Table Of ContentAdvances in Computerized
Analysis in Clinical and
Medical Imaging
Advances in Computerized
Analysis in Clinical and
Medical Imaging
Edited by
J. Dinesh Peter
Steven Lawrence Fernandes
Carlos Eduardo Thomaz
CRCPress
Taylor&FrancisGroup
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Contents
Preface .................................................................... vii
AbouttheEditors............................................................ix
Contributors ................................................................xi
1. ANewBiomarkerforAlzheimer’sBasedontheHippocampusImage
ThroughtheEvaluationoftheSurfaceChargeDistribution ................... 1
AldoA.Belardi,FernandhodeO.Freitas,RodrigoP.Bechelli,and
RodrigoG.G.Piva
2. IndependentVectorAnalysisofNon-NegativeImageMixtureModel
forClinicalImageSeparation............................................. 17
D.Sugumar,P.T.Vanathi,Xiao-ZhiGao,FelixErdmannOtt,and
M.S.AezhisaiVallavi
3. RationalizingofMorphologicalRenalParametersandeGFRforChronic
KidneyDiseaseDetection................................................ 41
DeepthyMaryAlex,D.AbrahamChandy,andAnandPaul
4. HumanComputerInterfaceforNeurodegenerativePatientsUsing
MachineLearningAlgorithms............................................ 51
S.Ramkumar,G.Emayavaramban,J.MacklinAbrahamNavamani,R.RenugaDevi,
A.Prema,B.Booba,andP.Sriramakrishnan
5. SmartMobilitySystemforPhysicallyChallengedPeople.................... 67
S.Sundaramahalingam,B.V.Manikandan,K.Banumalar,andS.Arockiaraj
6. DHS:TheCognitiveCompanionforAssistedLivingoftheElderly ........... 77
R.Krithiga
7. RaspberryPiBasedCancerCellDetectionUsingSegmentationAlgorithm..... 85
S.Yogashri,S.Jayanthy,andC.Narendhar
8. AnAACCommunicationDeviceforPatientswithTotalParalysis............. 97
OshinR.JacobandSundarG.Naveen
9. CaseStudiesonMedicalDiagnosisUsingSoftComputingTechniques....... 105
MaryX.Anitha,LinaRose,AldrinKarunaharan,andAnandPushparajJ.
10. Alzheimer’sDiseaseClassificationUsingMachineLearningAlgorithms.......117
S.Naganandhini,P.Shanmugavadivu,A.Asaithambi,andM.Mohammed
MansoorRoomi
v
vi Contents
11. FetalStandardPlaneDetectioninFreehandUltrasoundUsingMulti
LayeredExtremeLearningMachine .......................................135
S.JayanthiSreeandC.Vasanthanayaki
12. EarlierPredictionofCardiovascularDiseaseUsingIoTandDeepLearning
Approaches ............................................................143
R.SivaranjaniandN.Yuvaraj
13. AnalysisofHeartDiseasePredictionUsingVariousMachineLearning
Techniques.............................................................157
M.Marimuthu,S.Deivarani,andR.Gayathri
14. Computer-AidedDetectionofBreastCanceronMammograms:Extreme
LearningMachineNeuralNetworkApproach ..............................169
JayeshGeorgeM.andPerumalSankarS.
15. DeepLearningSegmentationTechniquesforCheckingtheAnomalies
ofWhiteMatterHyperintensitiesinAlzheimer’sPatients....................183
AntonittaEileenPiousandSrideviUnni
16. InvestigationsonStabilizationandCompressionofMedicalVideos ..........189
D.RaveenaJudieDolly,D.J.Jagannath,andR.AnupRaveenJaison
17. AnAutomatedHybridMethodologyUsingFireflyBasedFuzzyClustering
forDemarcationofTissueandTumorRegioninMagneticResonance
BrainImages ...........................................................193
SaravananAlagarsamy,KartheebanKamatchi,andVishnuvarthananGovindaraj
18. ARiskAssessmentModelforAlzheimer’sDiseaseUsingFuzzy
CognitiveMap..........................................................209
S.MeenakshiAmmalandL.S.Jayashree
19. ComparativeAnalysisofTexturePatternsfortheDetectionofBreast
CancerUsingMammogramImages .......................................221
J.ShinyChristobelandJ.JoshanAthanesious
20. AnalysisofVariousColorModelsforEndoscopicImages....................229
CarenBabu,AnandPaul,andD.AbrahamChandy
21. AdaptiveFractalImageCodingUsingDifferentialSchemefor
CompressingMedicalImages ............................................243
P.Chitra,M.MaryShanthiRani,andV.Sivakumar
Index .....................................................................253
Preface
In the last decade, a number of sophisticated and new clinical and medical image
analysis techniques had been evolved that strides the society in every facet of it. This
book provides an ideal reference for all the medical imaging researchers and profes-
sionalstoexploretheirinnovativemethodsandanalysisonimagingtechnologiesforthe
better prospective of patient care. The purpose of this compendium is to serve as an
exclusive source for the new computer assisted clinical and medical developments in
imaging diagnosis, intervention, and analysis. This book will also include articles on
computer-assisted medical scanning techniques, computer-aided diagnosis, robotic sur-
gery and imaging, imaging genomics, clinically oriented imaging physics and infor-
matics, augmented-reality medical visualization, imaging modalities, computerized
radiology, oncology, and surgery. Moreover, information on nonmedical imaging that
has medical applications such as multiphoton microscopy and confocal, photoacoustic
imaging, optical microendoscope, infrared radiation, and other imaging modalities
would be welcomed.
