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ORCID19. MICCAI 2016: Athens, Greece
- Sébastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gözde B. Ünal, William M. Wells III:
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II. Lecture Notes in Computer Science 9901, 2016, ISBN 978-3-319-46722-1 - Luyan Liu, Qian Wang
, Ehsan Adeli, Lichi Zhang, Han Zhang, Dinggang Shen:
Feature Selection Based on Iterative Canonical Correlation Analysis for Automatic Diagnosis of Parkinson's Disease. 1-8 - Brent C. Munsell, Guorong Wu, Yue Gao, Nicholas Desisto, Martin Styner:
Identifying Relationships in Functional and Structural Connectome Data Using a Hypergraph Learning Method. 9-17 - Xiaobo Chen, Han Zhang, Dinggang Shen:
Ensemble Hierarchical High-Order Functional Connectivity Networks for MCI Classification. 18-25 - Luyan Liu, Han Zhang, Islem Rekik, Xiaobo Chen, Qian Wang, Dinggang Shen:
Outcome Prediction for Patient with High-Grade Gliomas from Brain Functional and Structural Networks. 26-34 - Menglin Jiang, Shaoting Zhang, Yuanjie Zheng, Dimitris N. Metaxas:
Mammographic Mass Segmentation with Online Learned Shape and Appearance Priors. 35-43 - Christian Ledig, Sebastian Kaltwang, Antti Tolonen, Juha Koikkalainen, Philip Scheltens, Frederik Barkhof, Hanneke Rhodius-Meester, Betty M. Tijms, Afina W. Lemstra, Wiesje M. van der Flier, Jyrki Lötjönen, Daniel Rueckert:
Differential Dementia Diagnosis on Incomplete Data with Latent Trees. 44-52 - Sihong Chen, Dong Ni, Jing Qin, Bai Ying Lei, Tianfu Wang, Jie-Zhi Cheng:
Bridging Computational Features Toward Multiple Semantic Features with Multi-task Regression: A Study of CT Pulmonary Nodules. 53-60 - Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images. 61-69 - Jailin Peng, Le An, Xiaofeng Zhu, Yan Jin, Dinggang Shen:
Structured Sparse Kernel Learning for Imaging Genetics Based Alzheimer's Disease Diagnosis. 70-78 - Le An, Ehsan Adeli, Mingxia Liu, Jun Zhang, Dinggang Shen:
Semi-supervised Hierarchical Multimodal Feature and Sample Selection for Alzheimer's Disease Diagnosis. 79-87 - Kim-Han Thung, Ehsan Adeli, Pew-Thian Yap, Dinggang Shen:
Stability-Weighted Matrix Completion of Incomplete Multi-modal Data for Disease Diagnosis. 88-96 - Renata G. Raidou, Hugo J. Kuijf, Neda Sepasian, Nicola Pezzotti, Willem H. Bouvy, Marcel Breeuwer, Anna Vilanova:
Employing Visual Analytics to Aid the Design of White Matter Hyperintensity Classifiers. 97-105 - Neeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley:
The Automated Learning of Deep Features for Breast Mass Classification from Mammograms. 106-114 - Tao Xu, Han Zhang, Xiaolei Huang, Shaoting Zhang, Dimitris N. Metaxas:
Multimodal Deep Learning for Cervical Dysplasia Diagnosis. 115-123 - Wei Shen, Mu Zhou, Feng Yang, Di Dong, Caiyun Yang, Yali Zang, Jie Tian:
Learning from Experts: Developing Transferable Deep Features for Patient-Level Lung Cancer Prediction. 124-131 - Huazhu Fu, Yanwu Xu, Stephen Lin, Damon Wing Kee Wong, Jiang Liu:
DeepVessel: Retinal Vessel Segmentation via Deep Learning and Conditional Random Field. 132-139 - Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Andrés Arbeláez, Luc Van Gool:
Deep Retinal Image Understanding. 140-148 - Qi Dou, Hao Chen, Yueming Jin, Lequan Yu, Jing Qin, Pheng-Ann Heng:
3D Deeply Supervised Network for Automatic Liver Segmentation from CT Volumes. 149-157 - Karl D. Fritscher, Patrik Raudaschl, Paolo Zaffino, Maria Francesca Spadea, Gregory C. Sharp, Rainer Schubert:
