Information Processing in Medical Imaging

1. Front Matter

   Pages i-xix

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2. Segmentation

   1. Front Matter

      Pages 1-1

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   2. A Bayesian Neural Net to Segment Images with Uncertainty Estimates and Good Calibration

      • Rohit Jena, Suyash P. Awate

      Pages 3-15

   3. Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology

      • James R. Clough, Ilkay Oksuz, Nicholas Byrne, Julia A. Schnabel, Andrew P. King

      Pages 16-28

   4. Semi-supervised and Task-Driven Data Augmentation

      • Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Anton Becker, Olivio Donati, Ender Konukoglu

      Pages 29-41

3. Classification and Inference

   1. Front Matter

      Pages 43-43

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   2. Analyzing Brain Morphology on the Bag-of-Features Manifold

      • Laurent Chauvin, Kuldeep Kumar, Christian Desrosiers, Jacques De Guise, William Wells III, Matthew Toews

      Pages 45-56

   3. Modeling and Inference of Spatio-Temporal Protein Dynamics Across Brain Networks

      • Sara Garbarino, Marco Lorenzi, for the Alzheimer’s Disease Neuroimaging Initiative

      Pages 57-69

4. Deep Learning

   1. Front Matter

      Pages 71-71

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   2. InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction

      • Anees Kazi, Shayan Shekarforoush, S. Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Karsten Kortüm et al.

      Pages 73-85

   3. Adaptive Graph Convolution Pooling for Brain Surface Analysis

      • Karthik Gopinath, Christian Desrosiers, Herve Lombaert

      Pages 86-98

   4. On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging

      • Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, Vikas Singh

      Pages 99-111

   5. A Deep Neural Network for Manifold-Valued Data with Applications to Neuroimaging

      • Rudrasis Chakraborty, Jose Bouza, Jonathan Manton, Baba C. Vemuri

      Pages 112-124

   6. Improved Disease Classification in Chest X-Rays with Transferred Features from Report Generation

      • Yuan Xue, Xiaolei Huang

      Pages 125-138

5. Reconstruction

   1. Front Matter

      Pages 139-139

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   2. Limited Angle Tomography Reconstruction: Synthetic Reconstruction via Unsupervised Sinogram Adaptation

      • Bo Zhou, Xunyu Lin, Brendan Eck

      Pages 141-152

   3. Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences

      • Sandesh Ghimire, Prashnna Kumar Gyawali, Jwala Dhamala, John L. Sapp, Milan Horacek, Linwei Wang

      Pages 153-166

6. Disease Modeling

   1. Front Matter

      Pages 167-167

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   2. Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia

      • Vikram Venkatraghavan, Florian Dubost, Esther E. Bron, Wiro J. Niessen, Marleen de Bruijne, Stefan Klein et al.

      Pages 169-180

7. Shape

   1. Front Matter

      Pages 181-181

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This book constitutes the proceedings of the 26th International Conference on Information Processing in Medical Imaging, IPMI 2019, held at the Hong Kong University of Science and Technology, Hong Kong, China, in June 2019.

The 69 full papers presented in this volume were carefully reviewed and selected from 229 submissions. They were organized in topical sections on deep learning and segmentation; classification and inference; reconstruction; disease modeling; shape, registration; learning motion; functional imaging; and white matter imaging. The book also includes a number of post papers. 

• artificial intelligence
• bayesian networks
• classification
• computer vision
• estimation
• image analysis
• image coding
• image reconstruction
• image segmentation
• imaging systems
• learning algorithms
• medical images
• medical imaging
• neural networks
• principal component analysis
• probability
• reconstruction
• semantics
• signal processing
• Support Vector Machines (SVM)

• Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China

  Albert C. S. Chung

• Department of Radiology, University of Pennsylvania, Philadelphia, USA

  James C. Gee, Paul A. Yushkevich

• Department of Natural Language Processing, Baidu Inc., Shenzhen, China

  Siqi Bao

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