Evidence map›Paper›PMID 31617057›Full record

ArticleInternational journal of computer assisted radiology and surgery2020

Automatic atlas-based liver segmental anatomy identification for hepatic surgical planning.

Omar Ibrahim Alirr, Ashrani Aizzuddin Abd Rahni

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Article in International journal of computer assisted radiology and surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation.IEEE journal of translational engineering in health and medicine · 2024
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Omar Ibrahim AlirrDepartment of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia. eng.omarizi@siswa.ukm.edu.my.ORCID http://orcid.org/0000-0002-4978-5350
Ashrani Aizzuddin Abd RahniDepartment of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, Malaysia.

Funding

ukm GUP-2014-066
6 · The paper itself

Abstract

purposeFor the liver to remain viable, the resection during hepatectomy procedure should proceed along the major vessels; hence, the resection planes of the anatomic segments are defined, which mark the peripheries of the self-contained segments inside the liver. Liver anatomic segments identification represents an essential step in the preoperative planning for liver surgical resection treatment.

methodThe method based on constructing atlases for the portal and the hepatic veins bifurcations, the atlas is used to localize the corresponding vein in each segmented vasculature using atlas matching. Point-based registration is used to deform the mesh of atlas to the vein branch. Three-dimensional distance map of the hepatic veins is constructed; the fast marching scheme is applied to extract the centerlines. The centerlines of the labeled major veins are extracted by defining the starting and the ending points of each labeled vein. Centerline is extracted by finding the shortest path between the two points. The extracted centerline is used to define the trajectories to plot the required planes between the anatomical segments.

resultsThe proposed approach is validated on the IRCAD database. Using visual inspection, the method succeeded to extract the major veins centerlines. Based on that, the anatomic segments are defined according to Couinaud segmental anatomy.

conclusionAutomatic liver segmental anatomy identification assists the surgeons for liver analysis in a robust and reproducible way. The anatomic segments with other liver structures construct a 3D visualization tool that is used by the surgeons to study clearly the liver anatomy and the extension of the cancer inside the liver.

Indexed as

Surgery, Computer-AssistedHepatectomyHepatic VeinsHumansLiverPortal VeinAbdominal CTAtlas-based identificationLiver segmental anatomySurgical planning

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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.