Deep Neural Networks for Fast Segmentation of 3D Medical Images. 158-165 - Amir Jamaludin, Timor Kadir, Andrew Zisserman:
SpineNet: Automatically Pinpointing Classification Evidence in Spinal MRIs. 166-175 - Jiazhuo Wang, John D. MacKenzie, Rageshree Ramachandran, Danny Z. Chen:
A Deep Learning Approach for Semantic Segmentation in Histology Tissue Images. 176-184 - Yuanpu Xie, Zizhao Zhang, Manish Sapkota, Lin Yang:
Spatial Clockwork Recurrent Neural Network for Muscle Perimysium Segmentation. 185-193 - Darko Stern, Christian Payer, Vincent Lepetit, Martin Urschler:
Automated Age Estimation from Hand MRI Volumes Using Deep Learning. 194-202 - Christian F. Baumgartner, Konstantinos Kamnitsas, Jacqueline Matthew, Sandra Smith, Bernhard Kainz, Daniel Rueckert:
Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks. 203-211 - Dong Nie, Han Zhang, Ehsan Adeli, Luyan Liu, Dinggang Shen:
3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients. 212-220 - Darko Stern, Thomas Ebner, Martin Urschler:
From Local to Global Random Regression Forests: Exploring Anatomical Landmark Localization. 221-229 - Christian Payer, Darko Stern, Horst Bischof, Martin Urschler:
Regressing Heatmaps for Multiple Landmark Localization Using CNNs. 230-238 - Sangheum Hwang, Hyo-Eun Kim:
Self-Transfer Learning for Weakly Supervised Lesion Localization. 239-246 - Dong Ni, Xing Ji, Yaozong Gao, Jie-Zhi Cheng, Huifang Wang, Jing Qin, Bai Ying Lei, Tianfu Wang, Guorong Wu, Dinggang Shen:
Automatic Cystocele Severity Grading in Ultrasound by Spatio-Temporal Regression. 247-255 - Firat Özdemir, Ece Ozkan, Orcun Goksel:
Graphical Modeling of Ultrasound Propagation in Tissue for Automatic Bone Segmentation. 256-264 - Ryutaro Tanno, Aurobrata Ghosh, Francesco Grussu, Enrico Kaden, Antonio Criminisi, Daniel C. Alexander:
Bayesian Image Quality Transfer. 265-273 - Qiang Zhang, Abhir Bhalerao, Caron Parsons, Emma Helm, Charles Hutchinson:
Wavelet Appearance Pyramids for Landmark Detection and Pathology Classification: Application to Lumbar Spinal Stenosis. 274-282 - Marko Rak, Klaus-Dietz Tönnies:
A Learning-Free Approach to Whole Spine Vertebra Localization in MRI. 283-290 - Mohsen Farzi, Jose M. Pozo, Eugene V. McCloskey, J. Mark Wilkinson, Alejandro F. Frangi:
Automatic Quality Control for Population Imaging: A Generic Unsupervised Approach. 291-299 - Mehdi Moradi, Yufan Guo, Yaniv Gur, Mohammadreza Negahdar, Tanveer F. Syeda-Mahmood:
A Cross-Modality Neural Network Transform for Semi-automatic Medical Image Annotation. 300-307 - Siyamalan Manivannan, Caroline Cobb, Stephen Burgess, Emanuele Trucco:
Sub-category Classifiers for Multiple-instance Learning and Its Application to Retinal Nerve Fiber Layer Visibility Classification. 308-316 - Guido Pusiol, Andre Esteva, Scott S. Hall, Michael C. Frank, Arnold Milstein, Li Fei-Fei:
Vision-Based Classification of Developmental Disorders Using Eye-Movements. 317-325 - Róger Bermúdez-Chacón, Carlos J. Becker, Mathieu Salzmann, Pascal Fua:
Scalable Unsupervised Domain Adaptation for Electron Microscopy. 326-334 - Xiaoxu He, Yilong Yin, Manas Sharma, Gary Brahm, Ashley Mercado, Shuo Li:
Automated Diagnosis of Neural Foraminal Stenosis Using Synchronized Superpixels Representation. 335-343 - Satyananda Kashyap, Ipek Oguz, Honghai Zhang, Milan Sonka:
Automated Segmentation of Knee MRI Using Hierarchical Classifiers and Just Enough Interaction Based Learning: Data from Osteoarthritis Initiative. 344-351 - Guotai Wang, Maria A. Zuluaga, Rosalind Pratt, Michael Aertsen, Tom Doel, Maria Klusmann, Anna L. David, Jan Deprest, Tom Vercauteren, Sébastien Ourselin:
