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Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging

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Cover of 'Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Multi-modality Feature Learning in Diagnoses of Alzheimer’s Disease
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    Chapter 2 A Comparative Study of Modern Machine Learning Approaches for Focal Lesion Detection and Classification in Medical Images: BoVW, CNN and MTANN
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    Chapter 3 Introduction to Binary Coordinate Ascent: New Insights into Efficient Feature Subset Selection for Machine Learning
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    Chapter 4 Automated Lung Nodule Detection Using Positron Emission Tomography/Computed Tomography
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    Chapter 5 Detecting Mammographic Masses via Image Retrieval and Discriminative Learning
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    Chapter 6 High-Order Statistics of Micro-Texton for HEp-2 Staining Pattern Classification
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    Chapter 7 Intelligent Diagnosis of Breast Cancer Based on Quantitative B-Mode and Elastography Features
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    Chapter 8 Categorization of Lung Tumors into Benign/Malignant, Solid/GGO, and Typical Benign/Others
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    Chapter 9 Fuzzy Object Growth Model for Neonatal Brain MR Understanding
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    Chapter 10 Computer-Aided Prognosis: Accurate Prediction of Patients with Neurologic and Psychiatric Diseases via Multi-modal MRI Analysis
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    Chapter 11 Radiomics in Medical Imaging—Detection, Extraction and Segmentation
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    Chapter 12 Markerless Tumor Gating and Tracking for Lung Cancer Radiotherapy based on Machine Learning Techniques
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    Chapter 13 Image Guided and Robot Assisted Precision Surgery
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