Conference Proceedings

Conference proceedings is available at https://link.springer.com/book/10.1007/978-3-030-20351-1

The details of the conference programme can be found at [here].

Sunday, 2 June 2019

15:00-21:00 Registration - Conference Lodge

19:00-21:00 Dinner Reception - China Garden Restaurant

  • - Meeting Points: 18:45, Conference Lodge Lobby

Monday, 3 June 2019

Breakfast - Conference Lodge

08:00-08:15 Opening Session - IAS

08:15-09:45 Segmentation

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

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

Coffee Break

10:30-12:00 Classification and Inference - IAS

  • Analyzing Brain Morphology on the Bag-of-Features Manifold

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

Lunch - China Garden Restaurant

14:00-15:30 Deep Learning I - IAS

  • InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction

  • Adaptive Graph Convolution Pooling for Brain Surface Analysis

Coffee Break

16:00-17:30 Reconstruction - IAS

  • Limited Angle Tomography Reconstruction: Synthetic Reconstruction via Unsupervised Sinogram Adaptation

  • Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences

Dinner - Conference Lodge

4
June

Tuesday, 4 June 2019

Breakfast - Conference Lodge

08:30-10:00 - IAS

  • Keynote by Xiaodong Tao, PhD, VP of iFlyTek, CEO of iFlyTek Healthcare

    • Title: Imaging AI in China, Challenges and Future

  • Disease Modeling

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

Coffee Break

10:30-12:00 Shape I - IAS

  • Minimizing Non-Holonomicity: Finding Sheets in Fibrous Structures

  • Learning Low-Dimensional Representations of Shape Data Sets with Diffeomorphic Autoencoders

12:15 IPMI 2019 Group Photo Taking - IAS Foyer

12:30-13:45 Lunch - China Garden Restaurant

14:00-16:00 Posters I - IAS

Coffee Break

16:30-18:00 Registration - IAS

  • Local Optimal Transport for Functional Brain Template Estimation

  • Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations

19:00-21:00 Dinner - Conference Lodge

Wednesday, 5 June 2019

Breakfast - Conference Lodge

08:30-10:00 Deep Learning and Segmentation - IAS

  • Semi-Supervised and Task-Driven Data Augmentation

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

Coffee Break

10:30-12:00 Deep Learning II - IAS

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

  • Improved Disease Classification in Chest X-rays with Transferred Features from Report Generation

Packed Lunch - IAS

13:00 Social Events (Choose one out of three)[Online registration has been closed]

  • - Meeting Point: IAS Lobby
  • Event 1:
    • The Peak Circle Hike + Stanley
  • Event 2:
    • Dragon's Back Hike
  • Event 3:
    • Boat Trip to Sharp Island + Nearby Islands

18:30-22:00 Banquet and 50th Anniversary Talk - Hong Kong Country Club

  • - Address: 188 Wong Chuk Hang Road, Deep Water Bay, Hong Kong

6
June

Thursday, 6 June 2019

Breakfast - Conference Lodge

08:30-10:00 Learning Motion - IAS

  • Real-Time 2D-3D Deformable Registration with Deep Learning and Application to Lung Radiotherapy Targeting

  • Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces

Coffee Break

10:30-12:00 Functional Imaging - IAS

  • Integrating Convolutional Neural Networks and Probabilistic Graphical Modeling for Epileptic Seizure Detection in Multichannel EEG

  • A Novel Sparse Overlapping Modularized Gaussian Graphical Model for Functional Connectivity Estimation

Lunch - Conference Lodge

13:00-15:00 Posters II - IAS

Coffee Break

15:30-18:00 Sporting Events - TST Sports Center / Soccer Field

  • - Meeting Point: 15:30, Conference Lodge Lobby

19L00-21:00 Dinner - Conference Lodge

Friday, 7 June 2019

Breakfast - Conference Lodge

08:30-10:00 White Matter Imaging - IAS

  • Asymmetry Spectrum Imaging for Baby Diffusion Tractography

  • A Fast Fiber K-Nearest-Neighbor Algorithm with Application to Group-wise White Matter Topography Analysis

Coffee Break

10:30-12:00 Shape II - IAS

  • Diffeomorphic Medial Modeling

  • Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing

12:00-13:00 Closing Session

Departure

End

Conference Proceedings

Conference proceedings is available at https://link.springer.com/book/10.1007/978-3-030-20351-1


