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21st MICCAI 2018: Granada, Spain
- Alejandro F. Frangi, Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 - 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part I. Lecture Notes in Computer Science 11070, Springer 2018, ISBN 978-3-030-00927-4
Image Quality and Artefacts
- Jianing Wang, Yiyuan Zhao, Jack H. Noble, Benoit M. Dawant:
Conditional Generative Adversarial Networks for Metal Artifact Reduction in CT Images of the Ear. 3-11 - Peng Liu, Yangjunyi Li, Mohammad D. El Basha, Ruogu Fang:
Neural Network Evolution Using Expedited Genetic Algorithm for Medical Image Denoising. 12-20 - David Owen, Andrew Melbourne, Zach Eaton-Rosen, David L. Thomas, Neil Marlow, Jonathan D. Rohrer, Sébastien Ourselin:
Deep Convolutional Filtering for Spatio-Temporal Denoising and Artifact Removal in Arterial Spin Labelling MRI. 21-29 - Cagdas Ulas, Giles Tetteh, Stephan Kaczmarz, Christine Preibisch, Bjoern H. Menze:
DeepASL: Kinetic Model Incorporated Loss for Denoising Arterial Spin Labeled MRI via Deep Residual Learning. 30-38 - Cagdas Ulas, Giles Tetteh, Michael J. Thrippleton, Paul A. Armitage, Stephen D. Makin, Joanna M. Wardlaw, Mike E. Davies, Bjoern H. Menze:
Direct Estimation of Pharmacokinetic Parameters from DCE-MRI Using Deep CNN with Forward Physical Model Loss. 39-47 - Catherine J. Scott, Jieqing Jiao, M. Jorge Cardoso, Kerstin Kläser, Andrew Melbourne, Pawel J. Markiewicz, Jonathan M. Schott, Brian F. Hutton, Sébastien Ourselin:
Short Acquisition Time PET/MR Pharmacokinetic Modelling Using CNNs. 48-56 - Saeed Izadi, Kathleen P. Moriarty, Ghassan Hamarneh:
Can Deep Learning Relax Endomicroscopy Hardware Miniaturization Requirements? 57-64 - Amir Fazlollahi, Scott Ayton, Pierrick Bourgeat, Ibrahima Diouf, Parnesh Raniga, Jurgen Fripp, James Doecke, David Ames, Colin L. Masters, Christopher C. Rowe, Victor L. Villemagne, Ashley I. Bush, Olivier Salvado:
A Framework to Objectively Identify Reference Regions for Normalizing Quantitative Imaging. 65-72 - Hongxiang Lin, Takashi Azuma, Mehmet Burcin Unlu, Shu Takagi:
Evaluation of Adjoint Methods in Photoacoustic Tomography with Under-Sampled Sensors. 73-81 - Adrian Galdran, Pedro Costa, Alessandro Bria, Teresa Araújo, Ana Maria Mendonça, Aurélio Campilho:
A No-Reference Quality Metric for Retinal Vessel Tree Segmentation. 82-90 - Yuhua Chen, Feng Shi, Anthony G. Christodoulou, Yibin Xie, Zhengwei Zhou, Debiao Li:
Efficient and Accurate MRI Super-Resolution Using a Generative Adversarial Network and 3D Multi-level Densely Connected Network. 91-99 - Can Zhao, Aaron Carass, Blake E. Dewey, Jonghye Woo, Jiwon Oh, Peter A. Calabresi, Daniel S. Reich, Pascal Sati, Dzung L. Pham, Jerry L. Prince:
A Deep Learning Based Anti-aliasing Self Super-Resolution Algorithm for MRI. 100-108 - Prabhjot Kaur, Anil Kumar Sao:
Gradient Profile Based Super Resolution of MR Images with Induced Sparsity. 109-117 - Stefano B. Blumberg, Ryutaro Tanno, Iasonas Kokkinos, Daniel C. Alexander:
Deeper Image Quality Transfer: Training Low-Memory Neural Networks for 3D Images. 118-125 - Ortal Senouf, Sanketh Vedula, Grigoriy Zurakhov, Alexander M. Bronstein, Michael Zibulevsky, Oleg V. Michailovich, Dan Adam, David Blondheim:
High Frame-Rate Cardiac Ultrasound Imaging with Deep Learning. 126-134
Image Reconstruction Methods
- Lina Felsner, Martin Berger, Sebastian Kaeppler, Johannes Bopp, Veronika Ludwig, Thomas Weber, Georg Pelzer, Thilo Michel, Andreas K. Maier, Gisela Anton, Christian Riess:
Phase-Sensitive Region-of-Interest Computed Tomography. 137-144 - Yixing Huang, Tobias Würfl, Katharina Breininger, Ling Liu, Günter Lauritsch, Andreas K. Maier:
