Table Of ContentAhmed Abdulkadir · Seyed Mostafa Kia ·
Mohamad Habes · Vinod Kumar ·
Jane Maryam Rondina · Chantal Tax ·
Thomas Wolfers (Eds.)
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4th International Workshop, MLCN 2021
Held in Conjunction with MICCAI 2021
Strasbourg, France, September 27, 2021, Proceedings
Lecture Notes in Computer Science 13001
FoundingEditors
GerhardGoos
KarlsruheInstituteofTechnology,Karlsruhe,Germany
JurisHartmanis
CornellUniversity,Ithaca,NY,USA
EditorialBoardMembers
ElisaBertino
PurdueUniversity,WestLafayette,IN,USA
WenGao
PekingUniversity,Beijing,China
BernhardSteffen
TUDortmundUniversity,Dortmund,Germany
GerhardWoeginger
RWTHAachen,Aachen,Germany
MotiYung
ColumbiaUniversity,NewYork,NY,USA
Moreinformationaboutthissubseriesathttp://www.springer.com/series/7412
· ·
Ahmed Abdulkadir Seyed Mostafa Kia
· ·
Mohamad Habes Vinod Kumar
· ·
Jane Maryam Rondina Chantal Tax
Thomas Wolfers (Eds.)
Machine Learning in
Clinical Neuroimaging
4th International Workshop, MLCN 2021
Held in Conjunction with MICCAI 2021
Strasbourg, France, September 27, 2021
Proceedings
Editors
AhmedAbdulkadir SeyedMostafaKia
UniversityofPennsylvania DondersInstitute
Philadelphia,PA,USA Nijmegen,TheNetherlands
MohamadHabes VinodKumar
TheUniversityofTexasHealthScience MaxPlanckInstituteforBiological
CenteratSanAntonio Cybernetics
SanAntonio,TX,USA Tübingen,Germany
JaneMaryamRondina ChantalTax
UniversityCollegeLondon UniversityMedicalCenterUtrecht
London,UK Utrecht,TheNetherlands
CardiffUniversityBrainResearchImaging
ThomasWolfers
Centre(CUBRIC)
UniversityofOslo
Cardiff,UK
Oslo,Norway
ISSN 0302-9743 ISSN 1611-3349 (electronic)
LectureNotesinComputerScience
ISBN 978-3-030-87585-5 ISBN 978-3-030-87586-2 (eBook)
https://doi.org/10.1007/978-3-030-87586-2
LNCSSublibrary:SL6–ImageProcessing,ComputerVision,PatternRecognition,andGraphics
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Preface
Methodological developments in neuroimaging analysis contribute to the progress in
clinical neurosciences. In specific domains of academic image analysis, impressive
stridesweremadethankstomodernmachinelearninganddataanalysismethodssuchas
deepartificialneuralnetworks.Theinitialsuccessinacademicapplicationsofcomplex
neuralnetworksstartedawaveofstudiesthroughtheneuroimagingresearchfield.Deep
learningisnowcomplementingmoretraditionalmachinelearningasatoolforimage
anddataanalysis.Itisourviewthatincorporatinginterdisciplinarydomainknowledge
into the machine learning models is critical to answer challenging clinically relevant
researchquestionsinthefieldofclinicalneurosciencethateventuallywilltranslateto
clinicalroutine.Withthisworkshop,weaimedatcreatinganintellectualplayingfield
forcliniciansandmachinelearningexpertsaliketoshareanddiscussknowledgeatthe
interfacebetweenmachinelearningandclinicalapplication.
The 4th International Workshop on Machine Learning in Clinical Neuroimaging
(MLCN 2021) was held as a satellite event of the 24th International Conference on
Medical Imaging Computing and Computer-Assisted Intervention (MICCAI 2021) to
fosterascientificdialogbetweenexpertsinmachinelearningandclinicalneuroimaging.
ThecallforpaperswaspublishedonApril30,2021,andthesubmissionwindowclosed
on July 5, 2021. Each submitted manuscript was reviewed by three members of the
ProgramCommitteeinadouble-blinddreviewprocess.Theacceptedmanuscriptscon-
tainedinthisproceedingspresentedamethodologicallysound,novel,andthematically
fitting contribution to the field of clinical neuroimaging, and were presented and dis-
cussedbytheauthorsatthevirtualMLCNworkshop.Thecontributionsstudiedinvivo
structural and functional magnetic resonance imaging data. Several accepted submis-
sionswereconcernedwithcomputationalanatomyinvolvingawiderangeofmethods
includingsupervisedimagesegmentation,registration,classification,anomalydetection,
andgenerativemodeling.Networkanalysisandtimeserieswereothertopicalbranches
oftheworkshopcontributionsinwhichawidevarietyofmethodswereemployedand
developed including dictionary learning, graph neural networks, and space-time con-
volutionalneuralnetworks.Thefieldsofapplicationswereasdiverseasthemethods.
