Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges: 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers

497 Pages·2019·79.749 MB·English

by  Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi

Mihaela Pop · Maxime Sermesant · Jichao Zhao
Shuo Li · Kristin McLeod · Alistair Young
Kawal Rhode · Tommaso Mansi (Eds.)
Statistical Atlases
and Computational Models
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9 of the Heart
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S Atrial Segmentation
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and LV Quantification Challenges
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9th International Workshop, STACOM 2018
Held in Conjunction with MICCAI 2018
Granada, Spain, September 16, 2018, Revised Selected Papers
123
Lecture Notes in Computer Science 11395
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Lancaster University, Lancaster, UK
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Carnegie Mellon University, Pittsburgh, PA, USA
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University of Surrey, Guildford, UK
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Cornell University, Ithaca, NY, USA
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ETH Zurich, Zurich, Switzerland
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Stanford University, Stanford, CA, USA
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Weizmann Institute of Science, Rehovot, Israel
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Indian Institute of Technology Madras, Chennai, India
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University of California, Los Angeles, CA, USA
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University of California, Berkeley, CA, USA
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Mihaela Pop Maxime Sermesant Jichao Zhao
(cid:129) (cid:129)
Shuo Li Kristin McLeod Alistair Young
(cid:129) (cid:129)
Kawal Rhode Tommaso Mansi (Eds.)
(cid:129)
Statistical Atlases
and Computational Models
of the Heart
Atrial Segmentation
fi
and LV Quanti cation Challenges
9th International Workshop, STACOM 2018
Held in Conjunction with MICCAI 2018
Granada, Spain, September 16, 2018
Revised Selected Papers
123
Editors
Mihaela Pop Kristin McLeod
University of Toronto GE Healthcare
Toronto, ON,Canada Oslo, Norway
Maxime Sermesant Alistair Young
Inria,Epione Group King’sCollege London
Sophia-Antipolis, France London,UK
Jichao Zhao Kawal Rhode
Auckland University King’sCollege London
Auckland,New Zealand London,UK
ShuoLi TommasoMansi
University of Western Ontario Siemens Medical Solutions USA, Inc.
London,ON, Canada Princeton, NJ, USA
ISSN 0302-9743 ISSN 1611-3349 (electronic)
Lecture Notesin Computer Science
ISBN 978-3-030-12028-3 ISBN978-3-030-12029-0 (eBook)
https://doi.org/10.1007/978-3-030-12029-0
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Preface
Integrative models of cardiac function are important for understanding disease, eval-
uating treatment, and planning intervention. In the recent years, there has been con-
siderable progress in cardiac image analysis techniques, cardiac atlases, and
computationalmodelsthatcanintegratedatafromlarge-scaledatabasesofheartshape,
function, and physiology. However, significant clinical translation of these tools is
constrained by the lack of complete and rigorous technical and clinical validation as
well as benchmarking of the developed tools. For doing so, common and available
ground-truth data capturing generic knowledge on the healthy and pathological heart
are required. Several efforts are now established to provide Web-accessible structural
and functional atlases of the normal and pathological heart for clinical, research, and
educational purposes. We believe that these approaches will only be effectively
developed through collaboration across the full research scope of the cardiac imaging
and modeling communities.
STACOM 2018 (http://stacom2018.cardiacatlas.org) was held in conjunction with
the MICCAI 2018 international conference (Granada, Spain, Canada), following the
past eight editions: STACOM 2010 (Beijing, China), STACOM 2011 (Toronto,
Canada),STACOM2012(Nice,France),STACOM2013(Nagoya,Japan),STACOM
2014 (Boston, USA), STACOM 2015 (Munich, Germany), STACOM 2016 (Athens,
Greece), and STACOM 2017 (Quebec City, Canada). STACOM 2018 provided a
forumtodiscussthelatestdevelopmentsinvariousareasofcomputationalimagingand
modelingoftheheart,aswellasstatisticalcardiacatlases.Thetopicsoftheworkshop
included: cardiac imaging and image processing, machine learning applied to cardiac
imagingandimageanalysis,atlasconstruction,statisticalmodellingofcardiacfunction
across different patient populations, cardiac computational physiology, model cus-
tomization, atlas-based functional analysis, ontological schemata for data and results,
integrated functional and structural analyses, as well as the pre-clinical and clinical
applicability of these methods.
Besides regular contributing papers, additional efforts of the STACOM 2018
workshopwerealsofocusedontwochallenges:the3DAtrialSegmentationChallenge
andtheLeftVentricleFullQuantificationChallenge,brieflydescribedbelow.Atotalof
51 papers (i.e., regular papers and from the two challenges) were accepted to be
presentedatSTACOM2018,andarepublishedbySpringerinthisLNCSproceedings
volume.
3D Atrial Segmentation Challenge
Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. The poor
performance of current AF treatment is due to a lack of understanding of the atrial
