Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016

1. Front Matter

   Pages I-XXIV

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2. Learning-Based Multimodal Image Registration for Prostate Cancer Radiation Therapy

   • Xiaohuan Cao, Yaozong Gao, Jianhua Yang, Guorong Wu, Dinggang Shen

   Pages 1-9

3. A Deep Metric for Multimodal Registration

   • Martin Simonovsky, Benjamín Gutiérrez-Becker, Diana Mateus, Nassir Navab, Nikos Komodakis

   Pages 10-18

4. Learning Optimization Updates for Multimodal Registration

   • Benjamín Gutiérrez-Becker, Diana Mateus, Loïc Peter, Nassir Navab

   Pages 19-27

5. Memory Efficient LDDMM for Lung CT

   • Thomas Polzin, Marc Niethammer, Mattias P. Heinrich, Heinz Handels, Jan Modersitzki

   Pages 28-36

6. Inertial Demons: A Momentum-Based Diffeomorphic Registration Framework

   • Andre Santos-Ribeiro, David J. Nutt, John McGonigle

   Pages 37-45

7. Diffeomorphic Density Registration in Thoracic Computed Tomography

   • Caleb Rottman, Ben Larson, Pouya Sabouri, Amit Sawant, Sarang Joshi

   Pages 46-53

8. Temporal Registration in In-Utero Volumetric MRI Time Series

   • Ruizhi Liao, Esra A. Turk, Miaomiao Zhang, Jie Luo, P. Ellen Grant, Elfar Adalsteinsson et al.

   Pages 54-62

9. Probabilistic Atlas of the Human Hippocampus Combining Ex Vivo MRI and Histology

   • Daniel H. Adler, Ranjit Ittyerah, John Pluta, Stephen Pickup, Weixia Liu, David A. Wolk et al.

   Pages 63-71

10. Deformation Estimation with Automatic Sliding Boundary Computation

    • Joseph Samuel Preston, Sarang Joshi, Ross Whitaker

    Pages 72-80

11. Bilateral Weighted Adaptive Local Similarity Measure for Registration in Neurosurgery

    • Martin Kochan, Marc Modat, Tom Vercauteren, Mark White, Laura Mancini, Gavin P. Winston et al.

    Pages 81-88

12. Model-Based Regularisation for Respiratory Motion Estimation with Sparse Features in Image-Guided Interventions

    • Matthias Wilms, In Young Ha, Heinz Handels, Mattias Paul Heinrich

    Pages 89-97

13. Carotid Artery Wall Motion Estimated from Ultrasound Imaging Sequences Using a Nonlinear State Space Approach

    • Zhifan Gao, Yuanyuan Sun, Heye Zhang, Dhanjoo Ghista, Yanjie Li, Huahua Xiong et al.

    Pages 98-106

14. Accuracy Estimation for Medical Image Registration Using Regression Forests

    • Hessam Sokooti, Gorkem Saygili, Ben Glocker, Boudewijn P. F. Lelieveldt, Marius Staring

    Pages 107-115

15. Embedding Segmented Volume in Finite Element Mesh with Topology Preservation

    • Kazuya Sase, Teppei Tsujita, Atsushi Konno

    Pages 116-123

16. Deformable 3D-2D Registration of Known Components for Image Guidance in Spine Surgery

    • A. Uneri, J. Goerres, T. De Silva, M. W. Jacobson, M. D. Ketcha, S. Reaungamornrat et al.

    Pages 124-132

17. Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm

    • Seth D. Billings, Ayushi Sinha, Austin Reiter, Simon Leonard, Masaru Ishii, Gregory D. Hager et al.

    Pages 133-141

18. A Multi-resolution T-Mixture Model Approach to Robust Group-Wise Alignment of Shapes

    • Nishant Ravikumar, Ali Gooya, Serkan Çimen, Alejandro F. Frangi, Zeike A. Taylor

    Pages 142-149

19. Quantifying Shape Deformations by Variation of Geometric Spectrum

    • Hajar Hamidian, Jiaxi Hu, Zichun Zhong, Jing Hua

    Pages 150-157

20. Myocardial Segmentation of Contrast Echocardiograms Using Random Forests Guided by Shape Model

    • Yuanwei Li, Chin Pang Ho, Navtej Chahal, Roxy Senior, Meng-Xing Tang

    Pages 158-165

The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefully selected 228 revised regular papers from 756 submissions for presentation in three volumes. The papers have been organized in the following topical sections: Part I: brain analysis, brain analysis - connectivity; brain analysis - cortical morphology; Alzheimer disease; surgical guidance and tracking; computer aided interventions; ultrasound image analysis; cancer image analysis; Part II: machine learning and feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration and deformation estimation;  shape modeling; cardiac and vascular image analysis; image reconstruction; and MR imageanalysis.

• biomechanical simulation
• computer aided diagnosis
• brain network analysis
• robot intervention
• surgical simulation
• augmented reality
• classification
• clustering
• computational anatomy
• computational geometry
• deep neural networks
• image analysis
• intervention planning
• medical imaging
• navigation
• normalization
• statistical atlases
• support vector machines
• visualization
• x-ray imaging

• University College London, London, UK

  Sebastien Ourselin

• The Hebrew University of Jerusalem, Jerusalem, Israel

  Leo Joskowicz

• Harvard Medical School, Boston, USA

  Mert R. Sabuncu, William Wells

• Istanbul Technical University, Istanbul, Türkiye

  Gozde Unal

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