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Computer vision in medical imaging / / editor, C.H. Chen
| Computer vision in medical imaging / / editor, C.H. Chen |
| Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
| Descrizione fisica | 1 online resource (xiii, 393 pages) : illustrations (some color) |
| Disciplina | 006.37 |
| Collana | Series in computer vision |
| Soggetto topico |
Diagnostic imaging - Data processing
Computer vision in medicine |
| ISBN | 981-4460-94-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; CONTENTS; Chapter 1 An Introduction to Computer Vision in Medical Imaging Chi Hau Chen; 1. Introduction; 2. Some Medical Imaging Methods; 2.1. X-ray; 2.2. Magnetic Resonance Image (MRI); 2.3. Intravascular Ultrasound (IVUS); 3. Roles of Computer Vision, Image Processing and Pattern Recognition; 4. Active Contours; 4.1. Snakes; 4.2. Level set methods; 4.3. Geodesic active contours; 4.4. Region-based active contours; 4.5. Hybrid evolution method; 4.6. IVUS image segmentation; 5. Concluding Remarks; Acknowledgment; References; Part 1 Theory and Methodologies
Chapter 2 Distribution Matching Approaches to Medical Image Segmentation Ismail Ben Ayed1. Introduction; 2. Formulations; 3. Optimization Aspects; 3.1. Specialized optimizers; 3.2. Derivative-based optimizers; 3.2.1. Active curves and level sets; 3.2.2. Line search and trust region methods; 3.3. Bound optimizers; 3.3.1. Graph cuts; 3.3.2. Convex-relaxation techniques; 4. Medical Imaging Applications; 4.1. Left ventricle segmentation in cardiac images; 4.1.1. Example; 4.2. Vertebral-body segmentation in spine images; 4.2.1. Example; 4.3. Brain tumor segmentation; 5. Conclusion and Outlook ReferencesChapter 3 Digital Pathology in Medical Imaging Bikash Sabata, Chukka Srinivas, Pascal Bamford and Gerardo Fernandez; 1. Introduction; A. Subtyping and the role of digital pathology; B. Quantification of IHC markers; C. Tissue and stain variability; D. Rules-based segmentation and identification; E. Learning from image data examples; F. Object-based learning models; G. Membrane detection algorithms; H. HER2 Dual ISH slide scoring algorithm; 2. DP Enabled Applications; 3. Multiplexed Quantification; 4. Quantification Algorithms; 5. Summary; Acknowledgment; References Chapter 4 Adaptive Shape Prior Modeling via Online Dictionary Learning Shaoting Zhang, Yiqiang Zhan, Yan Zhou and Dimitris Metaxas1. Introduction; 2. Relevant Work; 3. Methodology; 3.1. Sparse Shape Composition; 3.2. Shape Dictionary Learning; 3.3. Online Shape Dictionary Update; 4. Experiments; 4.1. Lung Localization; 4.2. Real-time Left Ventricle Tracking; 5. Conclusions; References; Chapter 5 Feature-Centric Lesion Detection and Retrieval in Thoracic Images Yang Song, Weidong Cai, Stefan Eberl, Michael J Fulham and David Dagan Feng; 1. Lesion Detection; 1.1. Review of State-of-the-art 1.2. Region-based Feature Classification1.2.1. Region Type Identification; 1.2.2. Region Type Refinement; 1.2.3. 3D Object Localization; 1.3. Multi-stage Discriminative Model; 1.3.1. Abnormality Detection; 1.3.2. Tumor and Lymph Node Differentiation; 1.3.3. Tumor Region Refinement; 1.3.4. Experimental Results; 1.4. Data Adaptive Structure Estimation; 1.4.1. Initial Abnormality Detection; 1.4.2. Adaptive Structure Estimation; 1.4.3. Feature Extraction and Classification; 1.4.4. Experimental Results; 2. Thoracic Image Retrieval; 2.1. Review of State-of-the-art 2.2. Pathological Feature Description |
| Record Nr. | UNINA-9910790748003321 |
