This book constitutes the refereed proceedings of the International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry, MDA 2008, held in Leipzig, Germany, on July 14, 2008.
The 18 full papers presented were carefully reviewed and selected for inclusion in the book. The topics include techniques and developments of signal and image producing procedures, object matching and object tracking in microscopic and video microscopic images, 1D, 2D and 3D shape analysis, description, feature extraction of texture, structure and location, and signal analysis and interpretation, image segmentation algorithms, parallelization of image analysis and interpretation algorithms, and semantic tagging of microscopic images, and application-oriented research from life science applications.
Author(s): Petra Perner, Ovidio Salvetti
Series: Lecture Notes in Artificial Intelligence 5108
Edition: 1
Publisher: Springer
Year: 2008
Language: English
Pages: 181
Front matter......Page 1
Introduction......Page 9
Immune System Mechanisms......Page 11
Modeling Algorithm......Page 12
Scheduling the Models of the Immune System......Page 14
Proposal for a Macro-model Algorithm of the Immune System......Page 16
References......Page 18
Introduction......Page 20
Semi-automatic Data Pipelining Structure & Data Filtering......Page 22
Visualization of Molecule Properties......Page 23
Extracting Fragments & Clustering......Page 28
Results and Discussion......Page 29
Case Study......Page 30
Classification of Molecules Using Active/Inactive Fragments as Features......Page 32
References......Page 33
Introduction......Page 35
Finding the Embryo Border......Page 37
Finding the Heart......Page 40
Creating a One Dimensional Signal Representing the Heart Beat......Page 42
Experimental Results......Page 43
Conclusion and Future Work......Page 44
Introduction......Page 46
Heart Failure......Page 48
Decision Support in Heart Failure......Page 49
Image Processing Methods......Page 50
Signal Processing Methods......Page 53
IT Infrastructure......Page 55
Integration in the General CDSS Architecture......Page 56
Conclusions......Page 58
Introduction......Page 60
Instrumentation......Page 61
Light Beam Distributions Mathematical Model......Page 62
Automatic Data Acquisition and Processing......Page 65
Experimental Results......Page 66
References......Page 69
Introduction......Page 70
Co-occurrence Matrix......Page 72
Color Texture Feature......Page 73
Training Patterns......Page 74
Results and Discussions......Page 76
Conclusion......Page 79
Introduction......Page 81
Data Pre-processing......Page 82
Sample Grouping......Page 83
Exploratory Analysis......Page 84
Time-Course MALDI-TOF-MS Serum Peptide Profiling of Non-small Cell Lung Cancer Patients Treated with Bortezomib, Cisplatin and Gemcitabine......Page 85
Breast Cancer Study with Maldi-TOF Mass Spectrometry Data of Serum Samples......Page 87
Summary......Page 88
Introduction......Page 90
Error Estimation by Kriging......Page 92
Classification by Kriging Error Matching......Page 95
Experimental Results......Page 97
Conclusion......Page 100
Introduction......Page 103
The First Absolute Central Moment......Page 105
The Positive and Negative Deviations......Page 106
A Filter Analogous to a GoG Filter......Page 107
A Local Thresholding Procedure......Page 108
The Mass Center of the Gray-Level Variability......Page 109
An Edge Localization Procedure......Page 110
The Real-Time Image Processing System......Page 111
The Flow-Mediated Vasodilation......Page 112
Conclusion......Page 113
References......Page 114
Four Sample Problems......Page 116
Notation......Page 120
Solutions to the Sample Optimization Problems......Page 123
Introduction......Page 131
The Basic Idea......Page 132
Examples of 1-Parameter Filtrations......Page 133
Algebraic Topology Tools......Page 137
Algebraic Topology Tools......Page 141
Discrete Invariants......Page 144
Conclusions......Page 145
Introduction......Page 147
Challenges and Requirements to the Systems......Page 148
The Architecture......Page 149
Case-Based Image Segmentation......Page 150
CBR Meta Learning for Image Segmentation......Page 151
Case-Based Object Recognition......Page 153
Decision Tree Induction......Page 154
Case-Based Reasoning for Image Interpretation......Page 156
Conceptual Clustering......Page 157
Results......Page 158
Expert Opinion......Page 160
Conclusion......Page 162
References......Page 163
Introduction......Page 166
Applied Microscopy Techniques......Page 167
Known Approaches to Cell Recognition......Page 168
Separation of Image Foreground and Background......Page 169
Detection of Probable Cell Membrane Pixels......Page 171
Cell Segmentation by Active Contours......Page 172
Enhancements......Page 173
Insertion of New Points......Page 174
Results......Page 175
Conclusion......Page 177
Back matter......Page 181
