Medical Imaging Informatics (eBook)

Medical Imaging Informatics 2
Foreword 5
Preface 8
Contributors 12
Table of Contents 13
PART I Performing the Imaging Exam 19
Chapter 1 Introduction 20
What is Medical Imaging Informatics? 20
The Process of Care and the Role of Imaging 21
Medical Imaging Informatics: From Theory to Application 22
Improving the Use of Imaging 22
Choosing a Protocol: The Role of Medical Imaging Informatics 23
Cost Considerations 25
A Historic Perspective and Moving Forward 26
PACS: Capturing Images Electronically 26
Teleradiology: Standardizing Data and Communications 27
Integrating Patient Data 27
Understanding Images: Today’s Challenge 28
References 29
Chapter 2 A Primer on Imaging Anatomy and Physiology 31
A Review of Basic Imaging Modalities 31
Projectional Imaging 31
Core Physical Concepts 31
Imaging 33
Computed Tomography 39
Imaging 39
Additional CT Applications 49
Magnetic Resonance 50
Core Physical Concepts 50
Additional MR Imaging Sequences 56
Ultrasound Imaging 59
An Introduction to Imaging-based Anatomy & Physiology
Respiratory System 62
The Larynx and Trachea 62
The Lungs and Airways 63
The Pleura, Chest Wall, and Respiratory Muscles 66
Pulmonary Ventilation: Inspiration and Expiration 67
Pressure Relationships during Inspiration and Expiration 67
Factors Influencing Airflow 68
Measures of Lung Function 69
Basic Respiratory Imaging 70
Imaging Analysis of Pulmonary Pathophysiology 72
The Brain 74
Cerebral Hemispheres 75
Cerebral White Matter 78
Basal Nuclei 78
Brainstem 79
Meninges 79
Cerebral Vascular Anatomy 80
Breast Anatomy and Imaging 81
Breast Imaging 82
Breast Cancer and other Findings 85
Musculoskeletal System 87
Imaging of the Musculoskeletal System 88
Cardiac System 92
Cardiac Medical Problems 93
Basic Cardiac and Vascular Imaging 94
Urinary System 95
Basic Imaging of the Urinary System 96
Urinary Medical Problems 97
Upper Gastrointestinal (GI) System 100
References 102
PART II Integrating Imaging into the Patient Record 107
Chapter 3 Information Systems & Architectures
The Electronic Medical Record 108
EMR Information Systems 109
Hospital Information Systems 110
Picture Archive and Communication Systems 111
Data Standards for Communication and Representation 113
DICOM (Digital Imaging and Communication in Medicine) 113
The DICOM Model 114
DICOM Extensions 117
Health Level 7 (HL7) 118
Messaging Protocol 118
Reference Implementation Model (RIM) 119
Clinical Document Architecture (CDA) 120
Logical Observation Identifier Names and Codes (LOINC) 122
Distributed Information Systems 123
Peer-to-peer Architectures 123
First Generation P2P: Centralized Searching 124
Second Generation P2P: Simple Decentralized Searching (Query Flooding) 125
Second Generation P2P: Distributed Hash Tables 127
Third Generation P2P 128
P2P Healthcare Applications 130
Grid Computing 131
Globus Toolkit 133
Condor 134
Grid Computing Healthcare Applications 135
Cloud Computing: Beyond the Grid 137
Discussion and Applications 137
Teleradiology, Telemedicine, and Telehealth 138
Integrating Medical Data Access 141
Collaborative Clinical Research: Example Image Repositories 144
References 146
Chapter 4 Medical Data Visualization: Toward Integrated Clinical Workstations 153
Navigating Clinical Data 153
Elements of the Display 154
Visual Metaphors: Emphasizing Different Relationships 163
Temporal Representations 163
Spatial Representations 166
Multidimensional Relationships 169
Causal Relationships 170
Navigating Images 171
Combining Information: Integrating the Medical Data 175
Defining Context 175
Defining the User 176
Defining the Task: Incorporating Workflow 178
Combining Graphical Metaphors 180
Creating Integrated Displays 180
Interacting with Data 184
Imaging Workflow & Workstations
Discussion and Applications 191
TimeLine: Problem-centric Visualization 192
Data Reorganization 193
Visualization Dictionary 194
Patient-centric Visualization 196
References 198
PART III Documenting Imaging Findings 208
Chapter 5 Characterizing Imaging Data 209
What is a Pixel? 209
Representing Space, Time, and Energy 210
Mathematical Representations of Pixel Values 211
Physical Correspondence to the Real World 213
Compiling Scientific-quality Imaging Databases 214
Improving Pixel Characterization 215
Pre-acquisition: Standardizing Imaging Protocols 216
