Evidence map›Paper›PMID 38767767›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

Normscan: open-source Python software to create average models from CT scans.

George R Nahass, Mitchell A Marques, Naji Bou Zeid, Linping Zhao, Lee W T Alkureishi

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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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2 · The registry

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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.

George R NahassDivision of Plastic, Reconstructive, and Cosmetic Surgery, The Craniofacial Center, University of Illinois at Chicago, 811 S Paulina St., Chicago, IL, 60612, USA.
Mitchell A MarquesDivision of Plastic, Reconstructive, and Cosmetic Surgery, The Craniofacial Center, University of Illinois at Chicago, 811 S Paulina St., Chicago, IL, 60612, USA.
Naji Bou ZeidDivision of Plastic, Reconstructive, and Cosmetic Surgery, The Craniofacial Center, University of Illinois at Chicago, 811 S Paulina St., Chicago, IL, 60612, USA.
Linping ZhaoDivision of Plastic, Reconstructive, and Cosmetic Surgery, The Craniofacial Center, University of Illinois at Chicago, 811 S Paulina St., Chicago, IL, 60612, USA.
Lee W T AlkureishiDivision of Plastic, Reconstructive, and Cosmetic Surgery, The Craniofacial Center, University of Illinois at Chicago, 811 S Paulina St., Chicago, IL, 60612, USA. lalk@uic.edu.ORCID http://orcid.org/0000-0002-5661-2466

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAge-matched average 3D models facilitate both surgical planning and intraoperative guidance of cranial birth defects such as craniosynostosis. We aimed to develop an algorithm that accepts any number of CT scans as input and generates highly accurate, average models with minimal user input that are ready for 3D printing and clinical use.

methodsUsing a compiled database of 'normal' pediatric computed tomography (CT) scans, we report Normscan, an open-source platform built in Python that allows users to generate normative models of CT scans through user-defined landmarks. We use the basion, nasion, and left and right porions as anatomical landmarks for initial correspondence and then register the models using the iterative closest points algorithm before downstream averaging.

resultsNormscan is fast and easy to use via our user interface and also creates highly accurate average models of any number of input models. Additionally, it is highly repeatable, with coefficients of variance for the surface area and volume of the average model being less than 3% across ten independent trials. Average models can then be 3D printed and/or visualized in augmented reality.

conclusionsNormscan provides an end-to-end pipeline for the creation of average models of skulls. These models can be used for the generation of databases of specific demographic anatomical models as well as for intraoperative guidance and surgical planning. While Normscan was designed for craniosynostosis repair, due to the modular nature of the algorithm, Normscan has many applications in other areas of surgical planning and research.

Indexed as

CraniosynostosesImaging, Three-DimensionalModels, AnatomicPrinting, Three-DimensionalSkullSoftwareTomography, X-Ray ComputedAlgorithmsHumansInfantAverage model generationCraniosynostosisNeurosurgeryPlastic surgeryPythonSurgical planning

Identifiers

PMID38767767

What OpenQuestion holds

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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.