Some Investigations on Robustness of Deep Learning in Limited Angle Tomography. 145-153 - Haofu Liao, Zhimin Huo, William J. Sehnert, Shaohua Kevin Zhou, Jiebo Luo:
Adversarial Sparse-View CBCT Artifact Reduction. 154-162 - Hongying Li, Marc C. Robini, Zhongwei Zhou, Wei Tang, Yuemin Zhu:
Nasal Mesh Unfolding - An Approach to Obtaining 2-D Skin Templates from 3-D Nose Models. 163-170 - Yifan Wu, Vivek K. Singh, Brian Teixeira, Kai Ma, Birgi Tamersoy, Andreas Krauss, Terrence Chen:
Towards Generating Personalized Volumetric Phantom from Patient's Surface Geometry. 171-179 - Pengyue Zhang, Fusheng Wang, Wei Xu, Yu Li:
Multi-channel Generative Adversarial Network for Parallel Magnetic Resonance Image Reconstruction in K-space. 180-188 - Kinam Kwon, Dongchan Kim, HyunWook Park:
A Learning-Based Metal Artifacts Correction Method for MRI Using Dual-Polarity Readout Gradients and Simulated Data. 189-197 - Christoph Jud, Damien Nguyen, Robin Sandkühler, Alina Giger, Oliver Bieri, Philippe C. Cattin:
Motion Aware MR Imaging via Spatial Core Correspondence. 198-205 - Daniel Coelho de Castro, Ben Glocker:
Nonparametric Density Flows for MRI Intensity Normalisation. 206-214 - Lei Xiang, Yong Chen, Weitang Chang, Yiqiang Zhan, Weili Lin, Qian Wang, Dinggang Shen:
Ultra-Fast T2-Weighted MR Reconstruction Using Complementary T1-Weighted Information. 215-223 - Jiulong Liu, Tao Kuang, Xiaoqun Zhang:
Image Reconstruction by Splitting Deep Learning Regularization from Iterative Inversion. 224-231 - Maximilian Seitzer, Guang Yang, Jo Schlemper, Ozan Oktay, Tobias Würfl, Vincent Christlein, Tom Wong, Raad Mohiaddin, David N. Firmin, Jennifer Keegan, Daniel Rueckert, Andreas K. Maier:
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction. 232-240 - Taejoon Eo, Hyungseob Shin, Taeseong Kim, Yohan Jun, Dosik Hwang:
Translation of 1D Inverse Fourier Transform of K-space to an Image Based on Deep Learning for Accelerating Magnetic Resonance Imaging. 241-249 - Ilkay Öksüz, Bram Ruijsink, Esther Puyol-Antón, Aurélien Bustin, Gastão Cruz, Claudia Prieto, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Deep Learning Using K-Space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection. 250-258 - Jo Schlemper, Ozan Oktay, Wenjia Bai, Daniel Coelho de Castro, Jinming Duan, Chen Qin, Joseph V. Hajnal, Daniel Rueckert:
Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning. 259-267 - Giacomo Tarroni, Ozan Oktay, Matthew Sinclair, Wenjia Bai, Andreas Schuh, Hideaki Suzuki, Antonio de Marvao, Declan P. O'Regan, Stuart A. Cook, Daniel Rueckert:
A Comprehensive Approach for Learning-Based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks. 268-276 - Amir Alansary, Loïc Le Folgoc, Ghislain Vaillant, Ozan Oktay, Yuanwei Li, Wenjia Bai, Jonathan Passerat-Palmbach, Ricardo Guerrero, Konstantinos Kamnitsas, Benjamin Hou, Steven G. McDonagh, Ben Glocker, Bernhard Kainz, Daniel Rueckert:
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents. 277-285 - Yu Zhao, Shu Liao, Yimo Guo, Liang Zhao, Zhennan Yan, Sungmin Hong, Gerardo Hermosillo, Tianming Liu, Xiang Sean Zhou, Yiqiang Zhan:
Towards MR-Only Radiotherapy Treatment Planning: Synthetic CT Generation Using Multi-view Deep Convolutional Neural Networks. 286-294 - Jo Schlemper, Guang Yang, Pedro F. Ferreira, Andrew D. Scott, Laura-Ann McGill, Zohya Khalique, Margarita Gorodezky, Malte Roehl, Jennifer Keegan, Dudley Pennell, David N. Firmin, Daniel Rueckert:
Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI. 295-303 - Samuel St-Jean, Alberto De Luca, Max A. Viergever, Alexander Leemans:
