Anatomic hepatectomy planning through mobile display visualization and interaction

Henrique Galvan Debarba; Jerônimo Grandi; Anderson MacIel; Dinamar Zanchet

doi:10.3233/978-1-61499-022-2-111

Anatomic hepatectomy planning through mobile display visualization and interaction

Henrique Galvan Debarba
, Jerônimo Grandi
, Anderson MacIel
, Dinamar Zanchet

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

Abstract

Hepatectomies are resections in which segments of the liver are extracted. While medical images are fundamental in the surgery planning procedure, the process of analysis of such images slice-by-slice is still tedious and inefficient. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D through a mobile display device. The method is based on volume visualization of standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.

Original language	English (US)
Title of host publication	Medicine Meets Virtual Reality 19
Subtitle of host publication	NextMed, MMVR 2012
Publisher	IOS Press
Pages	111-115
Number of pages	5
ISBN (Print)	9781614990215
DOIs	https://doi.org/10.3233/978-1-61499-022-2-111
State	Published - 2012
Externally published	Yes
Event	Medicine Meets Virtual Reality 19: NextMed, MMVR 2012 - Newport Beach, CA, United States Duration: Feb 9 2012 → Feb 11 2012

Publication series

Name	Studies in Health Technology and Informatics
Volume	173
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	Medicine Meets Virtual Reality 19: NextMed, MMVR 2012
Country/Territory	United States
City	Newport Beach, CA
Period	2/9/12 → 2/11/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Augmented reality
Human-computer interaction
Surgery planning

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics
Health Information Management

Access to Document

10.3233/978-1-61499-022-2-111

Cite this

Anatomic hepatectomy planning through mobile display visualization and interaction. / Debarba, Henrique Galvan; Grandi, Jerônimo; MacIel, Anderson et al.
Medicine Meets Virtual Reality 19: NextMed, MMVR 2012. IOS Press, 2012. p. 111-115 (Studies in Health Technology and Informatics; Vol. 173).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Debarba, HG, Grandi, J, MacIel, A & Zanchet, D 2012, Anatomic hepatectomy planning through mobile display visualization and interaction. in Medicine Meets Virtual Reality 19: NextMed, MMVR 2012. Studies in Health Technology and Informatics, vol. 173, IOS Press, pp. 111-115, Medicine Meets Virtual Reality 19: NextMed, MMVR 2012, Newport Beach, CA, United States, 2/9/12. https://doi.org/10.3233/978-1-61499-022-2-111

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abstract = "Hepatectomies are resections in which segments of the liver are extracted. While medical images are fundamental in the surgery planning procedure, the process of analysis of such images slice-by-slice is still tedious and inefficient. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D through a mobile display device. The method is based on volume visualization of standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.",

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AU - Debarba, Henrique Galvan

AU - Grandi, Jerônimo

AU - MacIel, Anderson

AU - Zanchet, Dinamar

PY - 2012

Y1 - 2012

N2 - Hepatectomies are resections in which segments of the liver are extracted. While medical images are fundamental in the surgery planning procedure, the process of analysis of such images slice-by-slice is still tedious and inefficient. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D through a mobile display device. The method is based on volume visualization of standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.

AB - Hepatectomies are resections in which segments of the liver are extracted. While medical images are fundamental in the surgery planning procedure, the process of analysis of such images slice-by-slice is still tedious and inefficient. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D through a mobile display device. The method is based on volume visualization of standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.

KW - Augmented reality

KW - Human-computer interaction

KW - Surgery planning

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UR - https://www.scopus.com/pages/publications/84860639968#tab=citedBy

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DO - 10.3233/978-1-61499-022-2-111

M3 - Conference contribution

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SN - 9781614990215

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BT - Medicine Meets Virtual Reality 19

PB - IOS Press

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ER -

Anatomic hepatectomy planning through mobile display visualization and interaction

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this