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arxiv: 2604.25661 · v1 · submitted 2026-04-28 · cs.RO · cs.HC

SlicerRoboTMS: An Open-Source 3D Slicer Extension for Robot-Assisted Transcranial Magnetic Stimulation

Wenzhi Bai , Yituo Guo , Bhaskar Basu , Andrew Weightman , Zhenhong Li This is my paper

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel 2026-05-07 15:45 UTCgrok-4.3open to challenge →

classification cs.RO cs.HC
keywords Robo-TMS3D Slicerneuronavigationtranscranial magnetic stimulationrobot-assisted interventionopen-source extensionMRI guidancerobotic control
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0 comments X

The pith

SlicerRoboTMS supplies an open-source extension that links 3D Slicer's MRI tools directly to robotic hardware for consistent transcranial magnetic stimulation.

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

The paper presents SlicerRoboTMS as a free 3D Slicer module that handles MRI-based neuronavigation while connecting to robots through standard communication protocols and user-configurable hardware descriptions. This setup lets teams combine medical imaging, computer vision, and robotics without building every software layer from scratch each time. A working example shows the extension fitting into a full Robo-TMS procedure. The authors argue that releasing the code openly will let more groups test new coil placements and hardware combinations quickly and with matching results.

Core claim

SlicerRoboTMS creates a single software layer that reads MRI scans for precise brain targeting, sends movement commands to robots via established protocols, and accepts custom descriptions of different robotic arms or coils so the same interface works across varied laboratory setups.

What carries the argument

The SlicerRoboTMS extension, which supplies MRI neuronavigation and robotic control through standardized communication protocols together with configurable system descriptions.

Load-bearing premise

That the software integration will maintain reliable real-time accuracy when connected to actual MRI scanners and varied robotic hardware in live experiments.

What would settle it

A side-by-side test on a head phantom where the extension directs the robot coil to a planned MRI target yet the measured physical position deviates beyond the accepted clinical tolerance for TMS.

Figures

Figures reproduced from arXiv: 2604.25661 by Andrew Weightman, Bhaskar Basu, Wenzhi Bai, Yituo Guo, Zhenhong Li.

Figure 1
Figure 1. Figure 1: Contextual system architecture illustrating the role of SlicerRoboTMS view at source ↗
Figure 2
Figure 2. Figure 2: User interaction and visualisation layouts provided by SlicerRoboTMS. Two primary layouts are supported: (1) a system overview layout with a 3D view at source ↗
Figure 3
Figure 3. Figure 3: Experimental setup used for the example integration. The configuration includes: (1) an optical tracking camera (Intel RealSense D455), (2) a TMS view at source ↗
Figure 4
Figure 4. Figure 4: Integration architecture of the example SlicerRoboTMS-based Robo view at source ↗
read the original abstract

Robot-assisted Transcranial Magnetic Stimulation (Robo-TMS) is an image-guided robotic intervention that enhances the accuracy and reproducibility of conventional Transcranial Magnetic Stimulation (TMS), a widely used non-invasive brain stimulation procedure in clinical treatment and neuroscience research. Despite its potential, the development of Robo-TMS remains challenging due to the need for multidisciplinary expertise spanning medical imaging, computer vision, and robotics. This paper presents SlicerRoboTMS, an open-source 3D Slicer extension that provides a unified interaction infrastructure for Robo-TMS research. By leveraging 3D Slicer's medical image computing and visualisation capabilities, the extension supports Magnetic Resonance Imaging (MRI)-based neuronavigation and interfaces with robotic systems through standardised communication protocols and configurable system descriptions. An example integration is presented to demonstrate how SlicerRoboTMS can be incorporated into a representative Robo-TMS workflow. Designed to support diverse hardware configurations and rapid prototyping, SlicerRoboTMS lowers the barrier to entry and facilitates reproducible and extensible research in Robo-TMS. The extension is available at https://github.com/OpenRoboTMS/SlicerRoboTMS.

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 / 1 minor

Summary. The manuscript presents SlicerRoboTMS, an open-source 3D Slicer extension that supplies a unified interaction infrastructure for robot-assisted transcranial magnetic stimulation (Robo-TMS). It combines 3D Slicer's medical image computing and visualization for MRI-based neuronavigation with robotic control through standardized communication protocols and configurable system descriptions. An example integration is included to illustrate incorporation into a representative Robo-TMS workflow, with the stated goals of supporting diverse hardware configurations, enabling rapid prototyping, and facilitating reproducible research.