Automatic, Fast and Robust Characterization of Noise Distributions for Diffusion MRI. 304-312 - Michael Ebner, Guotai Wang, Wenqi Li, Michael Aertsen, Premal A. Patel, Rosalind Aughwane, Andrew Melbourne, Tom Doel, Anna L. David, Jan Deprest, Sébastien Ourselin, Tom Vercauteren:
An Automated Localization, Segmentation and Reconstruction Framework for Fetal Brain MRI. 313-320 - Álvaro S. Hervella, José Rouco, Jorge Novo, Marcos Ortega:
Retinal Image Understanding Emerges from Self-Supervised Multimodal Reconstruction. 321-328 - Yan Wang, Luping Zhou, Lei Wang, Biting Yu, Chen Zu, David S. Lalush, Weili Lin, Xi Wu, Jiliu Zhou, Dinggang Shen:
Locality Adaptive Multi-modality GANs for High-Quality PET Image Synthesis. 329-337 - Viswanath P. Sudarshan, Zhaolin Chen, Suyash P. Awate:
Joint PET+MRI Patch-Based Dictionary for Bayesian Random Field PET Reconstruction. 338-346 - Liyun Tu, Antonio R. Porras, Alec Boyle, Marius George Linguraru:
Analysis of 3D Facial Dysmorphology in Genetic Syndromes from Unconstrained 2D Photographs. 347-355 - Alexander Preuhs, Andreas K. Maier, Michael Manhart, Javad Fotouhi, Nassir Navab, Mathias Unberath:
Double Your Views - Exploiting Symmetry in Transmission Imaging. 356-364 - Olivia Paserin, Kishore Mulpuri, Anthony Cooper, Antony J. Hodgson, Rafeef Garbi:
Real Time RNN Based 3D Ultrasound Scan Adequacy for Developmental Dysplasia of the Hip. 365-373 - Sitong Wu, Zhifan Gao, Zhi Liu, Jianwen Luo, Heye Zhang, Shuo Li:
Direct Reconstruction of Ultrasound Elastography Using an End-to-End Deep Neural Network. 374-382 - Juan J. Cerrolaza, Yuanwei Li, Carlo Biffi, Alberto Gómez, Matthew Sinclair, Jacqueline Matthew, Caronline Knight, Bernhard Kainz, Daniel Rueckert:
3D Fetal Skull Reconstruction from 2DUS via Deep Conditional Generative Networks. 383-391 - Yuanwei Li, Bishesh Khanal, Benjamin Hou, Amir Alansary, Juan J. Cerrolaza, Matthew Sinclair, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Bernhard Kainz, Daniel Rueckert:
Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network. 392-400 - Caroline Vienne, Adrien Stolidi, Hermine Lemaire, Daniel Maier, Diana Renaud, Romain Grall, Sylvie Chevillard, Emilie Brun, Cécile Sicard, Olivier Limousin:
Towards Radiotherapy Enhancement and Real Time Tumor Radiation Dosimetry Through 3D Imaging of Gold Nanoparticles Using XFCT. 401-409 - Yongqin Zhang, Jie-Zhi Cheng, Lei Xiang, Pew-Thian Yap, Dinggang Shen:
Dual-Domain Cascaded Regression for Synthesizing 7T from 3T MRI. 410-417
Machine Learning in Medical Imaging
- Abhijit Guha Roy, Nassir Navab, Christian Wachinger:
Concurrent Spatial and Channel 'Squeeze & Excitation' in Fully Convolutional Networks. 421-429 - S. M. Masudur Rahman Al-Arif, Karen Knapp, Greg G. Slabaugh:
SPNet: Shape Prediction Using a Fully Convolutional Neural Network. 430-439 - Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits:
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. 440-448 - Mehdi Moradi, Ali Madani, Yaniv Gur, Yufan Guo, Tanveer F. Syeda-Mahmood:
Bimodal Network Architectures for Automatic Generation of Image Annotation from Text. 449-456 - Yuan Xue, Tao Xu, L. Rodney Long, Zhiyun Xue, Sameer K. Antani, George R. Thoma, Xiaolei Huang:
Multimodal Recurrent Model with Attention for Automated Radiology Report Generation. 457-466 - Nima Hatami, Michaël Sdika, Hélène Ratiney:
Magnetic Resonance Spectroscopy Quantification Using Deep Learning. 467-475 - Neerav Karani, Krishna Chaitanya, Christian F. Baumgartner, Ender Konukoglu:
A Lifelong Learning Approach to Brain MR Segmentation Across Scanners and Protocols. 476-484 - Guannan Zhao, Bo Zhou, Kaiwen Wang, Rui Jiang, Min Xu:
Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations. 485-492 - Magdalini Paschali, Sailesh Conjeti, Fernando Navarro, Nassir Navab:
Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples. 493-501 - Sumedha Singla, Mingming Gong, Siamak Ravanbakhsh, Frank C. Sciurba, Barnabás Póczos, Kayhan N. Batmanghelich:
Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector. 502-510 - Ke Yan, Mohammadhadi Bagheri, Ronald M. Summers:
3D Context Enhanced Region-Based Convolutional Neural Network for End-to-End Lesion Detection. 511-519 - Hyo-Eun Kim, Seungwook Kim, Jaehwan Lee:
Keep and Learn: Continual Learning by Constraining the Latent Space for Knowledge Preservation in Neural Networks. 520-528 - Joseph Paul Cohen, Margaux Luck, Sina Honari:
Distribution Matching Losses Can Hallucinate Features in Medical Image Translation. 529-536 - Jialei Chen, Yujia Xie, Kan Wang, Zih Huei Wang, Geet Lahoti, Chuck Zhang, Mani A. Vannan, Ben Wang, Zhen Qian:
Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation. 537-545 - Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento, Ian D. Reid, Gustavo Carneiro:
Training Medical Image Analysis Systems like Radiologists. 546-554 - Lodewijk Brand, Hua Wang, Heng Huang, Shannon L. Risacher, Andrew J. Saykin, Li Shen:
Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease. 555-562 - Yuanwei Li, Amir Alansary, Juan J. Cerrolaza, Bishesh Khanal, Matthew Sinclair, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Bernhard Kainz, Daniel Rueckert:
Fast Multiple Landmark Localisation Using a Patch-Based Iterative Network. 563-571 - Ruobing Huang, J. Alison Noble, Ana I. L. Namburete:
Omni-Supervised Learning: Scaling Up to Large Unlabelled Medical Datasets. 572-580 - Carolina Pacheco, René Vidal:
Recurrent Neural Networks for Classifying Human Embryonic Stem Cell-Derived Cardiomyocytes. 581-589 - Feiyun Zhu, Jun Guo, Zheng Xu, Peng Liao, Liu Yang, Junzhou Huang:
Group-Driven Reinforcement Learning for Personalized mHealth Intervention. 590-598 - Rory Raeper, Anna Lisowska, Islem Rekik:
Joint Correlational and Discriminative Ensemble Classifier Learning for Dementia Stratification Using Shallow Brain Multiplexes. 599-607
Statistical Analysis for Medical Imaging
- Xinwei Sun, Lingjing Hu, Fandong Zhang, Yuan Yao, Yizhou Wang:
FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis. 611-619 - Zhixiang Chen, Ruojin Cai, Jiwen Lu, Jianjiang Feng, Jie Zhou:
Order-Sensitive Deep Hashing for Multimorbidity Medical Image Retrieval. 620-628 - Moo K. Chung, Zhan Luo, Alex D. Leow, Andrew L. Alexander, Richard J. Davidson, H. Hill Goldsmith:
Exact Combinatorial Inference for Brain Images. 629-637 - Jérôme-Alexis Chevalier, Joseph Salmon, Bertrand Thirion:
Statistical Inference with Ensemble of Clustered Desparsified Lasso. 638-646 - Mingliang Wang, Daoqiang Zhang, Jiashuang Huang, Dinggang Shen, Mingxia Liu:
Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification. 647-654 - Tanya Nair, Doina Precup, Douglas L. Arnold, Tal Arbel:
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation. 655-663 - Abhijit Guha Roy, Sailesh Conjeti, Nassir Navab, Christian Wachinger:
Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling. 664-672 - Saurabh Garg, Suyash P. Awate:
Perfect MCMC Sampling in Bayesian MRFs for Uncertainty Estimation in Segmentation. 673-681 - Alain Jungo, Raphael Meier, Ekin Ermis, Marcela Blatti-Moreno, Evelyn Herrmann, Roland Wiest, Mauricio Reyes:
On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation. 682-690 - Zach Eaton-Rosen, Felix J. S. Bragman, Sotirios Bisdas, Sébastien Ourselin, M. Jorge Cardoso:
Towards Safe Deep Learning: Accurately Quantifying Biomarker Uncertainty in Neural Network Predictions. 691-699
Image Registration Methods
