Histopathological image analysis in medical decision making

361 Pages·2019·19.641 MB·English

by  R. T. Goswami (editor), Himansu Das (editor), Nilanjan Dey (editor), Amira Ashour (editor), Harihar Kalia (editor)

Histopathological Image
Analysis in Medical
Decision Making
Nilanjan Dey
Techno India College of Technology, India
Amira S. Ashour
Tanta University, Egypt
Harihar Kalia
Seemantha Engineering College, India
R.T. Goswami
Techno India College of Technology, India
Himansu Das
KIIT University, India
A volume in the Advances in
Medical Technologies and Clinical
Practice (AMTCP) Book Series
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Library of Congress Cataloging-in-Publication Data
Names: Dey, Nilanjan, 1984- editor. | Ashour, Amira, 1975- editor. | Kalia,
Harihar, editor. | Goswami, R. T., editor. | Das, Himansu, editor.
Title: Histopathological image analysis in medical decision making / Nilanjan
Dey, Amira S. Ashour, Harihar Kalia, R.T. Goswami, and Himansu Das,
editors.
Description: Hershey, PA : Medical Information Science Reference, [2019] |
Includes bibliographical references.
Identifiers: LCCN 2018008106| ISBN 9781522563167 (hbk.) | ISBN 9781522563174
(ebook)
Subjects: | MESH: Histological Techniques | Image Processing,
Computer-Assisted | Clinical Decision-Making | Pattern Recognition,
Automated
Classification: LCC RC78.7.D53 | NLM QS 26.5 | DDC 616.07/54--dc23 LC record available at
https://lccn.loc.gov/2018008106

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ISSN:2327-9354
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Editor-in-Chief: Srikanta Patnaik, SOA University, India & Priti Das,
S.C.B. Medical College, India
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Table of Contents
Preface..................................................................................................................xv
Acknowledgment.................................................................................................xx
Chapter 1
A.Study.on.Segmentation.of.Leukocyte.Image.With.Shannon’s.Entropy..............1
N. Sri Madhava Raja, St. Joseph’s College of Engineering, India
S. Arunmozhi, Manakula Vinayagar Institute of Technology, India
Hong Lin, University of Houston – Downtown, USA
Nilanjan Dey, Techno India College of Technology, India
V. Rajinikanth, St. Joseph’s College of Engineering, India
Chapter 2
Microscopic.Image.Processing.for.the.Analysis.of.Nosema.Disease...................28
Soumaya Dghim, Universidad de Las Palmas de Gran Canaria, Spain
Carlos M. Travieso-Gonzalez, Universidad de Las Palmas de Gran
Canaria, Spain
Mohamed Salah Gouider, Université de Tunis, Tunisia
Melvin Ramírez Bogantes, Costa Rica Institute of Technology, Costa
Rica
Rafael A. Calderon, National University of Costa Rica, Costa Rica
Juan Pablo Prendas-Rojas, Costa Rica Institute of Technology, Costa
Rica
Geovanni Figueroa-Mata, Costa Rica Institute of Technology, Costa
Rica
Chapter 3
Medical.Image.Lossy.Compression.With.LSTM.Networks.................................47
Nithin Prabhu G., JSS Science and Technology University, India
Trisiladevi C. Nagavi, JSS Science and Technology University, India
Mahesha P., JSS Science and Technology University, India

Chapter 4
Digital.Image.Analysis.for.Early.Diagnosis.of.Cancer:.Identification.of.Pre-
Cancerous.State.....................................................................................................69
Durjoy Majumder, West Bengal State University, India
Madhumita Das, West Bengal State University, India
Chapter 5
Multi-Criteria.Decision-Making.Techniques.for.Histopathological.Image.
Classification.......................................................................................................103
Revathi T., Mepco Schlenk Engineering College, India
Saroja S., Mepco Schlenk Engineering College, India
Haseena S., Mepco Schlenk Engineering College, India
Blessa Binolin Pepsi M., Mepco Schlenk Engineering College, India
Chapter 6
Histopathological.Image.Analysis.in.Medical.Decision.Making:.
Classification.of.Histopathological.Images.Based.on.Deep.Learning..
Model..................................................................................................................139
R. Meena Prakash, Sethu Institute of Technology, India
Shantha Selva Kumari R., Mepco Schlenk Engineering College, India
Chapter 7
A.Novel.Approach.of.K-SVD-Based.Algorithm.for.Image.Denoising..............154
Madhu Golla, VNR Vignana Jyothi Institute and Engineering and
Technology, India
Sudipta Rudra, VNR Vignana Jyothi Institute and Engineering and
Technology, India
Chapter 8
Analysis.of.Medical.Images.Using.Fractal.Geometry........................................181
Soumya Ranjan Nayak, KL University, India
Jibitesh Mishra, College of Engineering and Technology, India
Chapter 9
Analysis.of.Color.Image.Encryption.Using.Multidimensional.Bogdanov..
Map.....................................................................................................................202
R. N. Ramakant Parida, Kalinga Institute of Industrial Technology,
India
Swapnil Singh, Kalinga Institute of Industrial Technology, India
Chittaranjan Pradhan, Kalinga Institute of Industrial Technology, India