Post-acquisition: Pixel Value Calibration and Mapping 216
Dealing with Image Noise 221
Characterizing Noise 222
Noise Reduction 226
Registration: Improving Pixel Positional Characterization 230
Transformations 230
Similarity Metrics 233
Preprocessing 234
User Interaction 235
Comparison of Methods 235
Imaging Features 236
Appearance-based Image Features 236
Shape-based Image Features 239
Feature Selection 241
Aggregating Features: Dimensionality Reduction 242
Imaging Atlases and Group-wise Image Analysis 244
The Need for Atlases 245
Creating Atlases 245
Using Atlases 247
Morphometry 249
Discussion 251
Towards Medical Image Analysis 252
Mathematical Foundations 252
Image Modeling 254
Linking Images to Additional Knowledge 254
References 256
Chapter 6 Natural Language Processing of Medical Reports 268
An Introduction to Medical NLP 268
Assessment of Application Requirements 271
Overview of the Medical NLP Problem 272
Medical NLP System Components & Tasks
Identifying Document Structure: Structural Analysis 273
Section Boundary Detection and Classification 274
Sentence Boundary Detection 275
Tokenization 276
Defining Word Sequences 279
Named Entity Recognition and De-identification 284
Concept Coding: Ontological Mapping 287
The MetaMap Approach 288
Data Mining and Lookup-Table Caches 289
Phrasal Chunking 289
Context Modeling 291
Classifier Design 293
Linear Sequence Optimization 296
Parsing: Relation Extraction and Constituency Parsing 296
Compositionality in Language 297
Discussion 300
Untitled 301
Chapter 7 Organizing Observations: Data Models 310
Data Models for Representing Medical Data 310
Spatial Data Models 311
Spatial Representations 311
Spatial Relationships and Reasoning 312
Anatomical and Imaging-based Models 315
Temporal Data Models 319
Representing Time 319
Temporal Relationships and Reasoning 324
Some Open Issues in Temporal Modeling 326
Clinically-oriented Views 327
Alternative Views and Application Domains 329
Discussion and Applications 330
A Phenomenon-centric View: Supporting Investigation 330
What is a Mass? An Exercise in Separating Observations from Inferences 331
PCDM Core Entities 334
Implementing the PCDM 336
References 337
PART IV Toward Medical Decision Making 343
Chapter 8 Disease Models, Part I: Graphical Models 344
Uncertainty and Probability 344
Why Probabilities? 344
Laws of Probability: A Brief Review 346
Probability and Change 348
Graphical Models 349
Graph Theory 349
Graphs and Probabilities 350
Representing Time 352
Graphs and Causation 354
Bayesian Belief Networks in Medicine 355
Belief Network Construction: Building a Disease Model 356
Causal Inference 360
Causal Models, Interventions, and Counterfactuals 360
Latent Projections and their Causal Interpretation 363
Identification 364
Discussion and Applications 368
Building Belief and Causal Networks: Practical Considerations 369
Accruing Sufficient Patient Data 370
Handling Uncertainty in Data 372
Handling Selection Bias 373
References 374
Chapter 9 Disease Models, Part II: Querying & Applications
Exploring the Network: Queries and Evaluation 379
Inference: Answering Queries 379
Belief Updating 380
Abductive Reasoning 385
Inference on Relational Models 388
Diagnostic, Prognostic, and Therapeutic Questions 389
Evaluating BBNs 391
Predictive Power 391
Sensitivity Analysis 392
Interacting with Medical BBNs/Disease Models 394
Defining and Exploring Structure 394
Expressing Queries and Viewing Results 395
Discussion and Applications 397
Naïve Bayes 398
Imaging Applications 399
Querying and Problem-centric BBN Visualization 400
Visual Query Interface 400
AneurysmDB 404
References 406
Chapter 10 Evaluation 410
Biostatistics and Study Design: A Primer 410
Statistical Concepts 410
Confidence Intervals 410
Significance and Hypothesis Testing 411
Assessing Errors and Performance 414
Study Design 416
Types of Study Designs 417
Study Variable Selection and Population Definition 419
Population Size: Sample Size and Power Calculations 420
Study Bias and Error 423
Meta-analysis 424
Decision Making 425
Regression Analysis 425
Decision Trees 426
Informatics Evaluation 427
Evaluating Information Retrieval Systems 428
Information Needs 428
Relevance 430
Evaluation Metrics 431
Medical Content-based Image Retrieval Evaluation 433
Assessing Usability 435
Evaluation Techniques 436
Discussion 440
References 441