Theyincludeddetectionandmodelingofabnormalcorticalfoldingpatternsandsimu-
lationofbrainatrophy,mappinghistologytoexvivoimaging,mappingfunctionalcor-
ticalregions,andmappingstructuralwithfunctionalconnectivitygraphs.Themethod-
ological developments pushed the boundaries of clinical neuroscience image analysis
withfastalgorithmsforcomplexandaccuratedescriptorsofstructure,function,orthe
combinationofmultiplemodalities.
vi Preface
This workshop was made possible by a devoted community of authors, Program
Committee,SteeringCommittee,andworkshopparticipants.Wethankallcreatorsand
attendeesfortheirvaluablecontributions.
September2021 AhmedAbdulkadir
MohamadHabes
SeyedMostafaKia
VinodKumar
JaneMaryamRondina
ChantalTax
ThomasWolfers
Organization
SteeringCommittee
ChristosDavatzikos UniversityofPennsylvania,USA
AndreMarquand DondersInstitute,TheNetherlands
JonasRichiardi LausanneUniversityHospital,Switzerland
EmmaRobinson King’sCollegeLondon,UK
OrganizingCommittee
AhmedAbdulkadir UniversityofPennsylvania,USA
MohamadHabes UniversityofTexasHealthScienceCenteratSanAntonio,
USA
SeyedMostafaKia UniversityMedicalCenterUtrecht,TheNetherlands
VinodKumar MaxPlanckInstituteforBiologicalCybernetics,Germany
JaneMaryamRondina UniversityCollegeLondon,UK
ChantalTax UniversityMedicalCenterUtrecht,TheNetherlands
ThomasWolfers NORMENT,Norway
ProgramCommittee
MohammedAl-Masni YonseiUniversity,SouthKorea
AndreAltman UniversityCollegeLondon,UK
PierreBerthet UniversityofOslo,Norway
ÖzgünÇiçek UniversityofFreiburg,Germany
RichardDinga DondersInstitute,TheNetherlands
CharlotteFraza DondersInstitute,TheNetherlands
PouyaGhaemmaghami ConcordiaUniversity,Canada
FrancescoLaRosa EcolePolytechniqueFédéraledeLausanne,Switzerland
SarahLee AmallisConsulting,UK
HangfanLiu UniversityofPennsylvania,USA
EmanueleOlivetti FondazioneBrunoKessler,Italy
PradeepReddyRaamana UniversityofToronto,Canada
SaigeRutherford UniversityofMichigan,USA
HugoSchnack UniversityMedicalCenterUtrecht,TheNetherlands
HaochangShou UniversityofPennsylvania,USA
HaykelSnoussi UniversityofTexasHealthScienceCenteratSanAntonio,
USA
SourenaSoheiliNezhad RadboudUniversityMedicalCenter,TheNetherlands
RashidTanweer UniversityofPennsylvania,USA
PetteriTeikari UniversityCollegeLondon,UK
viii Organization
ErdemVarol ColumbiaUniversity,USA
MatthiasWilms UniversityofCalgary,Canada
TianboXu UniversityCollegeLondon,UK
MariamZabihi RadboudUniversityMedicalCenter,TheNetherlands
Contents
ComputationalAnatomy
Unfolding the Medial Temporal Lobe Cortex to Characterize
Neurodegeneration Due to Alzheimer’s Disease Pathology Using
ExvivoImaging ....................................................... 3
SadhanaRavikumar, LauraWisse, SydneyLim,
DavidIrwin, RanjitIttyerah, LongXie, SandhitsuR.Das,
EdwardLee, M.DylanTisdall, KarthikPrabhakaran,
JohnDetre, GaborMizsei, JohnQ.Trojanowski,
JohnRobinson, TheresaSchuck, MurrayGrossman,
EmilioArtacho-Pérula,MariaMercedesIñiguezdeOnzoñoMartin,
MaríadelMarArroyoJiménez, MonicaMuñoz,
FranciscoJavierMolinaRomero, MariadelPilarMarcosRabal,
SandraCebadaSánchez, JoséCarlosDelgadoGonzález,
CarlosdelaRosaPrieto, MartaCórcolesParada, DavidWolk,
RicardoInsausti,andPaulYushkevich
Distinguishing Healthy Ageing from Dementia: A Biomechanical
SimulationofBrainAtrophyUsingDeepNetworks ........................ 13
MarianaDaSilva, CaroleH.Sudre, KaraGarcia, CherBass,
M.JorgeCardoso,andEmmaC.Robinson
TowardsSelf-explainableClassifiersandRegressorsinNeuroimaging
withNormalizingFlows ................................................ 23
MatthiasWilms, PaulineMouches, JordanJ.Bannister,
DeepthiRajashekar,SönkeLangner,andNilsD.Forkert
Patchvs.GlobalImage-BasedUnsupervisedAnomalyDetectioninMR
BrainScansofEarlyParkinsonianPatients ................................ 34
VerónicaMuñoz-Ramírez, NicolasPinon, FlorenceForbes,
CaroleLartizen,andMichelDojat
MRIImageRegistrationConsiderablyImprovesCNN-BasedDisease
Classification ......................................................... 44
MalteKlingenberg, DidemStark, FabianEitel, and KerstinRitter
fortheAlzheimer’sDiseaseNeuroimagingInitiative
Dynamic Sub-graph Learning for Patch-Based Cortical Folding
Classification ......................................................... 53
ZhiweiDeng,JiongZhang,YonggangShi,andtheHealthandAging
BrainStudy(HABS-HD)StudyTeam
