Evidence map›Paper›PMID 40687495›Full record

ArticleJournal of medical robotics research

Cross-Modality Registration using Bone Surface Pointcloud for Robotic Ultrasound-Guided Spine Surgery.

Xihan Ma, Xiao Zhang, Yang Wang, Christopher J Nycz, Arno Sungarian, Songbai Ji, Xinming Huang, Haichong K Zhang

Abstract read
In one paragraph

Article in Journal of medical robotics research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. A comprehensive framework for planning pedicle screw trajectory using ANTs template-based registration approach.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xihan MaDepartment of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd., Worcester, MA 01609, USA.ORCID 0000-0003-1007-0910
Xiao ZhangDepartment of Electrical and Computer Engineering, Worcester Polytechnic Institute 100 Institute Rd., Worcester, MA 01609, USA.ORCID 0000-0001-6165-5527
Yang WangDepartment of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd., Worcester, MA 01609, USA.ORCID 0000-0003-2345-4729
Christopher J NyczDepartment of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd., Worcester, MA 01609, USA.ORCID 0000-0002-3753-786X
Arno SungarianMemorial Medical Center, University of Massachusetts, 55 N Lake Ave., Worcester, MA 01655, USA.ORCID 0009-0006-1954-7526
Songbai JiDepartment of Biomedical Engineering, Worcester Polytechnic Institute, 100 Institute Rd., Worcester, MA 01609, USA.ORCID 0000-0002-2886-5781
Xinming HuangDepartment of Electrical and Computer Engineering, Worcester Polytechnic Institute 100 Institute Rd., Worcester, MA 01609, USA.ORCID 0000-0003-0584-3448
Haichong K ZhangDepartment of Robotics Engineering, Worcester Polytechnic Institute, 100 Institute Rd., Worcester, MA 01609, USA.ORCID 0000-0002-1314-8456

Funding

PSMA-based Cancer Imaging AgentsR01CA134675 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI POMPER, MARTIN G · 2009 to 2025
$6.2M
Physician Assistance Technology in Image-guided Robotic Intervention of ProstateR01EB030539 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI HATA, NOBUHIKO, ZHANG, HAICHONG · 2021 to 2024
$2.7M
Automatic Wide-Field Optical Coherence Tomography for Assessment of Transplant Kidney ViabilityR01DK133717 · NIDDK · UNIVERSITY OF MASSACHUSETTS AMHERST · PI POTTER, STEVEN, TANG, QINGGONG · 2022 to 2025
$2.5M
Robotic Lung Ultrasound for Triage of COVID-19 Patients in a Resource-Limited EnvironmentDP5OD028162 · OD · WORCESTER POLYTECHNIC INSTITUTE · PI ZHANG, HAICHONG · 2019 to 2023
$2.3M
NCI NIH HHS R01 CA134675NIBIB NIH HHS R01 EB030539NIDDK NIH HHS R01 DK133717NIH HHS DP5 OD028162
6 · The paper itself

Abstract

Image guidance using preoperative magnetic resonance imaging (MRI) and intraoperative ultrasound (US) can improve the outcome of spine surgery. Employing a robotic US system (RUSS) allows the automated acquisition of large 3D US volumes, facilitating accurate registration. However, such registration remains challenging due to the cross-modality discrepancy. To address this issue, we present a pipeline that extracts spine pointclouds from MRI and 3D US to perform per-vertebra registration. Experiments showed a registration accuracy of 1.82 mm in terms of residual root mean square error and 7.02 mm in terms of Chamfer distance. The pipeline exhibits superior robustness to suboptimal initial conditions compared with the two baseline methods. It also demonstrated good time efficiency under real-time conditions, demonstrating the potential applicability in RUSS-guided spine surgeries.

Indexed as

cross-modality registrationimage-guided interventionrobotic ultrasoundSpine surgeryultrasound

Identifiers

PMID40687495
PMCPMC12273864

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.