Sunday, 2 June 2019:

 

15:00-21:00 Registration - Conference Lodge

19:00-21:00 Dinner Reception - China Garden Restaurant (Meeting Point: 18:45, Conference Lodge Lobby)

 

Monday, 3 June 2019:

 

Breakfast - Conference Lodge

08:00-08:15 Opening Session - IAS

08:15–09:45 Segmentation (Session Chair: Paul Yushkevich;  Study Group Chair: Juan Iglesias Gonzalez)

·       A Bayesian Neural Net to Segment Images with Uncertainty Estimates and Good Calibration - Rohit Jena and Suyash P. Awate [PDF]

·       Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology - James R. Clough, Ilkay Oksuz, Nicholas Byrne, Julia A. Schnabel, and Andrew P. King [PDF]

Coffee Break

10:30–12:00 Classification and Inference (Session Chair: Stefan Sommer;  Study Group Chair: Qingyu Zhao) - IAS

·       Analyzing Brain Morphology on the Bag-of-Features Manifold - Laurent Chauvin, Kuldeep Kumar, Christian Desrosiers, Jacques De Guise, William Wells III and Matthew Toews [PDF]

·       Modeling and Inference of Spatio-Temporal Protein Dynamics Across Brain Networks - Sara Garbarino and Marco Lorenzi [PDF]

12:30-13:45 Lunch - China Garden Restaurant

14:00–15:30 Deep Learning I (Session Chair: Baba Vemuri;  Study Group Chair: Sharon Huang) - IAS

·       InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction - Anees Kazi, Shayan Shekarforoush, S. Arvind krishna, Hendrik Burwinkel, Gerome Vivar, Karsten Korteüum, Seyed-Ahmad Ahmadi, Shadi Albarqouni, and Nassir Navab [PDF]

·       Adaptive Graph Convolution Pooling for Brain Surface Analysis - Karthik Gopinath, Christian Desrosiers, and Herve Lombaert [PDF]

Coffee Break

16:00–17:30 Reconstruction (Session Chair: Pengcheng Shi;  Study Group Chair: Huafeng Liu) - IAS

·       Limited Angle Tomography Reconstruction: Synthetic Reconstruction via Unsupervised Sinogram Adaptation - Bo Zhou, Xunyu Lin, and Brendan Eck [PDF]

·       Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences - Sandesh Ghimire, Prashnna Kumar Gyawali, Jwala Dhamala, John L. Sapp, Milan Horacek, and Linwei Wang [PDF]

19:00-21:00 Dinner - Conference Lodge

  

Tuesday, 4 June 2019:

 

Breakfast - Conference Lodge

08:30-10:00 - IAS

  • Keynote by Xiaodong Tao, PhD, VP of iFlyTek, CEO of iFlyTek Healthcare (Chairs: Dinggang Shen and Hao Chen)

·       Title: Imaging AI in China, Challenges and Future

  • Disease Modeling (Session Chair: Marco Lorenzi;  Study Group Chair: Chair: Stanley Durrleman)

·       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, and Stefan Klein [PDF]

Coffee Break

10:30–12:00 Shape I (Session Chair: Carl-Fredrik Westin;  Study Group Chair: Chair: Marc Niethammer) - IAS

·       Minimizing Non-Holonomicity: Finding Sheets in Fibrous Structures - Babak Samari, Tabish Syed, and Kaleem Siddiqi [PDF]

·       Learning Low-Dimensional Representations of Shape Data Sets with Diffeomorphic Autoencoders - Alexandre Bône, Maxime Louis, Olivier Colliot, Stanley Durrleman, and the Alzheimer’s Disease Neuroimaging Initiative [PDF]

12:15 IPMI 2019 Group Photo Taking - IAS Foyer

12:30-13:45 Lunch - China Garden Restaurant

14:00-16:00 Posters I - IAS

Coffee Break

16:30–18:00 Registration (Session Chair: Stefan Klein;  Study Group Chair: Chair: Julia Schnabel) - IAS

·       Local Optimal Transport for Functional Brain Template Estimation - T. Bazeille, H. Richard, H. Janati, B. Thirion [PDF]

