Computational Diffusion MRI: 13th International Workshop, CDMRI 2022 Held in Conjunction with MICCAI 2022 Singapore, Singapore, September 22, 2022 Proceedings

156 Pages·2022·37.602 MB·English

by  Suheyla Cetin-Karayumak, Daan Christiaens, Matteo Figini, Pamela Guevara, Tomasz Pieciak, Elizabeth Powell, Francois Rheault

Suheyla Cetin-Karayumak ·
Daan Christiaens · Matteo Figini ·
Pamela Guevara · Tomasz Pieciak ·
Elizabeth Powell · Francois Rheault (Eds.)
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Diffusion MRI
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13th International Workshop, CDMRI 2022
Held in Conjunction with MICCAI 2022
Singapore, Singapore, September 22, 2022, Proceedings
Lecture Notes in Computer Science 13722
FoundingEditors
GerhardGoos
KarlsruheInstituteofTechnology,Karlsruhe,Germany
JurisHartmanis
CornellUniversity,Ithaca,NY,USA
EditorialBoardMembers
ElisaBertino
PurdueUniversity,WestLafayette,IN,USA
WenGao
PekingUniversity,Beijing,China
BernhardSteffen
TUDortmundUniversity,Dortmund,Germany
MotiYung
ColumbiaUniversity,NewYork,NY,USA
Moreinformationaboutthisseriesathttps://link.springer.com/bookseries/558
· ·
Suheyla Cetin-Karayumak Daan Christiaens
· ·
Matteo Figini Pamela Guevara
· ·
Tomasz Pieciak Elizabeth Powell
Francois Rheault (Eds.)
Computational
Diffusion MRI
13th International Workshop, CDMRI 2022
Held in Conjunction with MICCAI 2022
Singapore, Singapore, September 22, 2022
Proceedings
Editors
SuheylaCetin-Karayumak DaanChristiaens
HarvardMedicalSchool KULeuven
Boston,MA,USA Leuven,Belgium
MatteoFigini PamelaGuevara
UniversityCollegeLondon UniversidaddeConcepción
London,UK Concepción,Chile
TomaszPieciak ElizabethPowell
UniversidaddeValladolid UniversityCollegeLondon
Valladolid,Spain London,UK
FrancoisRheault
UniversitédeSherbrooke
Sherbrooke,QC,Canada
ISSN 0302-9743 ISSN 1611-3349 (electronic)
LectureNotesinComputerScience
ISBN 978-3-031-21205-5 ISBN 978-3-031-21206-2 (eBook)
https://doi.org/10.1007/978-3-031-21206-2
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Preface
Itisourprivilegetointroducetheproceedingsofthisyear’sInternationalWorkshopon
ComputationalDiffusionMRI(CDMRI2022).Sinceitsconceptionovertenyearsago,
CDMRIhasbeenorganizedeachyearasasatelliteeventoftheMedicalImageCom-
puting and Computer Assisted Intervention (MICCAI) conference, bringing together
researchers from across the globe to discuss the latest advances in the acquisition,
analysis,andapplicationofdiffusionMRI(dMRI).
DiffusionMRIhastransformedourabilitytonon-invasivelyprobetissuemicrostruc-
tureandfunctionoverthelastfourdecades,withapplicationsrangingfromthemapping
ofneuralpathwaystoassistingwithtumorclassificationtoaidingneurosurgicalplan-
ningandbeyond.However,tocontinueprogressioninthisfieldandaccessevenmore
complex microstructural features, richer and more sophisticated acquisition protocols
arerequiredthatmaynotbefeasibleinclinicalsettings.Inrecentyears,machinelearn-
ingtechniqueshavebeguntoofferthepossibilityofachievingequivalentinformation
fromsmaller,moreclinicallyfeasibledatasets,andassucharebecomingincreasingly
prevalent in the dMRI literature. The submissions to CDMRI 2022 are reflective of
this trend: over 80% of the proffered papers proposed machine learning strategies to
improve either dMRI image processing or data storage. These numbers also highlight
thesynergywiththemachine-learning-orientedMICCAIcommunity.Readersofthese
proceedings can expect to find contributions on topics such as susceptibility distor-
tioncorrectionusingsemi-superviseddeeplearning,microstructuralmodelfittingusing
self-supervisedlearning,anddatacompressionusingneuralnetworks.
However, post-hoc data augmentation techniques are not infallible. This year, the
CDMRI workshop hosted the MICCAI challenge entitled ‘Quality Augmentation in
Diffusion MRI for Clinical Studies: Validation in Migraine’ (QuaD22), which asked
the pertinent question ‘Are we losing relevant quantitative clinical information when
generating high-quality images with artificial intelligence techniques?’ The QuaD22
organizers tasked participants with generating DTI-related parameters from a dMRI
