Rapid patient-specific neural networks for intraoperative X-ray to volume registration.

Vivek Gopalakrishnan, Neel Dey, David-Dimitris Chlorogiannis, Andrew Abumoussa, Anna M Larson, Darren B Orbach, Sarah Frisken, Polina Golland

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In one paragraph

Article in ArXiv, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

Updated by
Rapid patient-specific neural networks for X-ray to volume registration.2026

5 · Who and what money

Authors and funding

8 authors.

Vivek GopalakrishnanHarvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.

Neel DeyComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.

David-Dimitris ChlorogiannisDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Andrew AbumoussaDepartment of Neurosurgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA.

Anna M LarsonDepartment of Interventional Neuroradiology, Boston Children's Hospital, Boston, MA, USA.

Darren B OrbachDepartment of Interventional Neuroradiology, Boston Children's Hospital, Boston, MA, USA.

Sarah FriskenDepartment of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Polina GollandHarvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.

Funding

Neuroimaging Training ProgramT32EB001680 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BRUCE R ROSEN · 2003 to 2026

$3.8M

NIBIB NIH HHS T32 EB001680

6 · The paper itself

Abstract

The integration of artificial intelligence in image-guided interventions holds transformative potential, promising to extract 3D geometric and quantitative information from conventional 2D imaging modalities during complex procedures. Achieving this requires the rapid and precise alignment of 2D intraoperative images (

Identifiers

PMID40166742

PMCPMC11957231

What OpenQuestion holds

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Registered trials

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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.