Table Of Contents:

List of Contributors xvii
Preface xxi
Acknowledgments xxxi

The Subgross Morphology of Normal and Pathologically Altered Breast Tissue 1(50)

Tibor Tot

Introduction 2(1)

Subgross Breast Anatomy 3(12)

The Normal Mammogram 15(5)

In Situ Development of Malignant Tumors 20(10)

Invasive Carcinomas 30(15)

Time as Morphologic Factor 45(6)

References 47(4)

Fundamentals of Achieving Functional and Anatomical Imaging with Breast MRI: Physical and Clinical Concepts 51(58)

Dee H. Wu

Ann G. Archer

L. Jill Hast

Brenda Elledge

Douglas Beall

Max Walter

Susan M. Edwards

Heather R. Webb

Barry J. Greer

Erika Rubesova

Introduction 52(7)

Consequences of Composition, Architectural, and Functional Evaluation in Breast MR Imaging 59(1)

Breast Composition and Hormonal Influences (Fat, Ducts, Secretions, and Breast Implants) 60(3)

Region of Interest Definition of Tumors 63(1)

Technological Fundamentals of Breast MRI 64(38)

Summary 102(7)

Acknowledgments 102(1)

References 103(6)

An Indexed Atlas of Digital Mammograms for Computer-Aided Diagnosis of Breast Cancer 109(20)

Hilary Alto

Rangaraj M. Rangayyan

Raman B. Paranjape

J.E. Leo Desautels

Heather Bryant

Introduction 110(1)

Databases of Mammograms 111(1)

The Indexed Atlas Concept 112(2)

Design of the University of Calgary Indexed Atlas of Mammograms 114(5)

Use of Mobile Software Agents with the Indexed Atlas 119(1)

Discussion 120(9)

Acknowledgments 122(1)

References 122(7)

Genetic Algorithms in CAD Mammography 129(30)

Renato Campanini

Nico Lanconelli

Introduction 130(3)

CAD Critical Issues 133(3)

Genetic Algorithms: A Brief Overview 136(5)

GA for Parameters Optimization 141(10)

GA for Feature Selection 151(8)

References 156(3)

Mammographic Mass Detection by Robust Learning Algorithms 159(38)

Aize Cao

Qing Song

Xulei Yang

Zhimin Wang

Yan Shui

Introduction 160(1)

Robust Information Clustering for Automatic Mass Detection 161(17)

Vicinal Support Vector Machine for Mass-Pattern Analysis 178(19)

References 192(5)

Analysis of Bilateral Asymmetry in Mammograms via Directional Filtering with Gabor Wavelets 197(32)

Ricardo J. Ferrari

Rangaraj M. Rangayyan

J.E. Leo Desautels

Annie F. Frere

Introduction 198(2)

Bilateral Asymmetry in Mammograms 200(1)

Construction of Gabor Wavelets 200(5)

Directional Analysis 205(6)

Analysis of Asymmetry in Mammograms 211(4)

Results 215(9)

Discussion and Conclusions 224(5)

Acknowledgments 224(1)

References 224(5)

Support Vector Machines in CAD Mammography 229(34)

Renato Campanini

Nico Lanconelli

Matteo Roffilli

Introduction 230(1)

Support Vector Machines: A Qualitative Approach 231(6)

SVMs for CAD 237(7)

Novel Featureless Approach 244(7)

SVMs: Mathematical Details 251(12)

References 260(3)

A Weighted Gaussian Mixture Model with Markov Random Fields and Adaptive Expert Combination Strategy for Segmenting Masses in Mammograms 263(28)

Sameer Singh

Keir Bovis

Introduction 264(2)

Weighted Gaussian Mixture Models 266(3)

Combination of Experts 269(5)

Experimental Details 274(3)

Results 277(8)

Conclusions 285(6)

References 286(5)

Detection of Microcalcifications in Mammograms 291(24)

Begona Acha

Carmen Serrano

Rangaraj M. Rangayyan

J. E. Leo Desautels

Detection of Microcalcifications: Background and Motivation 292(1)

State of the Art 293(4)

Detection of Microcalcifications Using the 2D Linear Prediction Error 297(8)

Results 305(2)

Conclusions 307(8)

References 308(7)

Using Computational Intelligence for Computer-Aided Diagnosis of Screen-Film Mammograms 315(62)

Walker H. Land, Jr.