| New Jersey : , : World Scientific, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computer vision in medical imaging / / editor, C.H. Chen
| Computer vision in medical imaging / / editor, C.H. Chen |
| Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
| Descrizione fisica | 1 online resource (xiii, 393 pages) : illustrations (some color) |
| Disciplina | 006.37 |
| Collana | Series in computer vision |
| Soggetto topico |
Diagnostic imaging - Data processing
Computer vision in medicine |
| ISBN | 981-4460-94-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; CONTENTS; Chapter 1 An Introduction to Computer Vision in Medical Imaging Chi Hau Chen; 1. Introduction; 2. Some Medical Imaging Methods; 2.1. X-ray; 2.2. Magnetic Resonance Image (MRI); 2.3. Intravascular Ultrasound (IVUS); 3. Roles of Computer Vision, Image Processing and Pattern Recognition; 4. Active Contours; 4.1. Snakes; 4.2. Level set methods; 4.3. Geodesic active contours; 4.4. Region-based active contours; 4.5. Hybrid evolution method; 4.6. IVUS image segmentation; 5. Concluding Remarks; Acknowledgment; References; Part 1 Theory and Methodologies
Chapter 2 Distribution Matching Approaches to Medical Image Segmentation Ismail Ben Ayed1. Introduction; 2. Formulations; 3. Optimization Aspects; 3.1. Specialized optimizers; 3.2. Derivative-based optimizers; 3.2.1. Active curves and level sets; 3.2.2. Line search and trust region methods; 3.3. Bound optimizers; 3.3.1. Graph cuts; 3.3.2. Convex-relaxation techniques; 4. Medical Imaging Applications; 4.1. Left ventricle segmentation in cardiac images; 4.1.1. Example; 4.2. Vertebral-body segmentation in spine images; 4.2.1. Example; 4.3. Brain tumor segmentation; 5. Conclusion and Outlook ReferencesChapter 3 Digital Pathology in Medical Imaging Bikash Sabata, Chukka Srinivas, Pascal Bamford and Gerardo Fernandez; 1. Introduction; A. Subtyping and the role of digital pathology; B. Quantification of IHC markers; C. Tissue and stain variability; D. Rules-based segmentation and identification; E. Learning from image data examples; F. Object-based learning models; G. Membrane detection algorithms; H. HER2 Dual ISH slide scoring algorithm; 2. DP Enabled Applications; 3. Multiplexed Quantification; 4. Quantification Algorithms; 5. Summary; Acknowledgment; References Chapter 4 Adaptive Shape Prior Modeling via Online Dictionary Learning Shaoting Zhang, Yiqiang Zhan, Yan Zhou and Dimitris Metaxas1. Introduction; 2. Relevant Work; 3. Methodology; 3.1. Sparse Shape Composition; 3.2. Shape Dictionary Learning; 3.3. Online Shape Dictionary Update; 4. Experiments; 4.1. Lung Localization; 4.2. Real-time Left Ventricle Tracking; 5. Conclusions; References; Chapter 5 Feature-Centric Lesion Detection and Retrieval in Thoracic Images Yang Song, Weidong Cai, Stefan Eberl, Michael J Fulham and David Dagan Feng; 1. Lesion Detection; 1.1. Review of State-of-the-art 1.2. Region-based Feature Classification1.2.1. Region Type Identification; 1.2.2. Region Type Refinement; 1.2.3. 3D Object Localization; 1.3. Multi-stage Discriminative Model; 1.3.1. Abnormality Detection; 1.3.2. Tumor and Lymph Node Differentiation; 1.3.3. Tumor Region Refinement; 1.3.4. Experimental Results; 1.4. Data Adaptive Structure Estimation; 1.4.1. Initial Abnormality Detection; 1.4.2. Adaptive Structure Estimation; 1.4.3. Feature Extraction and Classification; 1.4.4. Experimental Results; 2. Thoracic Image Retrieval; 2.1. Review of State-of-the-art 2.2. Pathological Feature Description |
| Record Nr. | UNINA-9910825001503321 |
| New Jersey : , : World Scientific, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||