Dynamically Balanced Online Random Forests for Interactive Scribble-Based Segmentation. 352-360 - Tasos Papastylianou, Erica Dall' Armellina, Vicente Grau:
Orientation-Sensitive Overlap Measures for the Validation of Medical Image Segmentations. 361-369 - Carlos Correa Shokiche, Philipp Baumann, Ruslan Hlushchuk, Valentin Djonov, Mauricio Reyes:
High-Throughput Glomeruli Analysis of μ CT Kidney Images Using Tree Priors and Scalable Sparse Computation. 370-378 - Benoît Caldairou, Boris C. Bernhardt, Jessie Kulaga-Yoskovitz, Hosung Kim, Neda Bernasconi, Andrea Bernasconi:
A Surface Patch-Based Segmentation Method for Hippocampal Subfields. 379-387 - Isabella Nogues, Le Lu, Xiaosong Wang, Holger Roth, Gedas Bertasius, Nathan Lay, Jianbo Shi, Yohannes Tsehay, Ronald M. Summers:
Automatic Lymph Node Cluster Segmentation Using Holistically-Nested Neural Networks and Structured Optimization in CT Images. 388-397 - Michel M. dos Santos, Paula R. B. Diniz, Abel G. Silva-Filho, Wellington P. dos Santos:
Evaluation-Oriented Training via Surrogate Metrics for Multiple Sclerosis Segmentation. 398-405 - Lisa Y. W. Tang, Tom Brosch, Xingtong Liu, Youngjin Yoo, Anthony Traboulsee, David K. B. Li, Roger C. Tam:
Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction. 406-414 - Patrick Ferdinand Christ, Mohamed Ezzeldin A. Elshaer, Florian Ettlinger, Sunil Tatavarty, Marc Bickel, Patrick Bilic, Markus Rempfler, Marco Armbruster, Felix Hofmann, Melvin D'Anastasi, Wieland H. Sommer, Seyed-Ahmad Ahmadi, Bjoern H. Menze:
Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields. 415-423 - Özgün Çiçek, Ahmed Abdulkadir, Soeren S. Lienkamp, Thomas Brox, Olaf Ronneberger:
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation. 424-432 - Robert Korez, Bostjan Likar, Franjo Pernus, Tomaz Vrtovec:
Model-Based Segmentation of Vertebral Bodies from MR Images with 3D CNNs. 433-441 - Jinzheng Cai, Le Lu, Zizhao Zhang, Fuyong Xing, Lin Yang, Qian Yin:
Pancreas Segmentation in MRI Using Graph-Based Decision Fusion on Convolutional Neural Networks. 442-450 - Holger R. Roth, Le Lu, Amal Farag, Andrew Sohn, Ronald M. Summers:
Spatial Aggregation of Holistically-Nested Networks for Automated Pancreas Segmentation. 451-459 - Aïcha BenTaieb, Ghassan Hamarneh:
Topology Aware Fully Convolutional Networks for Histology Gland Segmentation. 460-468 - Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, Yoshua Bengio:
HeMIS: Hetero-Modal Image Segmentation. 469-477 - Pim Moeskops, Jelmer M. Wolterink, Bas H. M. van der Velden, Kenneth G. A. Gilhuijs, Tim Leiner, Max A. Viergever, Ivana Isgum:
Deep Learning for Multi-task Medical Image Segmentation in Multiple Modalities. 478-486 - Hao Chen, Yefeng Zheng, Jin Hyeong Park, Pheng-Ann Heng, Shaohua Kevin Zhou:
Iterative Multi-domain Regularized Deep Learning for Anatomical Structure Detection and Segmentation from Ultrasound Images. 487-495 - Yan Xu, Yang Li, Mingyuan Liu, Yipei Wang, Maode Lai, Eric I-Chao Chang:
Gland Instance Segmentation by Deep Multichannel Side Supervision. 496-504 - Oualid M. Benkarim, Gemma Piella, Miguel Ángel González Ballester, Gerard Sanroma:
Enhanced Probabilistic Label Fusion by Estimating Label Confidences Through Discriminative Learning. 505-512 - Siqi Bao, Albert C. S. Chung:
Feature Sensitive Label Fusion with Random Walker for Atlas-Based Image Segmentation. 513-520 - Heran Yang, Jian Sun, Huibin Li, Lisheng Wang, Zongben Xu:
