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ORCID25. IPMI 2017: Boone, NC, USA
- Marc Niethammer, Martin Styner, Stephen R. Aylward, Hongtu Zhu, Ipek Oguz, Pew-Thian Yap, Dinggang Shen:
Information Processing in Medical Imaging - 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings. Lecture Notes in Computer Science 10265, Springer 2017, ISBN 978-3-319-59049-3
Analysis on Manifolds
- Monami Banerjee, Bing Jian, Baba C. Vemuri:
Robust Fréchet Mean and PGA on Riemannian Manifolds with Applications to Neuroimaging. 3-15 - Loïc Devilliers, Xavier Pennec
, Stéphanie Allassonnière:
Inconsistency of Template Estimation with the Fréchet Mean in Quotient Space. 16-27 - Suyash P. Awate, Richard M. Leahy, Anand A. Joshi:
Kernel Methods for Riemannian Analysis of Robust Descriptors of the Cerebral Cortex. 28-40 - Wenliang Pan, Xueqin Wang, Canhong Wen, Martin Styner, Hongtu Zhu:
Conditional Local Distance Correlation for Manifold-Valued Data. 41-52 - Line Kühnel, Stefan Sommer:
Stochastic Development Regression on Non-linear Manifolds. 53-64
Shape Analysis
- Loïc Le Folgoc, Aditya V. Nori, Antonio Criminisi:
Spectral Kernels for Probabilistic Analysis and Clustering of Shapes. 67-79 - Pengxiang Wu, Chao Chen, Yusu Wang, Shaoting Zhang, Changhe Yuan, Zhen Qian, Dimitris N. Metaxas, Leon Axel:
Optimal Topological Cycles and Their Application in Cardiac Trabeculae Restoration. 80-92 - Shireen Y. Elhabian, Ross T. Whitaker:
From Label Maps to Generative Shape Models: A Variational Bayesian Learning Approach. 93-105 - Christoph D. Hofer, Roland Kwitt, Marc Niethammer, Yvonne Höller, Eugen Trinka, Andreas Uhl:
Constructing Shape Spaces from a Topological Perspective. 106-118
Disease Diagnosis/Progression
- Vikram Venkatraghavan, Esther E. Bron, Wiro J. Niessen, Stefan Klein:
A Discriminative Event Based Model for Alzheimer's Disease Progression Modeling. 121-133 - Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi, Alexandra L. Young, Neil P. Oxtoby, Sara Garbarino, Timothy J. Shakespeare, Sebastian J. Crutch, Daniel C. Alexander:
A Vertex Clustering Model for Disease Progression: Application to Cortical Thickness Images. 134-145 - Thomas Schlegl, Philipp Seeböck, Sebastian M. Waldstein, Ursula Schmidt-Erfurth, Georg Langs:
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery. 146-157 - Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Daniel Kaufer, Guorong Wu:
A Novel Dynamic Hyper-graph Inference Framework for Computer Assisted Diagnosis of Neuro-Diseases. 158-169 - Jenna Schabdach, William M. Wells III, Michael H. Cho, Kayhan N. Batmanghelich:
A Likelihood-Free Approach for Characterizing Heterogeneous Diseases in Large-Scale Studies. 170-183 - Jie Zhang, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang:
Multi-source Multi-target Dictionary Learning for Prediction of Cognitive Decline. 184-197 - Xiaoqian Wang, Kefei Liu, Jingwen Yan, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Heng Huang:
Predicting Interrelated Alzheimer's Disease Outcomes via New Self-learned Structured Low-Rank Model. 198-209 - Qiang Zhang, Abhir Bhalerao, Charles Hutchinson:
Weakly-Supervised Evidence Pinpointing and Description. 210-222 - Jwala Dhamala, John L. Sapp, Milan Horacek, Linwei Wang:
Quantifying the Uncertainty in Model Parameters Using Gaussian Process-Based Markov Chain Monte Carlo: An Application to Cardiac Electrophysiological Models. 223-235 - Bin Kong, Xin Wang, Zhongyu Li, Qi Song, Shaoting Zhang:
Cancer Metastasis Detection via Spatially Structured Deep Network. 236-248 - Sarfaraz Hussein, Kunlin Cao, Qi Song, Ulas Bagci:
Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning. 249-260
Brain Networks and Connectivity
- Junyan Wang, Dogu Baran Aydogan, Rohit Varma, Arthur W. Toga, Yonggang Shi:
Topographic Regularity for Tract Filtering in Brain Connectivity. 263-274 - Nicolas Honnorat, Christos Davatzikos:
Riccati-Regularized Precision Matrices for Neuroimaging. 275-286 - Chendi Wang, Bernard Ng, Rafeef Abugharbieh:
Multimodal Brain Subnetwork Extraction Using Provincial Hub Guided Random Walks. 287-298 - Moo K. Chung, Victoria Villalta-Gil, Hyekyoung Lee, Paul J. Rathouz, Benjamin B. Lahey, David H. Zald:
Exact Topological Inference for Paired Brain Networks via Persistent Homology. 299-310 - Ernst Schwartz, Karl-Heinz Nenning, Gregor Kasprian, Anna-Lisa Schuler, Lisa Bartha-Doering, Georg Langs:
Multivariate Manifold Modelling of Functional Connectivity in Developing Language Networks. 311-322 - Danilo Bzdok, Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion:
Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging. 323-335 - Daniel Moyer, Boris A. Gutman, Neda Jahanshad, Paul M. Thompson:
