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Author:   Kenji Suzuki
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 2014
Weight:   7.151kg
ISBN:  

9781493942336

ISBN 10:   1493942336
Pages:   406
Publication Date:   23 August 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Brain Disease Classification and Progression using Machine Learning Techniques.- The Role of Content-Based Image Retrieval in Mammography CAD.- A Novel Image-based Approach for Early Detection of Prostate Cancer using DCE-MRI.- Computational Intelligent Image Analysis for Assisting Radiation Oncologists’ Decision Making in Radiation Treatment Planning.- Computational Anatomy in the Abdomen: Automated Multi-Organ and Tumor Analysis from Computed Tomography.- Liver Volumetry in MRI by using Fast Marching Algorithm Coupled with 3D Geodesic Active Contour Segmentation.- Computer-aided Image Analysis for Vertebral Anatomy on X-ray CT Images.- Robust Segmentation of Challenging Lungs in CT using Multi-Stage Learning and Level Set Optimization.- Bone Suppression in Chest Radiographs by Means of Anatomically Specific Multiple Massive-Training ANNs Combined with Total Variation Minimization Smoothing and Consistency Processing.- Image Segmentation for Connectomics using Machine Learning.- Image Analysis Techniques for the Quantification of Brain Tumors on MR Images.- Respiratory and Cardiac Function Analysis on the Basis of Dynamic Chest Radiography.- Adaptive Noise Reduction and Edge Enhancement in Medical Images by using ICA.- Subtraction Techniques for CT and DSA and Automated Detection of Lung Nodules in 3D CT.

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Author Information

Dr. Kenji Suzuki is an Assistant Professor of Radiology at the University of Chicago. He has written over 240 papers including 95 peer-reviewed journal papers. Dr. Suzuki received his PhD in Engineering in 2001. His research interests include computer-aided diagnosis of lesions in the abdomen, thorax, and heart, medical image analysis and machine learning in medical imaging.

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