Deep Fusion Net for Multi-atlas Segmentation: Application to Cardiac MR Images. 521-528 - Mahsa Shakeri, Enzo Ferrante, Stavros Tsogkas, Sarah Lippé, Samuel Kadoury, Iasonas Kokkinos, Nikos Paragios:
Prior-Based Coregistration and Cosegmentation. 529-537 - Ipek Oguz, Satyananda Kashyap, Hongzhi Wang, Paul A. Yushkevich, Milan Sonka:
Globally Optimal Label Fusion with Shape Priors. 538-546 - Ninon Burgos, Filipa Guerreiro, Jamie McClelland, Simeon Nill, David Dearnaley, Nandita deSouza, Uwe Oelfke, Antje-Christin Knopf, Sébastien Ourselin, M. Jorge Cardoso:
Joint Segmentation and CT Synthesis for MRI-only Radiotherapy Treatment Planning. 547-555 - Masahiro Oda, Natsuki Shimizu, Kenichi Karasawa, Yukitaka Nimura, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert, Kensaku Mori:
Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation. 556-563 - Long Xie, Laura E. M. Wisse, Sandhitsu R. Das, Hongzhi Wang, David A. Wolk, José V. Manjón, Paul A. Yushkevich:
Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI. 564-571 - Khosro Bahrami, Islem Rekik, Feng Shi, Yaozong Gao, Dinggang Shen:
7T-Guided Learning Framework for Improving the Segmentation of 3T MR Images. 572-580 - Xiahai Zhuang:
Multivariate Mixture Model for Cardiac Segmentation from Multi-Sequence MRI. 581-588 - Amir Alansary, Konstantinos Kamnitsas, Alice Davidson, Rostislav Khlebnikov, Martin Rajchl, Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, Ben Glocker, Daniel Rueckert, Bernhard Kainz:
Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI. 589-597 - Mattias P. Heinrich, Maximilian Blendowski:
Multi-organ Segmentation Using Vantage Point Forests and Binary Context Features. 598-606 - Tomás Sixta, Boris Flach:
Multiple Object Segmentation and Tracking by Bayes Risk Minimization. 607-615 - Lena Maier-Hein, Tobias Roß, Janek Gröhl, Ben Glocker, Sebastian Bodenstedt, Christian Stock, Eric Heim, Michael Götz, Sebastian J. Wirkert, Hannes Kenngott, Stefanie Speidel, Klaus H. Maier-Hein:
Crowd-Algorithm Collaboration for Large-Scale Endoscopic Image Annotation with Confidence. 616-623 - Jie Yang, Elsa D. Angelini, Pallavi P. Balte, Eric A. Hoffman, Colin O. Wu, Bharath A. Venkatesh, R. Graham Barr, Andrew F. Laine:
Emphysema Quantification on Cardiac CT Scans Using Hidden Markov Measure Field Model: The MESA Lung Study. 624-631 - Mitko Veta, Paul J. van Diest, Josien P. W. Pluim:
Cutting Out the Middleman: Measuring Nuclear Area in Histopathology Slides Without Segmentation. 632-639 - Sheng Wang, Jiawen Yao, Zheng Xu, Junzhou Huang:
Subtype Cell Detection with an Accelerated Deep Convolution Neural Network. 640-648 - Jiawen Yao, Sheng Wang, Xinliang Zhu, Junzhou Huang:
Imaging Biomarker Discovery for Lung Cancer Survival Prediction. 649-657 - Lin Yang, Yizhe Zhang, Ian H. Guldner, Siyuan Zhang, Danny Z. Chen:
3D Segmentation of Glial Cells Using Fully Convolutional Networks and k-Terminal Cut. 658-666 - Bisser Raytchev, Atsuki Masuda, Masatoshi Minakawa, Kojiro Tanaka, Takio Kurita, Toru Imamura, Masashi Suzuki, Toru Tamaki, Kazufumi Kaneda:
Detection of Differentiated vs. Undifferentiated Colonies of iPS Cells Using Random Forests Modeled with the Multivariate Polya Distribution. 667-675 - Zheng Xu, Junzhou Huang:
Detecting 10, 000 Cells in One Second. 676-684 - Yunxiang Mao, Zhaozheng Yin:
A Hierarchical Convolutional Neural Network for Mitosis Detection in Phase-Contrast Microscopy Images. 685-692
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