Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques: Applications and TechniquesGonzalez, Fabio A., Romero, Eduardo Medical images are at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. Since the last decade, computers have become an invaluable tool for supporting medical image acquisition, processing, organization and analysis. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. This innovative publication serves as a leading industry reference as well as a source of creative ideas for applications of medical issues. |
Contents
| 1 | |
Section 2 Feature Extraction | 26 |
ComputerAided Detectionand Diagnosis of Breast CancerUsing Machine LearningTexture and Shape Features | 27 |
Machine Learning forAutomated Polyp Detectionin Computed TomographyColonography | 54 |
Variational ApproachBased Image PreProcessing Techniques forVirtual Colonoscopy | 78 |
Machine Learning for BrainImage Segmentation | 102 |
A Genetic AlgorithmBasedLevel Set Curve Evolution forProstate Segmentation onPelvic CT and MRI Images | 127 |
Genetic Adaptation of LevelSets Parameters for MedicalImaging Segmentation | 150 |
Assessment of Kidney FunctionUsing Dynamic ContrastEnhanced MRI Techniques | 214 |
Ensemble of Neural Networksfor Automated Cell PhenotypeImage Classification | 234 |
ContentBased Access toMedical Image Collections | 260 |
Predicting Complex Patternsof Human Movements UsingBayesian Online Learning inMedical Imaging Applications | 283 |
Left Ventricle Segmentation andMotion Analysis in MultiSliceComputerized Tomography | 307 |
Compilation of References | 323 |
About the Contributors | 357 |
| 365 | |
Automatic Analysis ofMicroscopic Images inHematological CytologyApplications | 167 |
Biomedical Microscopic ImageProcessing by Graphs | 197 |
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Biomedical Image Analysis and Machine Learning Technologies: Applications ... Fabio A. Gonzalez,Eduardo Romero No preview available - 2009 |
Common terms and phrases
algorithm analysis application approach associated automated automatic blood breast calculated cancer cell chapter classification collection colon color combination complex Computer Conference contour corresponding dataset defined deformable described detection distance distribution estimation et al evaluation example extraction false Figure filter Finally framework function given global graph human IEEE IEEE Transactions image analysis Image Processing image segmentation important initial interest International Journal kidney labels level set machine learning maps mass mean measures Medical Imaging methods motion networks Neural normal object obtained optimal parameters patterns performance pixels polyp position presented Press problem Proceedings proposed Recognition region representation represented retrieval samples Science segmentation selection semantic shape shows similar space spatial specific statistical step strategy structures surface task techniques texture tion University values vector Virtual Colonoscopy Vision visual