migraine dataset acquired with 21 diffusion gradient directions that were of a similar
high-quality to parameters obtained from a dataset with 61 gradient directions, with
theaimofevaluatingwhetheritwaspossibletodetectthesamesignificantdifferences
between episodic migraine and chronic migraine patients in the reduced acquisition
scenarioasinthefully-sampledsituation.
ThisworkshopwouldnothavebeenpossiblewithoutthededicationoftheProgram
Committee (listed below), who, through a double-blind peer review process, ensured
thehigheststandardwasachieved.Ofthe13submissionsreceived,fourwereaccepted
withoutrevision,eightwereacceptedafterrevision,andonewasrejected;eachsubmis-
sionwasreviewedbyatleasttwomembersoftheProgramCommittee.Weextendour
vi Preface
gratitudetoeveryoneinvolvedintheProgramCommittee.Finally,wewishtothankour
keynotespeakers(listedbelow),whodeliveredaseriesoftrulyenlighteninglectures.
September2022 SuheylaCetin-Karayumak
DaanChristiaens
MatteoFigini
PamelaGuevara
TomaszPieciak
ElizabethPowell
FrancoisRheault
Organization
ProgramCommitteeChairs
SuheylaCetin-Karayumak HarvardMedicalSchool,USA
DaanChristiaens KULeuven,Belgium
MatteoFigini UniversityCollegeLondon,UK
PamelaGuevara UniversidaddeConcepción,Chile
TomaszPieciak UniversidaddeValladolid,Spain
ElizabethPowell UniversityCollegeLondon,UK
FrancoisRheault UniversitédeSherbrooke,Canada
ProgramCommittee
NageshAdluru UniversityofWisconsin–Madison,USA
MaryamAfzali CardiffUniversity,UK
SuyashP.Awate IndianInstituteofTechnology(IIT)Bombay,
India
DoguBaranAydogan AaltoUniversity,Finland
YaëlBalbastre MassachusettsGeneralHospital,USA
PietroBontempi UniversityofVerona,Italy
RyanP.Cabeen UniversityofSouthernCalifornia,USA
MaximeChamberland DondersInstituteforBrain,Cognitionand
Behaviour,TheNetherlands
AlessandroDaducci UniversityofVerona,Italy
GabrielGirard EPFL,Switzerland
TingGong UniversityCollegeLondon,UK
MugeKaraman UniversityofIllinoisatChicago,USA
EmmaMuñoz-Moreno IDIBAPS,Spain
MarcoPalombo CardiffUniversity,UK
MarcoPizzolato TechnicalUniversityofDenmark,Denmark
AlonsoRamirez-Manzanares CIMATA.C.,Mexico
SimonaSchiavi UniversityofGenoa,Italy
ThomasSchultz UniversityofBonn,Germany
JelleVeraart NYUSchoolofMedicine,USA
YeWu UniversityofNorthCarolinaatChapelHill,USA
Pew-ThianYap UniversityofNorthCarolinaatChapelHill,USA
FanZhang HarvardMedicalSchool,USA
viii Organization
KeynoteSpeakers
SuyashP.Awate IndianInstituteofTechnology(IIT),Bombay,
India
AmyHoward UniversityofOxford,UK
SusieY.Huang MartinosCenterforBiomedicalImaging,USA
EvrenÖzarslan LinköpingUniversity,Sweden
AndrewZalesky UniversityofMelbourne,Australia
Contents
DataPreprocessing
SliceEstimationinDiffusionMRIofNeonatalandFetalBrainsinImage
andSphericalHarmonicsDomainsUsingAutoencoders .................... 3
HamzaKebiri, GabrielGirard, YasserAlemán-Gómez,
ThomasYu, AndrásJakab, ErickJorgeCanales-Rodríguez,
andMeritxellBachCuadra
Super-Resolution of Manifold-Valued Diffusion MRI Refined
byMulti-modalImaging ................................................ 14
TylerA.SpearsandP.ThomasFletcher
Lossy Compression of Multidimensional Medical Images Using
SinusoidalActivationNetworks:AnEvaluationStudy ...................... 26
MatteoMancini,DerekK.Jones,andMarcoPalombo
Correction of Susceptibility Distortion in EPI: A Semi-supervised
ApproachwithDeepLearning ........................................... 38
AntoineLegouhy, MarkGraham, MicheleGuerreri, WhitneyStee,
ThomasVillemonteix,PhilippePeigneux,andHuiZhang
TheImpactofSusceptibilityDistortionCorrectionProtocolsonAdolescent
DiffusionMRIMeasures ............................................... 50
TaliaM.Nir, JulioE.Villalón-Reina, PaulM.Thompson,
andNedaJahanshad
SignalRepresentations
DiffusionMRIFibreOrientationDistributionInpainting .................... 65
ZihaoTang, XinyiWang, MarianoCabezas, ArkievD’Souza,
FernandoCalamante,DongnanLiu,MichaelBarnett,ChenyuWang,
andWeidongCai
FittingaDirectionalMicrostructureModeltoDiffusion-RelaxationMRI
DatawithSelf-supervisedMachineLearning .............................. 77
JasonP.Lim,StefanoB.Blumberg,NeilNarayan,SeanC.Epstein,
DanielC.Alexander,MarcoPalombo,andPaddyJ.Slator