·       Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations - Chen Qin, Bibo Shi, Rui Liao, Tommaso Mansi, Daniel Rueckert, and Ali Kamen [PDF]

19:00-21:00 Dinner - Conference Lodge

  

Wednesday, 5 June 2019:

 

Breakfast - Conference Lodge

08:30-10:00 Deep Learning & Segmentation (Session Chair: Suyash Awate; Study Group Chair: Alejandro Frangi) - IAS

·       Semi-Supervised and Task-Driven Data Augmentation - Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Anton Becker, Olivio Donati, Ender Konukoglu [PDF]

·       On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging - Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, and Vikas Singh [PDF]

Coffee Break

10:30–12:00 Deep Learning II (Session Chair: S. Kevin Zhou;  Study Group Chair: Ender Konukoglu) - IAS

·       A Deep Neural Network for Manifold-Valued Data with Applications to Neuroimaging - Rudrasis Chakraborty, Jose Bouza, Jonathan Manton, and Baba C. Vemuri [PDF]

·       Improved Disease Classification in Chest X-rays with Transferred Features from Report Generation - Yuan Xue, and Xiaolei Huang [PDF]

Packed Lunch - IAS

13:00 Social Event (Choose one out of three) [Online registration has been closed]

(Meeting Point: IAS Lobby)

·       The Peak Circle Hike + Stanley

·       Dragon's Back Hike

·       Boat Trip to Sharp Island + Nearby Islands

18:30-22:00 Banquet and 50th Anniversary Talk - Hong Kong Country Club

(Address: 188 Wong Chuk Hang Road, Deep Water Bay, Hong Kong)

  

Thursday, 6 June 2019:

 

Breakfast - Conference Lodge

08:30-10:00 Learning Motion (Session Chair: Linwei Wang;  Study Group Chair: Kaleem Siddiqi) - IAS

·       Real-Time 2D-3D Deformable Registration with Deep Learning and Application to Lung Radiotherapy Targeting - Markus D. Foote, Blake E. Zimmerman, Amit Sawant, and Sarang C. Joshi [PDF]

·       Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces - Peirong Liu, Zhengwang Wu, Gang Li, Pew-Thian Yap, and Dinggang Shen [PDF]

Coffee Break

10:30–12:00 Functional Imaging (Session Chair: Bernard Ng;  Study Group Chair: Matthew Toews) - IAS

·       Integrating Convolutional Neural Networks and Probabilistic Graphical Modeling for Epileptic Seizure Detection in Multichannel EEG - Jeff Craley, Emily Johnson, and Archana Venkataraman [PDF]

·       A Novel Sparse Overlapping Modularized Gaussian Graphical Model for Functional Connectivity Estimation - Zhiyuan Zhu, Zonglei Zhen, and Xia Wu [PDF]

Lunch - Conference Lodge

13:00-15:00 Posters II - IAS

Coffee Break

15:30-18:00 Sporting Events - TST Sports Center / Soccer Field 

(Meeting Point: 15:30, Conference Lodge Lobby)

19:00-21:00 Dinner - Conference Lodge

  

Friday, 7 June 2019:

 

Breakfast - Conference Lodge

08:30-10:00 White Matter Imaging (Session Chair: Gary Hui Zhang;  Study Group Chair: Archana Venkataraman) - IAS

·       Asymmetry Spectrum Imaging for Baby Diffusion Tractography - Ye Wu, Weili Lin, Dinggang Shen, Pew-Thian Yap, and the UNC/UMN Baby Connectome Project Consortium [PDF]

·       A Fast Fiber K-Nearest-Neighbor Algorithm with Application to Group-Wise White Matter Topography Analysis - Junyan Wang and Yonggang Shi [PDF]

Coffee Break

10:30–12:00 Shape II (Session Chair: Herve Lombaert;  Study Group Chair: Guido Gerig) - IAS

·       Diffeomorphic Medial Modeling - Paul A. Yushkevich, Ahmed Aly, Jiancong Wang, Long Xie, Robert C. Gorman, Laurent Younes, Alison M. Pouch [PDF]

·       Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing - Loïc Le Folgoc, Daniel C. Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, and Ben Glocker [PDF]

12:00-13:00 Closing Session

Departure

  


Posters I

·       1. 3D Organ Shape Reconstruction from Topogram Images - Elena Balashova, Jiangping Wang, Vivek Singh, Bogdan Georgescu, Brian Teixeira, and Ankur Kapoor [PDF]