Significance. If the integration and abstraction layer function as described, SlicerRoboTMS could meaningfully lower barriers to Robo-TMS research by providing a shared, extensible platform built on the established 3D Slicer ecosystem. The open-source release and emphasis on configurability are explicit strengths that could support community contributions and hardware-agnostic experimentation in a field that otherwise requires substantial multidisciplinary integration effort.

major comments (2)
  1. [Abstract] Abstract: the claim that the extension 'supports diverse hardware configurations' and 'lowers the barrier to entry' through 'configurable system descriptions' and 'standardised communication protocols' is load-bearing for the central contribution, yet the manuscript supplies no quantitative evidence (e.g., coil positioning error, multi-robot compatibility tests, latency, or failure rates) or ablation of what the configuration files actually expose versus hard-coded assumptions.
  2. [Example Integration] Example Integration section: the described workflow integration is presented without any reported performance metrics, validation against ground-truth navigation, or tests under realistic MRI-guided conditions, leaving the asserted reliability and reproducibility benefits unverified.
minor comments (1)
  1. [Abstract] The GitHub link is useful; consider adding a permanent archive identifier (e.g., Zenodo DOI) to ensure long-term accessibility of the code.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive review and for identifying areas where the manuscript's claims require better alignment with the presented content. As this is a software tool paper focused on an open-source infrastructure, we will revise to clarify scope and design intent without adding unsubstantiated quantitative claims.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the claim that the extension 'supports diverse hardware configurations' and 'lowers the barrier to entry' through 'configurable system descriptions' and 'standardised communication protocols' is load-bearing for the central contribution, yet the manuscript supplies no quantitative evidence (e.g., coil positioning error, multi-robot compatibility tests, latency, or failure rates) or ablation of what the configuration files actually expose versus hard-coded assumptions.

    Authors: We agree that the abstract claims would benefit from stronger grounding in the manuscript content. The support for diverse hardware is realized through fully externalized configuration files that specify robot kinematics, communication endpoints, coordinate transformations, and coil models; no robot-specific logic is hard-coded in the extension core. This design is shown in the example integration, where swapping configuration files enables different robots without source changes. However, we did not include quantitative metrics because the work presents the infrastructure rather than a benchmarked system. In revision we will rephrase the abstract to describe these as design features that enable configurability, add an explicit statement that quantitative validation is hardware-dependent and outside the current scope, and include a short Discussion paragraph noting the absence of such metrics while pointing to the open-source release as the means for community-driven evaluation. revision: partial

  2. Referee: [Example Integration] Example Integration section: the described workflow integration is presented without any reported performance metrics, validation against ground-truth navigation, or tests under realistic MRI-guided conditions, leaving the asserted reliability and reproducibility benefits unverified.

    Authors: The Example Integration section is provided solely to illustrate how SlicerRoboTMS can be embedded in a typical Robo-TMS pipeline using 3D Slicer's existing navigation and the extension's robotic interfaces. It is not intended as a validation study. The reliability and reproducibility benefits are asserted on the basis of (1) reuse of 3D Slicer's established MRI-based navigation tools and (2) the use of standardized protocols that reduce ad-hoc integration code. We will revise the section and the surrounding text to state explicitly that the example is illustrative, that no performance or ground-truth data are reported, and that end-users should conduct application-specific accuracy and latency tests. A corresponding sentence will be added to the Conclusion. revision: partial

Circularity Check

0 steps flagged

No circularity: descriptive software tool paper with no derivations or predictions

full rationale

This manuscript is a tool description paper presenting an open-source 3D Slicer extension. It contains no equations, no fitted parameters, no predictions of new quantities, and no derivation chain. The abstract and structure focus on architecture, interfaces via standard protocols, configurable descriptions, and a single example integration. No self-citations are invoked as load-bearing premises for any result. The contribution is self-contained as a release of code and workflow support; claims about reproducibility rest on the open-source availability rather than any tautological reduction to inputs. This matches the default expectation of no circularity for non-theoretical papers.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is a software tool paper with no mathematical modeling, physical derivations, or new theoretical constructs; therefore no free parameters, axioms, or invented entities are present.

pith-pipeline@v0.9.0 · 5518 in / 1122 out tokens · 78008 ms · 2026-05-07T15:45:54.665140+00:00 · methodology

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Reference graph

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