Daniel W. McKee

Frances R. Anderson

Timothy Masters

Joseph Y. Lo

Mark Embrechts

John Heine

Evolutionary Programming and Evolutionary Computation 317(9)

Evolutionary Programming/Adaptive Boosting Hybrid 326(6)

Another Evolutionary Programming Approach 332(6)

EP-Derived Support Vector Machines 338(12)

A Support Vector Machine (SVM) Generalized Regression Neural Network (GRNN) Oracle 350(7)

Partial Least Squares (PLS) and Kernel-Partial Least Squares (K-PLS) 357(9)

Artificial Intelligence, Knowledge Representation, and Knowledge Engineering 366(11)

Acknowledgments 371(1)

References 372(5)

New Approach for Breast Skin-Line Estimation in Mammograms 377(32)

Yajie Sun

Jasjit Suri

Rangaraj M. Rangayyan

J.E. Leo Desautels

Introduction 379(2)

A Brief Overview of the Proposed System 381(2)

Initial Skin-Line Boundary Estimation 383(2)

Initial Confirmed Portion Extraction: A Greedy Approach 385(3)

Extraction of Stroma Edge 388(4)

Skin-line Estimation: A Dependency Approach 392(4)

Performance Evaluation System 396(5)

Results: Dependency Approach versus Deformable Model 401(4)

Discussion and Conclusions 405(4)

Acknowledgments 406(1)

References 406(3)

Computerized Mass Detection for Digital Breast Tomosynthesis 409(20)

Ingrid Reiser

Robert Nishikawa

Introduction 410(1)

CADe Based on the Reconstructed Breast Volume 411(9)

CADe Based on the Sequence of Projection Images 420(5)

Summary 425(4)

Acknowledgments 426(1)

References 426(3)

Breast-Imaging Registration: A Review 429(58)

Yujun Guo

Jasjit Suri

Radhika Sivaramakrishna

Introduction 430(4)

Registration Background 434(6)

Intramodality Breast-Image Registration 440(18)

Intermodality Breast-Image Registration 458(5)

Biomechanical Breast Model 463(4)

Validation of Breast-Registration Methods 467(4)

Discussion and Conclusions 471(16)

References 474(13)

A Mammographic Registration Framework Based on Anatomical Linear Structures 487(42)

Robert Marti

Caroline M.E. Rubin

Erika R.E. Denton

Reyer Zwiggelaar

Introduction 488(1)

Correspondence of Mammographic Images 489(12)

Identifying Salient Linear Structures 501(7)

Registration Using Linear Structures 508(5)

Detection of Abnormalities 513(2)

Tracking of Linear Structures 515(3)

Automatic MR Correspondence Based on Linear Structures 518(6)

Conclusions 524(5)

References 525(4)

AMDI
Indexed Atlas of Digital Mammograms That Integrates Case Studies, E-Learning, and Research Systems via the Web 529(28)

Denise Guliato

Ernani V. De Melo

Ricardo S. Boaventura

Rangaraj M. Rangayyan

Breast Cancer and Mammography 530(1)

Indexed Atlases and Telemedicine 530(1)

Overview of AMDI 531(21)

Conclusion 552(5)

Acknowledgments 553(1)

References 553(4)

Detection, Characterization, and Visualization of Breast Cancer Using 3D Ultrasound Images 557(12)

Daisuke Fukuoka

Takeshi Hara

Hiroshi Fujita

Introduction 558(1)

Material and Methods 558(6)

Results 564(1)

Discussions 565(1)

Conclusions 566(3)

References 566(3)

Computer-Aided Diagnosis for 2D/3D Breast Ultrasound 569(44)

Ruey-Feng Chang

Chia-Ling Tsai

Sheng-Fang Huang

Wen-Jia Kuo

Dar-Ren Chen

Woo Kyung Moon

Yu-Len Huang

Wei-Ming Chen

Wen-Jie Wu

Introduction 571(1)

Texture-Based Computer-Aided Diagnosis for 2D Breast Ultrasound 572(5)

Shape-Based Computer-Aided Diagnosis for 2D Breast Ultrasound 577(5)

Classification Techniques for Breast US CAD 582(8)

Computer-Aided Diagnosis for 3D Breast Ultrasound 590(17)

Conclusion 607(6)

References 608(5)

Automatic Pectoral Muscle Segmentation on Mediolateral Oblique View Mammograms 613(26)

Sze Man Kwok

Ramachandran Chandrasekhar

Yianni Attikiouzel

Mary T. Rickard

Introduction 614(2)

Overall Algorithm 616(1)

Orientation and Notation 617(1)

Straight-Line Estimation and Validation 618(6)

Iterative Cliff Detection 624(3)

Experimental Setup 627(2)

Results 629(3)

Discussion 632(3)

Conclusions 635(4)

Acknowledgments 636(1)

References 636(3)

Performance Evaluation of CADe Algorithms in Mammography 639(62)

Michael A. Wirth

Introduction 640(5)

Performance Evaluation in CADe 645(5)

Evaluating Image-Processing Algorithms 650(5)

Evaluating Enhancement Algorithms 655(4)

Little Boxes Made of Algorithms 659(2)