·       2. A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation - Wouter M. Kouw, Silas N. Ørting, Jens Petersen, Kim S. Pedersen, and Marleen de Bruijne [PDF]

·       3. A Graph Model of the Lungs with Morphology–Based Structure for Tuberculosis Type Classification - Dicente Cid, Oscar Jiménez-del-Toro, Pierre-Alexandre Poletti, and Henning Müller [PDF]

·       4. A Longitudinal Model for Tau Aggregation in Alzheimer’s Disease Based on Structural Connectivity - Fan Yang, Samadrita Roy Chowdhury, Heidi I. L. Jacobs, Keith A. Johnson, and Joyita Dutta [PDF]

·       5. Accurate Nuclear Segmentation with Center Vector Encoding - Jiahui Li, Zhiqiang Hu, and Shuang Yang [PDF]

·       6. Bayesian Longitudinal Modeling of Early Stage Parkinson’s Disease Using DaTscan Images - Yuan Zhou, and Hemant D. Tagare [PDF]

·       7. Brain Tumor Segmentation on MRI with Missing Modalities - Yan Shen, and Mingchen Gao [PDF]

·       8. CIA-Net: Robust Nuclei Instance Segmentation with Contour-Aware Information Aggregation - Yanning Zhou, Omer Fahri Onder, Qi Dou, Efstratios Tsougenis, Hao Chen and Pheng-Ann Heng [PDF]

·       9. Contextual Fibre Growth to Generate Realistic Axonal Packing for Diffusion MRI Simulation - Ross Callaghan, Daniel Alexander, Hui Zhang, and Marco Palombo [PDF]

·       10. DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction - Zhihui Guo, Junjie Bai, Yi Lu, Xin Wang, Kunlin Cao, Qi Song, Milan Sonka, and Youbing Yin [PDF]

·       11. ECKO: Ensemble of Clustered Knockoffs for Robust Multivariate Inference on fMRI Data - Tuan-Binh Nguyen, Jérôme-Alexis Chevalier, and Bertrand Thirion [PDF]

·       12. Graph Convolutional Nets for Tool Presence Detection in Surgical Videos - Sheng Wang, Zheng Xu, Chaochao Yan, and Junzhou Huang [PDF]

·       13. High-Order Oriented Cylindrical Flux for Curvilinear Structure Detection and Vessel Segmentation - Jierong Wang, and Albert C. S. Chung [PDF]

·       14. Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network - Liyan Sun, Zhiwen Fan, Xinghao Ding, Yue Huang, and John Paisley [PDF]

·       15. Manifold Exploring Data Augmentation with Geometric Transformations for Increased Performance and Robustness - Magdalini Paschali, Walter Simson, Abhijit Guha Roy, Rüdiger Göbl, Christian Wachinger, and Nassir Navab [PDF]

·       16. Multifold Acceleration of Diffusion MRI via Deep Learning Reconstruction from Slice-Undersampled Data - Yoonmi Hong, Geng Chen, Pew-Thian Yap, and Dinggang Shen [PDF]

·       17. Riemannian Geometry Learning for Disease Progression Modelling - Maxime Louis, Raphaël Couronné, Igor Koval, Benjamin Charlier, and Stanley Durrleman [PDF]

·       18. Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model - Wenhui Cui, Yanlin Liu, Yuxing Li, Menghao Guo, Yiming Li, Xiuli Li, Tianle Wang, Xiangzhu Zeng, and Chuyang Ye [PDF]

·       19. Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices with Applications to Neuroimaging - Chun-Hao Yang, and Baba C. Vemuri [PDF]

·       20. Simultaneous Spatial-temporal Decomposition of Connectome-Scale Brain Networks by Deep Sparse Recurrent Auto-Encoders - Qing Li, Qinglin Dong, Fangfei Ge, Ning Qiang, Yu Zhao, Han Wang, Heng Huang, Xia Wu, and Tianming Liu [PDF]

·       21. Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention - Richard Droste, Yifan Cai, Harshita Sharma, Pierre Chatelain, Lior Drukker, Aris T. Papageorghiou, and J. Alison Noble [PDF]

Posters II

·       1. A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces - Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas Wymbs, Stewart Mostofsky, and Archana Venkataraman [PDF]