- Yoshito Otake, Masaki Takao, Norio Fukuda, Shu Takagi, Naoto Yamamura, Nobuhiko Sugano, Yoshinobu Sato:
Registration-Based Patient-Specific Musculoskeletal Modeling Using High Fidelity Cadaveric Template Model. 703-710 - Hongzhi Wang, Rui Zhang:
Atlas Propagation Through Template Selection. 711-719 - Mohsen Farzi, Jose M. Pozo, Eugene V. McCloskey, Richard Eastell, J. Mark Wilkinson, Alejandro F. Frangi:
Spatio-Temporal Atlas of Bone Mineral Density Ageing. 720-728 - Adrian V. Dalca, Guha Balakrishnan, John V. Guttag, Mert R. Sabuncu:
Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration. 729-738 - Jingfan Fan, Xiaohuan Cao, Zhong Xue, Pew-Thian Yap, Dinggang Shen:
Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning Based Registration. 739-746 - Sandy Engelhardt, Raffaele De Simone, Peter M. Full, Matthias Karck, Ivo Wolf:
Improving Surgical Training Phantoms by Hyperrealism: Deep Unpaired Image-to-Image Translation from Real Surgeries. 747-755 - Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew C. H. Lee, Amir Alansary, Steven G. McDonagh, Joseph V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz:
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry. 756-764 - Thilo Sentker, Frederic Madesta, René Werner:
GDL-FIRE ^\text 4D : Deep Learning-Based Fast 4D CT Image Registration. 765-773 - Yipeng Hu, Eli Gibson, Nooshin Ghavami, Ester Bonmati, Caroline M. Moore, Mark Emberton, Tom Vercauteren, J. Alison Noble, Dean C. Barratt:
Adversarial Deformation Regularization for Training Image Registration Neural Networks. 774-782 - Jan Kybic, Jirí Borovec:
Fast Registration by Boundary Sampling and Linear Programming. 783-791 - Nikolas Hesse, Sergi Pujades, Javier Romero, Michael J. Black, Christoph Bodensteiner, Michael Arens, Ulrich G. Hofmann, Uta Tacke, Mijna Hadders-Algra, Raphael Weinberger, Wolfgang Müller-Felber, A. Sebastian Schroeder:
Learning an Infant Body Model from RGB-D Data for Accurate Full Body Motion Analysis. 792-800 - Yungeng Zhang, Yuru Pei, Yuke Guo, Gengyu Ma, Tianmin Xu, Hongbin Zha:
Consistent Correspondence of Cone-Beam CT Images Using Volume Functional Maps. 801-809 - Stefano Moriconi, Maria A. Zuluaga, Hans Rolf Jäger, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Elastic Registration of Geodesic Vascular Graphs. 810-818 - Pei Dong, Xiaohuan Cao, Pew-Thian Yap, Dinggang Shen:
Efficient Groupwise Registration of MR Brain Images via Hierarchical Graph Set Shrinkage. 819-826 - Julia Rackerseder, Maximilian Baust, Rüdiger Göbl, Nassir Navab, Christoph Hennersperger:
Initialize Globally Before Acting Locally: Enabling Landmark-Free 3D US to MRI Registration. 827-835 - Guillermo Gallardo, Nathalie T. H. Gayraud, Rachid Deriche, Maureen Clerc, Samuel Deslauriers-Gauthier, Demian Wassermann:
Solving the Cross-Subject Parcel Matching Problem Using Optimal Transport. 836-843 - Rena Elkin, Saad Nadeem, Eldad Haber, Klara Steklova, Hedok Lee, Helene Benveniste, Allen R. Tannenbaum:
GlymphVIS: Visualizing Glymphatic Transport Pathways Using Regularized Optimal Transport. 844-852 - Ilwoo Lyu, Martin A. Styner, Bennett A. Landman:
Hierarchical Spherical Deformation for Shape Correspondence. 853-861 - Yaël Balbastre, Mikael Brudfors, Kevin Bronik, John Ashburner:
Diffeomorphic Brain Shape Modelling Using Gauss-Newton Optimisation. 862-870 - Yifan Cai, Harshita Sharma, Pierre Chatelain, J. Alison Noble:
Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps. 871-879 - Jian Wang, William M. Wells III, Polina Golland, Miaomiao Zhang:
Efficient Laplace Approximation for Bayesian Registration Uncertainty Quantification. 880-888
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