Performance Evaluation Framework 661(6)

Mammogram Databases 667(4)

Breast-Region Segmentation: Examination of a Performance-Evaluation Process 671(12)

Recommendations 683(18)

References 686(15)

A Simple Method for Automatically Locating the Nipple on Mammograms 701(22)

Ramachandran Chandrasekhar

Yianni Attikiouzel

Introduction 702(1)

Review of Previous Work 703(1)

Outline of Method 703(2)

Notation 705(1)

Detailed Description of Algorithm 705(3)

Experimental Method 708(4)

Results and Discussion 712(8)

Conclusions 720(3)

Acknowledgments 721(1)

References 721(2)

Algorithms for Segmenting Small Low-Contrast Objects in Images 723(16)

Isaac N. Bankman

Tanya Nizialek

Inpakala Simon

Olga B. Gatewood

Irving N. Weinberg

William R. Brody

Introduction 724(3)

Segmentation Algorithms 727(4)

Results 731(5)

Conclusion 736(3)

References 737(2)

Computer-Aided Diagnosis of Breast Cancer on MR Imaging 739(24)

Qiu Wu

Mia K. Markey

Medical Imaging for Breast Cancer Detection and Diagnosis 740(1)

Magnetic Resonance Imaging of the Breast 740(1)

Dynamic Contrast-Enhanced Breast MRI 741(3)

Computer-Aided Detection and Diagnosis 744(1)

Developing CADe/CADx for DCE Breast MRI 745(8)

Future Directions 753(10)

Acknowledgments 754(1)

References 755(8)

Review on Real-Time Magnetic Resonance Gad-Enhanced Breast Lesion Characterization 763(28)

Jasjit S. Suri

Alexander X. Falcao

Laura Reden

Jianbo Gao

Swamy Laxminarayan

Introduction 764(2)

Data Acquisition and Scanning Protocols 766(3)

Three Techniques for MR Breast Tumor Detection and Analysis 769(13)

Issues Related to Real Time and Graphical User Interfaces 782(2)

Conclusions and Future Challenges 784(7)

Acknowledgments 784(1)

References 785(6)

Breast MRI Computer-Aided Diagnosis Systems 791(42)

Lina Arbash Meinel

Joseph M. Reinhardt

Introduction 792(1)

Breast MRI Segmentation 793(22)

Selection of the Shape, Texture, and Contrast-Enhancement Features 815(4)

Breast MRI Classification 819(7)

Validation 826(1)

Future research 827(6)

References 828(5)

Automatic Assessment of Mammogram Adequacy and Quality 833(14)

Sze Man Kwok

Ramachandran Chandrasekhar

Introduction 834(2)

The Mediolateral Oblique View Mammogram 836(1)

Adequacy Assessment Algorithms 837(6)

Results 843(1)

Discussion 843(1)

Conclusions 844(3)

Acknowledgments 844(1)

References 844(3)

Probability Modeling of CAD Systems for Mammography 847(24)

John Maleyeff

Frank C. Kaminsky

Introduction 848(2)

Background and Motivation 850(1)

Probability Modeling in CAD 851(6)

Analysis of Mammography Systems 857(4)

Illustrative Model Results 861(5)

Conclusion 866(5)

References 868(3)

Computer-Aided Diagnosis in Breast Imaging: Where Do We Go after Detection? 871(30)

Joseph Y. Lo

Anna O. Bilska-Wolak

Jay A. Baker

Georgia D. Tourassi

Carey E. Floyd

Mia K. Markey

Introduction 872(1)

CADx Classifier Models 873(6)

Feature Selection 879(3)

Data Sampling 882(4)

Clinical and Regulatory Acceptance 886(15)

References 892(9)

The Current Status and Likely Future of Breast Imaging CAD 901(62)

Jasjit S. Suri

Ramachandran Chandrasekhar

Nico Lanconelli

Renato Campanini

Matteo Roffilli

Ruey-Feng Chang

Yujun Guo

Radhika Sivaramakrishna

Tibor Tot

Begona Acha

Carmen Serrano

Ingrid Reiser

Robert M. Nishikawa

Dee H. Wu

Koon-Pong Wong

Ashwini Kshirsagar

Yajie Sun

Michael Wirth

Aize Cao

J.E. Leo Desautels

Rangaraj M. Rangayyan

Introduction 903(2)

Shift in Breast Imaging Paradigms 905(1)

Different Imaging Modalities for Breast Imaging 905(13)

Current and Future Challenges for CAD 918(17)

Commercial Breast CAD Systems and Their Role in Clinical Settings 935(5)

Resources in Breast Imaging: Research Centers, Conferences, Databases, Publications, and Patents 940(2)

Conclusions 942(21)

Acknowledgment 944(1)

References 944(19)
Index 963