Chapter 10
Automatic.Computerized.Diagnostic.Tool.for.Down.Syndrome.Detection.in.
Fetus....................................................................................................................226
Michael Dinesh Simon, Anna University, India
Kavitha A. R., Anna University, India
Chapter 11
Adaptive.Prediction.Methods.for.Medical.Image/Video.compression.for.
Telemedicine.Application...................................................................................244
Ketki C. Pathak, Sarvajanik College of Engineering and Technology,
India
Jignesh N. Sarvaiya, Sardar Vallabhbhai National Institute of
Technology Suart, India
Anand D. Darji, Sardar Vallabhbhai National Institute of Technology
Suart, India
Chapter 12
HE.Stain.Image.Segmentation.Using.an.Innovative.Type-2.Fuzzy.Set-Based.
Approach.............................................................................................................276
Dibya Jyoti Bora, Kaziranga University, India
Compilation of References...............................................................................300
About the Contributors....................................................................................330
Index...................................................................................................................338
Detailed Table of Contents
Preface..................................................................................................................xv
Acknowledgment.................................................................................................xx
Chapter 1
A.Study.on.Segmentation.of.Leukocyte.Image.With.Shannon’s.Entropy..............1
N. Sri Madhava Raja, St. Joseph’s College of Engineering, India
S. Arunmozhi, Manakula Vinayagar Institute of Technology, India
Hong Lin, University of Houston – Downtown, USA
Nilanjan Dey, Techno India College of Technology, India
V. Rajinikanth, St. Joseph’s College of Engineering, India
In.recent.years,.a.considerable.number.of.approaches.have.been.proposed.by.
the.researchers.to.evaluate.infectious.diseases.by.examining.the.digital.images.
of.peripheral.blood.cell.(PBC).recorded.using.microscopes..In.this.chapter,.a.
semi-automated.approach.is.proposed.by.integrating.the.Shannon’s.entropy.(SE).
thresholding.and.DRLS-based.segmentation.procedure.to.extract.the.stained.blood.
cell.from.digital.PBC.pictures..This.work.implements.a.two-step.practice.with.
cuckoo.search.(CS).and.SE-based.pre-processing.and.DRLS-based.post-processing.
procedure.to.examine.the.PBC.pictures..During.the.experimentation,.the.PBC.pictures.
are.adopted.from.the.database.leukocyte.images.for.segmentation.and.classification.
(LISC)..The.proposed.approach.is.implemented.by.considering.the.RGB.scale.and.
gray.scale.version.of.the.PBC.pictures,.and.the.performance.of.the.proposed.approach.
is.confirmed.by.computing.the.picture.similarity.and.statistical.measures.computed.
with.the.extracted.stained.blood.cell.with.the.ground.truth.image.

Chapter 2
Microscopic.Image.Processing.for.the.Analysis.of.Nosema.Disease...................28
Soumaya Dghim, Universidad de Las Palmas de Gran Canaria, Spain
Carlos M. Travieso-Gonzalez, Universidad de Las Palmas de Gran
Canaria, Spain
Mohamed Salah Gouider, Université de Tunis, Tunisia
Melvin Ramírez Bogantes, Costa Rica Institute of Technology, Costa
Rica
Rafael A. Calderon, National University of Costa Rica, Costa Rica
Juan Pablo Prendas-Rojas, Costa Rica Institute of Technology, Costa
Rica
Geovanni Figueroa-Mata, Costa Rica Institute of Technology, Costa
Rica
In.this.chapter,.the.authors.tried.to.develop.a.tool.to.automatize.and.facilitate.the.
detection.of.Nosema.disease..This.work.develops.new.technologies.in.order.to.solve.
one.of.the.bottlenecks.found.on.the.analysis.bee.population..The.images.contain.
various.objects;.moreover,.this.work.will.be.structured.on.three.main.steps..The.
first.step.is.focused.on.the.detection.and.study.of.the.objects.of.interest,.which.are.
Nosema.cells..The.second.step.is.to.study.others’.objects.in.the.images:.extract.
characteristics..The.last.step.is.to.compare.the.other.objects.with.Nosema..The.authors.
can.recognize.their.object.of.interest,.determining.where.the.edges.of.an.object.are,.
counting.similar.objects..Finally,.the.authors.have.images.that.contain.only.their.
objects.of.interest..The.selection.of.an.appropriate.set.of.features.is.a.fundamental.
challenge.in.pattern.recognition.problems,.so.the.method.makes.use.of.segmentation.
techniques.and.computer.vision..The.authors.believe.that.the.attainment.of.this.work.
will.facilitate.the.diary.work.in.many.laboratories.and.provide.measures.that.are.
more.precise.for.biologists.
Chapter 3
Medical.Image.Lossy.Compression.With.LSTM.Networks.................................47
Nithin Prabhu G., JSS Science and Technology University, India
Trisiladevi C. Nagavi, JSS Science and Technology University, India
Mahesha P., JSS Science and Technology University, India
Medical.images.have.a.larger.size.when.compared.to.normal.images..There.arises.a.
problem.in.the.storage.as.well.as.in.the.transmission.of.a.large.number.of.medical.
images..Hence,.there.exists.a.need.for.compressing.these.images.to.reduce.the.size.
as.much.as.possible.and.also.to.maintain.a.better.quality..The.authors.propose.a.
method.for.lossy.image.compression.of.a.set.of.medical.images.which.is.based.on.
Recurrent.Neural.Network.(RNN)..So,.the.proposed.method.produces.images.of.
variable.compression.rates.to.maintain.the.quality.aspect.and.to.preserve.some.of.
the.important.contents.present.in.these.images.