A Restaurant Process Mixture Model for Connectivity Based Parcellation of the Cortex. 336-347 - Wenqi Li, Guotai Wang, Lucas Fidon, Sébastien Ourselin, M. Jorge Cardoso, Tom Vercauteren:
On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task. 348-360 - Mengyu Dai, Zhengwu Zhang, Anuj Srivastava:
Discovering Change-Point Patterns in Dynamic Functional Brain Connectivity of a Population. 361-372 - Nahuel Lascano, Guillermo Gallardo-Diez, Rachid Deriche, Dorian Mazauric, Demian Wassermann:
Extracting the Groupwise Core Structural Connectivity Network: Bridging Statistical and Graph-Theoretical Approaches. 373-384 - Islem Rekik, Gang Li, Weili Lin, Dinggang Shen:
Estimation of Brain Network Atlases Using Diffusive-Shrinking Graphs: Application to Developing Brains. 385-397 - Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Guorong Wu:
A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity. 398-410 - Heng Huang, Xintao Hu, Milad Makkie, Qinglin Dong, Yu Zhao, Junwei Han, Lei Guo, Tianming Liu:
Modeling Task fMRI Data via Deep Convolutional Autoencoder. 411-424
Diffusion Imaging
- Jian Cheng, Peter J. Basser:
Director Field Analysis to Explore Local White Matter Geometric Structure in Diffusion MRI. 427-439 - Benoit Scherrer, Maxime Taquet, Armin Schwartzman, Etienne St-Onge, Gaëtan Rensonnet, Sanjay P. Prabhu, Simon K. Warfield:
Decoupling Axial and Radial Tissue Heterogeneity in Diffusion Compartment Imaging. 440-452 - Kratika Gupta, Suyash P. Awate:
Bayesian Dictionary Learning and Undersampled Multishell HARDI Reconstruction. 453-465 - Chuyang Ye:
Estimation of Tissue Microstructure Using a Deep Network Inspired by a Sparse Reconstruction Framework. 466-477 - Jingwen Zhang, Chao Huang, Joseph G. Ibrahim, Shaili Jha, Rebecca C. Knickmeyer, John H. Gilmore, Martin Styner, Hongtu Zhu:
HFPRM: Hierarchical Functional Principal Regression Model for Diffusion Tensor Image Bundle Statistics. 478-489
Quantitative Imaging
- Qingyu Zhao, Stephen M. Pizer, Ron Alterovitz, Marc Niethammer, Julian G. Rosenman:
Orthotropic Thin Shell Elasticity Estimation for Surface Registration. 493-504 - Wufeng Xue, Ilanit Ben Nachum, Sachin Pandey, James Warrington, Stephanie Leung, Shuo Li:
Direct Estimation of Regional Wall Thicknesses via Residual Recurrent Neural Network. 505-516 - Hamid Fehri, Ali Gooya, Simon A. Johnston, Alejandro F. Frangi:
Multi-class Image Segmentation in Fluorescence Microscopy Using Polytrees. 517-528 - Haoliang Sun, Xiantong Zhen, Chris Bailey, Parham Rasoulinejad, Yilong Yin, Shuo Li:
Direct Estimation of Spinal Cobb Angles by Structured Multi-output Regression. 529-540
Imaging Genomics
- Lei Du, Tuo Zhang, Kefei Liu, Jingwen Yan, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Junwei Han, Lei Guo, Li Shen:
Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via a Novel Structured SCCA Approach. 543-555
Image Registration
- Miaomiao Zhang, Ruizhi Liao, Adrian V. Dalca, Esra Abaci Turk, Jie Luo, Patricia Ellen Grant, Polina Golland:
Frequency Diffeomorphisms for Efficient Image Registration. 559-570 - Alexis Arnaudon, Darryl D. Holm, Akshay Pai, Stefan Sommer:
A Stochastic Large Deformation Model for Computational Anatomy. 571-582 - Greg M. Fleishman, P. Thomas Fletcher, Paul M. Thompson:
Symmetric Interleaved Geodesic Shooting in Diffeomorphisms. 583-593
Segmentation
- Konstantinos Kamnitsas, Christian F. Baumgartner, Christian Ledig, Virginia F. J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
Unsupervised Domain Adaptation in Brain Lesion Segmentation with Adversarial Networks. 597-609 - Juan Eugenio Iglesias:
Globally Optimal Coupled Surfaces for Semi-automatic Segmentation of Medical Images. 610-621 - Hariharan Ravishankar, Sheshadri Thiruvenkadam, Rahul Venkataramani, Vivek Vaidya:
Joint Deep Learning of Foreground, Background and Shape for Robust Contextual Segmentation. 622-632 - Dong Yang, Tao Xiong, Daguang Xu, Qiangui Huang, David Liu, Shaohua Kevin Zhou, Zhoubing Xu, Jin Hyeong Park, Mingqing Chen, Trac D. Tran, Sang Peter Chin, Dimitris N. Metaxas, Dorin Comaniciu:
Automatic Vertebra Labeling in Large-Scale 3D CT Using Deep Image-to-Image Network with Message Passing and Sparsity Regularization. 633-644
General Image Analysis
- Jo Schlemper, Jose Caballero, Joseph V. Hajnal, Anthony N. Price, Daniel Rueckert:
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction. 647-658 - Adrian V. Dalca, Katherine L. Bouman, William T. Freeman, Natalia S. Rost, Mert R. Sabuncu, Polina Golland:
Population Based Image Imputation. 659-671 - Stefano Moriconi, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
VTrails: Inferring Vessels with Geodesic Connectivity Trees. 672-684
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