Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging

✍ Scribed by Kenji Suzuki,Yisong Chen (eds.)

• Publisher: Springer International Publishing
• Year: 2018
• Tongue: English
• Leaves: 397
• Series: Intelligent Systems Reference Library 140
• Edition: 1
• Category: Library

✦ Synopsis

This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world.

Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an “information overload” for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment.

Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field.

✦ Table of Contents

Front Matter ....Pages i-xxi
Front Matter ....Pages 1-1
Multi-modality Feature Learning in Diagnoses of Alzheimer’s Disease (Daoqiang Zhang, Chen Zu, Biao Jie, Tingting Ye)....Pages 3-30
A Comparative Study of Modern Machine Learning Approaches for Focal Lesion Detection and Classification in Medical Images: BoVW, CNN and MTANN (Nima Tajbakhsh, Kenji Suzuki)....Pages 31-58
Introduction to Binary Coordinate Ascent: New Insights into Efficient Feature Subset Selection for Machine Learning (Amin Zarshenas, Kenji Suzuki)....Pages 59-83
Front Matter ....Pages 85-85
Automated Lung Nodule Detection Using Positron Emission Tomography/Computed Tomography (Atsushi Teramoto, Hiroshi Fujita)....Pages 87-110
Detecting Mammographic Masses via Image Retrieval and Discriminative Learning (Menglin Jiang, Shaoting Zhang, Dimitris N. Metaxas)....Pages 111-132
Front Matter ....Pages 133-133
High-Order Statistics of Micro-Texton for HEp-2 Staining Pattern Classification (Xian-Hua Han, Yen-Wei Chen)....Pages 135-164
Intelligent Diagnosis of Breast Cancer Based on Quantitative B-Mode and Elastography Features (Chung-Ming Lo, Ruey-Feng Chang)....Pages 165-191
Categorization of Lung Tumors into Benign/Malignant, Solid/GGO, and Typical Benign/Others (Yasushi Hirano)....Pages 193-208
Fuzzy Object Growth Model for Neonatal Brain MR Understanding (Saadia Binte Alam, Syoji Kobashi, Jayaram K Udupa)....Pages 209-222
Front Matter ....Pages 223-223
Computer-Aided Prognosis: Accurate Prediction of Patients with Neurologic and Psychiatric Diseases via Multi-modal MRI Analysis (Huiguang He, Hongwei Wen, Dai Dai, Jieqiong Wang)....Pages 225-265
Radiomics in Medical Imaging—Detection, Extraction and Segmentation (Jie Tian, Di Dong, Zhenyu Liu, Yali Zang, Jingwei Wei, Jiangdian Song et al.)....Pages 267-333
Front Matter ....Pages 335-335
Markerless Tumor Gating and Tracking for Lung Cancer Radiotherapy based on Machine Learning Techniques (Tong Lin, Yucheng Lin)....Pages 337-359
Image Guided and Robot Assisted Precision Surgery (Fang Chen, Jia Liu, Hongen Liao)....Pages 361-387

✦ Subjects

Computational Intelligence