structure. Gadolinium-enhanced magnetic resonance imaging (i.e., late gadolinium
enhancement, LGE) is widely used to study the extent of fibrosis (scars) across the
atria.DirectsegmentationoftheatrialchambersfromLGEimagesisverychallenging.
Thereisanurgentneedforintelligentalgorithmsthatcanperformfullyautomaticatrial
VI Preface
segmentation for the atrial cavity, to accurately reconstruct and visualize the atrial
structure. This challenge has provided an open competition for wider communities to
test and validate their methods for image segmentation on a large 3D clinical dataset.
The exciting development is a very important step toward patient-specific diagnostics
and treatment of AF.
Thereadercanfindmoreinformationonthechallengewebsite:http://atriaseg2018.
cardiacatlas.org/.
Left Ventricle (LV) Full Quantification Challenge
Accurate cardiac left ventricle (LV) quantification is among the most clinically
important and most frequently demanded tasks for identification and diagnosis of
cardiac diseases and is of great interest in the research community of medical image
analysis. The LVQuan18 challenge:
(cid:129) Focused on full quantification of the LV (i.e., all clinical significant LV indices
regarding to the anatomical structure of LV were investigated in addition to the
frequently studied LV volume)
(cid:129) Provided a unified platform for participants around the world to develop effective
solutions for LV full quantification
(cid:129) BenchmarkedallsubmittedsolutionsforthetaskofLVquantificationandadvance
the state-of-art performance for computer-aided cardiac image quantification
The reader can find more information on the challenge website: https://lvquan18.
github.io/.
We hope that the results obtained by these two challenges, along with the regular
paper contributions, will act to accelerate progress in the important areas of heart
function and structure analysis.
We would like to thank all organizers, reviewers, authors, and sponsors for their
time, efforts, contributions, and financial support in making STACOM 2018 a suc-
cessful event.
September 2018 Mihaela Pop
Maxime Sermesant
Jichao Zhao
Shuo Li
Kristin McLeod
Alistair Young
Kawal Rhode
Tommaso Mansi
Organization
Chairs and Organizers
STACOM
Mihaela Pop Sunnybrook, University of Toronto, Canada
Maxime Sermesant Inria, Epione Group, France
Alistair Young University of Auckland, New Zealand
Kristin McLeod GE Healthcare, Norway
Kawal Rhode KCL, London, UK
Tommaso Mansi Siemens Healthineers, USA
3D Atrial Segmentation Challenge
Jichao Zhao University of Auckland, New Zealand
Zhaohan Xiong University of Auckland, New Zealand
LV Full Quantification Challenge
Shuo Li Digital Imaging Group, Western University, London,
Ontario, Canada
Wuefeng Xue Western University, London, Ontario, Canada
Additional Reviewers
Nicolas Cedilnik Matthew Ng
Florin Ghesu Tiziano Passerini
Akif Gulsun Saikiran Rapaka
Fumin Guo Avan Suinesiaputra
Florian Mihai Itu Wuegeng Xue
Shuman Jia Ingmar Voigt
Viorel Mihalef
OCS - Springer Conference Submission/Publication System
Mihaela Pop Medical Biophysics, University of Toronto,
Sunnybrook Research Institute, Toronto, Canada
Webmaster
Avan Suinesiaputra University of Auckland, New Zealand
Workshop Website
stacom2018.cardiacatlas.org
VIII Organization
Sponsors
We are extremely grateful for industrial funding support. The STACOM 2018
workshop and challenges received financial support from the following sponsors:
SysAfib (http://sysafib.org/)
Nvidia (http://nvidia.com)
MedTech coRE (https://www.cmdt.org.nz/medtechcore)
Arterys (http://arterys.com)
Contents
Regular Papers
Estimating Sheets in the Heart Wall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Tabish A. Syed, Babak Samari, and Kaleem Siddiqi
Automated Motion Correction and 3D Vessel Centerlines Reconstruction
from Non-simultaneous Angiographic Projections . . . . . . . . . . . . . . . . . . . . 12
Abhirup Banerjee, Rajesh K. Kharbanda, Robin P. Choudhury,
and Vicente Grau
Left Ventricle Segmentation and Quantification from Cardiac Cine MR
Images via Multi-task Learning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Shusil Dangi, Ziv Yaniv, and Cristian A. Linte
Statistical Shape Clustering of Left Atrial Appendages. . . . . . . . . . . . . . . . . 32
Jakob M. Slipsager, Kristine A. Juhl, Per E. Sigvardsen,
Klaus F. Kofoed, Ole De Backer, Andy L. Olivares, Oscar Camara,
and Rasmus R. Paulsen
Deep Learning Segmentation of the Left Ventricle in Structural CMR:
Towards a Fully Automatic Multi-scan Analysis. . . . . . . . . . . . . . . . . . . . . 40
Hakim Fadil, John J. Totman, and Stephanie Marchesseau
Cine and Multicontrast Late Enhanced MRI Registration
for 3D Heart Model Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Fumin Guo, Mengyuan Li, Matthew Ng, Graham Wright,
and Mihaela Pop
Joint Analysis of Personalized In-Silico Haemodynamics and Shape
Descriptors of the Left Atrial Appendage. . . . . . . . . . . . . . . . . . . . . . . . . . 58
Jordi Mill, Andy L. Olivares, Etelvino Silva, Ibai Genua,
Alvaro Fernandez, Ainhoa Aguado, Marta Nuñez-Garcia,
Tom de Potter, Xavier Freixa, and Oscar Camara
How Accurately Does Transesophageal Echocardiography Identify
the Mitral Valve? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Claire Vannelli, Wenyao Xia, John Moore, and Terry Peters
Stochastic Model-Based Left Ventricle Segmentation in 3D
Echocardiography Using Fractional Brownian Motion . . . . . . . . . . . . . . . . . 77
Omar S. Al-Kadi, Allen Lu, Albert J. Sinusas, and James S. Duncan