Each chapter in this book will provide annotations for all the medical and clinical
imaging and fundamental advances of clinical and medical image analysis techniques.
This book will be a good source for all the medical imaging and clinical research
professionals, outstanding scientists, and educators from all around the world for
network of knowledge sharing. This book will comprise high-quality disseminations of
newideas,technologyfocus,researchresultsanddiscussionsontheevolutionofclinical
and medical image analysis techniques for the benefit of both scientific and industrial
developments. This book is devoted to the spreading of knowledge through the
publication of scholarly research, primarily in the fields of clinical and medical imaging.
The types of chapters consented include those that cover the development and imple-
mentation of algorithms and strategies based on the use of geometrical, statistical,
physical, functional to solve the following types of problems, using medical image
datasets: visualization, feature extraction, segmentation, image-guided surgery and
intervention, digital anatomical atlases, representation of pictorial data, statistical shape
analysis, computational physiology, virtual and augmented reality for therapy planning
and guidance, telemedicine with medical images, telepresence in medicine, and image-
guided surgeries.
vii
About the Editors
J. Dinesh Peter is currently working as associate professor, Depart-
ment of Computer Science and Engineering at Karunya Institute of
Technology and Sciences, Coimbatore, Tamil Nadu, India. Prior to
this, he was a full time research scholar at National Institute of
Technology, Calicut, India, from where he received his Ph.D. in
computer science and engineering. His research focus includes Big data, image proces-
sing, and computer vision. He has several publications in various reputed international
journals and conference papers which are widely referred to. He is a member of IEEE,
MICCAI, Computer Society of India, and Institution of Engineers India and has served
as session chairs and delivered plenary speeches for various international conferences
and workshops. He has conducted many international conferences and been an editor
for Springer proceedings and many special issues in journals.
Steven Lawrence Fernandes is currently working as a postdoctoral
researcher in the area of deep learning under the guidance of Prof.
Sumit Kumar Jha at The University of Central Florida, USA. He also
has postdoctoral research experience working at The University of
Alabama at Birmingham, USA. He has his Ph.D. in computer vision
and machine learning from Karunya Institute of Technology and
Sciences, Coimbatore, Tamil Nadu, India. His Ph.D. work “Match
CompositeSketchwithDroneImages”hasreceivedpatentnotification
(Patent Application Number: 2983/CHE/2015) from Government of India, Controller
General of Patents, Designs & Trade Marks. He has received the prestigious U.S. award
from Society for Design and Process Science for his outstanding service contributions in
the year 2017 and Young Scientist Award by Vision Group on Science and Technology,
Government of Karnataka, India in the year 2014. He also received research grant from
University of Houston Downtown, USA and The Institution of Engineers (India),
Kolkata, India. He has collaborated with various scientists, professors, researchers, and
jointly published more than 50 research articles which are in Science Citation Indexed
(SCI) Journals.
Carlos Eduardo Thomaz holds a degree in electronic engineering
from the Pontifical Catholic University of Rio de Janeiro (1993), a
master’s degree in electrical engineering from the Pontifical Catholic
University of Rio deJaneiro (1999), a Ph.D. and a postdoctoraldegree
incomputersciencefromImperialCollegeLondon(2005).Heisafull
professor at FEI’s University Center. He has experience in the area of
computer science, with emphasis on pattern recognition in statistics,
working mainly in the following subjects: computational vision, computation in
medical images, and biometrics.
ix
