPR, or DICOM) and outline a concrete plan for future work to strengthen the practical-utility narrative.
  2. [Performance assessment] Performance assessment section: A summary table of processing times versus video duration and hardware configurations would improve readability and allow direct comparison of the 'fast mode' advantage across conditions.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive review and recommendation for minor revision. The comments highlight important considerations for strengthening the presentation of our evaluation results. We address each major comment below and have revised the manuscript to better contextualize the survey findings and acknowledge limitations.

read point-by-point responses

  1. Referee: [Testing phase] Testing phase, external survey paragraph: The acceptance claims rest on an external survey of only ten surgeons with no reported details on specialties, experience levels, geographic distribution, or institutional workflows. This small sample and unspecified diversity make the high perceived usefulness (5.07/7) and recommendation likelihood (9.20/10) scores susceptible to selection bias and weaken the generalizability of the 'surgeon-friendly' and high-acceptance conclusions to the broader surgical community.

    Authors: We agree that the external survey of ten surgeons represents a modest sample and that the absence of detailed participant demographics limits strong claims of generalizability. This evaluation was conducted as a pilot with surgeons from collaborating institutions to gather initial feedback on usability and acceptance. In the revised manuscript, we have added available details on the participant pool (specialties and approximate experience levels) and included an explicit limitations paragraph noting the potential for selection bias and the preliminary nature of these findings. We have also tempered language regarding broad 'surgeon-friendly' characterization while preserving the reported scores as evidence of positive reception in this cohort, consistent with our existing note on the need for broader validation. revision: yes

  2. Referee: [Analysis phase] Analysis phase, internal survey description: The internal survey with four clinicians and four computer scientists is presented as identifying early requirements, yet the manuscript provides no quantitative comparison of usability scores before and after the interface refinements (e.g., label clarity improvements). This leaves the causal link between the survey findings and the reported prototype usability gains (4.68/5 and 4.03/5) under-supported.

    Authors: The internal survey was used qualitatively to identify specific issues, including the lowest score of 4.00 on label clarity, which directly guided refinements to case selection, video merging, and related features. The reported prototype scores reflect the version after these changes. A formal pre-post quantitative comparison was not performed given the iterative development approach and limited resources for repeated testing. We have revised the manuscript to more explicitly describe the survey-identified issues and the corresponding interface modifications, thereby clarifying the connection between feedback and improvements without implying a controlled before-after experiment. revision: partial

Circularity Check

0 steps flagged

No circularity: empirical usability evaluation with direct survey data

full rationale

The paper describes an iterative user-centered software development process for Endoshare, followed by prototype testing and external surveys using usability heuristics and Technology Acceptance Model constructs. All central claims rest on reported empirical results from small participant groups (internal n=8, external n=10) and hardware performance timings, with no equations, fitted parameters, predictions, or self-citations invoked as load-bearing justifications. The derivation chain is self-contained because it consists of straightforward data collection and reporting rather than any reduction of outputs to inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The paper relies on standard software engineering practices and established usability assessment methods without introducing free parameters, new axioms beyond domain assumptions about privacy barriers, or invented entities.

axioms (1)
  • domain assumption Privacy concerns and heterogeneous recording formats limit adoption of video-based surgical data science
    Invoked in the opening of the abstract as the motivation for developing the tool.

pith-pipeline@v0.9.0 · 5902 in / 1428 out tokens · 48795 ms · 2026-05-18T05:28:00.490463+00:00 · methodology

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    unclear

    Relation between the paper passage and the cited Recognition theorem.

    Prototype testing reported high usability for clinicians (4.68 +/- 0.40 out of 5) and for computer scientists (4.03 +/- 0.51 out of 5)... ten surgeons completed an external survey combining the same heuristics with Technology Acceptance Model constructs

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Reference graph

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