·       2. A Geometric Framework for Feature Mappings in Multimodal Fusion of Brain Image Data - Wen Zhang, Liang Mi, Paul M. Thompson, and Yalin Wang [PDF]

·       3. A Hierarchical Manifold Learning Framework for High-Dimensional Neuroimaging Data - Siyuan Gao, Gal Mishne, and Dustin Scheinost [PDF]

·       4. A Model for Elastic Evolution on Foliated Shapes - Dai-Ni Hsieh, Sylvain Arguillère, Nicolas Charon, Michael I. Miller, and Laurent Younes [PDF]

·       5. Analyzing Mild Cognitive Impairment Progression via Multi-view Structural Learning - Li Wang, Paul M. Thompson, and Dajiang Zhu [PDF]

·       6. New Graph-Blind Convolutional Network for Brain Connectome Data Analysis - Yanfu Zhan, and Heng Huang [PDF]

·       7. Data-Driven Model Order Reduction For Diffeomorphic Image Registration - Jian Wang, Wei Xing, Robert M. Kirby, and Miaomiao Zhang [PDF]

·       8. DGR-Net: Deep Groupwise Registration of Multispectral Images - Tongtong Che, Yuanjie Zheng, Xiaodan Sui, Yanyun Jiang, Jinyu Cong, Wanzhen Jiao, and Bojun Zhao [PDF]

·       9. Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery - Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, and James S. Duncan [PDF]

·       10. Generalizations of Ripley’s K-Function with Application to Space Curves - Jon Sporring, Rasmus Waagepetersen, and Stefan Sommer [PDF]

·       11. Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates - H. Janati, T. Bazeille, B. Thirion, M. Cuturi, and A. Gramfort [PDF]

·       12. InSpect: INtegrated SPECTral Component Estimation and Mapping for Multi-Contrast Microstructural MRI - Paddy J. Slator, Jana Hutter, Razvan V. Marinescu, Marco Palombo, Alexandra L. Young, Laurence H. Jackson, Alison Ho, Lucy C. Chappell, Mary Rutherford, Joseph V. Hajnal, and Daniel C. Alexander [PDF]

·       13. Joint Inference on Structural and Diffusion MRI for Sequence-Adaptive Bayesian Segmentation of Thalamic Nuclei with Probabilistic Atlases - Juan Eugenio Iglesias, Koen Van Leemput, Polina Golland, and Anastasia Yendiki [PDF]

·       14. Learning a Conditional Generative Model for Anatomical Shape Analysis - Benjamín Gutiérrez-Becker, and Christian Wachinger [PDF]

·       15. Learning-Based Optimization of the Under-Sampling Pattern in MRI - Cagla Deniz Bahadir, Adrian V. Dalca, and Mert R. Sabuncu [PDF]

·       16. Melanoma Recognition via Visual Attention - Yiqi Yan, Jeremy Kawahara, and Ghassan Hamarneh [PDF]

·       17. Nonlinear Markov Random Fields Learned via Backpropagation - Mikael Brudfors, Yaël Balbastre, and John Ashburner [PDF]

·       18. Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler - Thomas Yu, Marco Pizzolato, Gabriel Girard, Jonathan Rafael-Patino, Erick Jorge Canales-Rodríguez, and Jean-Philippe Thiran [PDF]

·       19. SHAMANN: Shared Memory Augmented Neural Networks - Cosmin I. Bercea, Olivier Pauly, Andreas Maier, and Florin C. Ghesu [PDF]

·       20. Signet Ring Cell Detection With a Semi-supervised Learning Framework - Jiahui Li, Shuang Yang, Xiaodi Huang, Qian Da, Xiaoqun Yang, Zhiqiang Hu, Qi Duan, Chaofu Wang, and Hongsheng Li [PDF]

·       21. Spherical U-Net on Cortical Surfaces: Methods and Applications - Fenqiang Zhao, Shunren Xia, Zhengwang Wu, Dingna Duan, Li Wang, Weili Lin, John H Gilmore, Dinggang Shen, and Gang Li [PDF]

·       22. Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis - Qingyu Zhao, Nicolas Honnorat, Ehsan Adeli, Adolf Pfefferbaum, Edith V. Sullivan, and Kilian M. Pohl [PDF]