A robust multi-variability model based liver segmentation algorithm for CT-scan and MRI modalities

Lebre, Marie-Ange (author): Univ Clermont Auvergne, CHU Clermont Ferrand, CNRS, SIGMA Clermont,Inst Pascal, F-63000 Clermont Ferrand, France

Vacavant, Antoine (author): Univ Clermont Auvergne, CHU Clermont Ferrand, CNRS, SIGMA Clermont,Inst Pascal, F-63000 Clermont Ferrand, France

Grand-Brochier, Manuel (author): Univ Clermont Auvergne, CHU Clermont Ferrand, CNRS, SIGMA Clermont,Inst Pascal, F-63000 Clermont Ferrand, France

Rositi, Hugo (author): Univ Clermont Auvergne, CHU Clermont Ferrand, CNRS, SIGMA Clermont,Inst Pascal, F-63000 Clermont Ferrand, France

Strand, Robin, 1978- (author): Uppsala universitet,Bildanalys och människa-datorinteraktion

Abergel, Armand (author): Univ Clermont Auvergne, CHU Clermont Ferrand, CNRS, SIGMA Clermont,Inst Pascal, F-63000 Clermont Ferrand, France

Chabrot, Pascal (author): Univ Clermont Auvergne, CHU Clermont Ferrand, CNRS, SIGMA Clermont,Inst Pascal, F-63000 Clermont Ferrand, France

Magnin, Benoit (author): Univ Clermont Auvergne, CHU Clermont Ferrand, CNRS, SIGMA Clermont,Inst Pascal, F-63000 Clermont Ferrand, France

(creator_code:org_t)

PERGAMON-ELSEVIER SCIENCE LTD, 2019
2019
English.
In: Computerized Medical Imaging and Graphics. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0895-6111 .- 1879-0771. ; 76

Related links:: https://www.scienced...; show more...; https://urn.kb.se/re...; https://doi.org/10.1...; show less...

Abstract Subject headings

Developing methods to segment the liver in medical images, study and analyze it remains a significant challenge. The shape of the liver can vary considerably from one patient to another, and adjacent organs are visualized in medical images with similar intensities, making the boundaries of the liver ambiguous. Consequently, automatic or semi-automatic segmentation of liver is a difficult task. Moreover, scanning systems and magnetic resonance imaging have different settings and parameters. Thus the images obtained differ from one machine to another. In this article, we propose an automatic model-based segmentation that allows building a faithful 3-D representation of the liver, with a mean Dice value equal to 90.3% on CT and MRI datasets. We compare our algorithm with a semi-automatic method and with other approaches according to the state of the art. Our method works with different data sources, we use a large quantity of CT and MRI images from machines in various hospitals and multiple DICOM images available from public challenges. Finally, for evaluation of liver segmentation approaches in state of the art, robustness is not adequacy addressed with a precise definition. Another originality of this article is the introduction of a novel measure of robustness, which takes into account the liver variability at different scales. (C) 2019 Published by Elsevier Ltd.

MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)

By the author/editor: Lebre, Marie-Ang ...; Vacavant, Antoin ...; Grand-Brochier, ...; Rositi, Hugo; Strand, Robin, 1 ...; Rosier, Hubert; show more...; Abergel, Armand; Chabrot, Pascal; Magnin, Benoit; show less...

About the subject

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Radiology Nuclea ...

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Medical Engineer ...; and Medical Image Pr ...

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.