Evidence map›Paper›PMID 39775631›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

3d freehand ultrasound reconstruction by reference-based point cloud registration.

Christoph Großbröhmer, Lasse Hansen, Jürgen Lichtenstein, Ludger Tüshaus, Mattias P Heinrich

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Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Christoph GroßbröhmerInstitute of Medical Informatics, University of Lübeck, Lübeck, Germany.ORCID http://orcid.org/0000-0002-8926-8729
Lasse HansenEchoScout GmbH, Lübeck, Germany. lasse@echoscout.ai.ORCID http://orcid.org/0000-0003-3963-7052
Jürgen LichtensteinClinic of Oral and Maxillofacial Surgery, UKSH, Kiel, Germany.
Ludger TüshausClinic of Pediatric Surgery, UKSH, Lübeck, Germany.ORCID http://orcid.org/0000-0001-7997-6396
Mattias P HeinrichInstitute of Medical Informatics, University of Lübeck, Lübeck, Germany.ORCID http://orcid.org/0000-0002-7489-1972

Funding

Bundesministerium für Bildung und Forschung 13GW0578CWirtschaftsförderung und Technologietransfer Schleswig-Holstein 22023016
6 · The paper itself

Abstract

purposeThis study aims to address the challenging estimation of trajectories from freehand ultrasound examinations by means of registration of automatically generated surface points. Current approaches to inter-sweep point cloud registration can be improved by incorporating heatmap predictions, but practical challenges such as label-sparsity or only partially overlapping coverage of target structures arise when applying realistic examination conditions.

methodsWe propose a pipeline comprising three stages: (1) Utilizing a Free Point Transformer for coarse pre-registration, (2) Introducing HeatReg for further refinement using support point clouds, and (3) Employing instance optimization to enhance predicted displacements. Key techniques include expanding point sets with support points derived from prior knowledge and leverage of gradient keypoints. We evaluate our method on a large set of 42 forearm ultrasound sweeps with optical ground-truth tracking and investigate multiple ablations.

resultsThe proposed pipeline effectively registers free-hand intra-patient ultrasound sweeps. Combining Free Point Transformer with support-point enhanced HeatReg outperforms the FPT baseline by a mean directed surface distance of 0.96 mm (40%). Subsequent refinement using Adam instance optimization and DiVRoC further improves registration accuracy and trajectory estimation.

conclusionThe proposed techniques enable and improve the application of point cloud registration as a basis for freehand ultrasound reconstruction. Our results demonstrate significant theoretical and practical advantages of heatmap incorporation and multi-stage model predictions.

Indexed as

Imaging, Three-DimensionalAlgorithmsForearmHumansUltrasonographyPoint cloudReconstructionRegistrationUltrasound

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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.