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Ron Kikinis - IEEE Xplore Author Profile
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Ron Kikinis

Also published under: R. Kikinis

Publications
77
Citations
6,434
Publications by Year
19912025
Co-Authors:
Show All Co-Authors (217)
Image of author Ron Kikinis

Ron Kikinis

Also published under: R. Kikinis

Affiliation

Brigham and Women’s Hospital
Harvard Medical School
Boston, MA, USA

Publication Topics

Biography

Ron Kikinis is the director of the Surgical Planning Laboratory of the Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, and a professor of radiology at Harvard Medical School. Before joining Brigham and Women's Hospital in 1988, he worked as a researcher at the ETH in Zurich and as a resident at the University Hospital in Zurich, Switzerland. He received his M.D. from the University of Zurich, Switzerland, in 1982. His interests include the development of image processing algorithms and software systems, and their application to a variety of medical applications.(Based on document published on 9 October 2006).
Publications
77
Citations
6,434
Publications by Year
19912025
Co-Authors:
Show All Co-Authors (217)
Author's Published Works

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An End-to-End Geometry-Based Pipeline for Automatic Preoperative Surgical Planning of Pelvic Fracture Reduction and Fixation

Jiaxuan Liu;Haitao Li;Bolun Zeng;Huixiang Wang;Ron Kikinis;Leo Joskowicz;Xiaojun Chen

IEEE Transactions on Medical Imaging
Year: 2025 | Volume: 44, Issue: 1 | Journal Article |
Computer-assisted preoperative planning of pelvic fracture reduction surgery has the potential to increase the accuracy of the surgery and to reduce complications. However, the diversity of the pelvic fractures and the disturbance of small fracture fragments present a great challenge to perform reliable automatic preoperative planning. In this paper, we present a comprehensive and automatic preope...Show More

An End-to-End Geometry-Based Pipeline for Automatic Preoperative Surgical Planning of Pelvic Fracture Reduction and Fixation

Jiaxuan Liu;Haitao Li;Bolun Zeng;Huixiang Wang;Ron Kikinis;Leo Joskowicz;Xiaojun Chen

Year: 2025 | Volume: 44, Issue: 1 | Journal Article |

A Registration- and Uncertainty-Based Framework for White Matter Tract Segmentation with Only One Annotated Subject

Hao Xu;Tengfei Xue;Dongnan Liu;Fan Zhang;Carl-Fredrik Westin;Ron Kikinis;Lauren J. O’Donnell;Weidong Cai

2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
White matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI) plays an important role in the analysis of human health and brain diseases. However, the annotation of WM tracts is time-consuming and needs experienced neuroanatomists. In this study, to explore tract segmentation in the challenging setting of minimal annotations, we propose a novel framework utilizing only ...Show More

A Registration- and Uncertainty-Based Framework for White Matter Tract Segmentation with Only One Annotated Subject

Hao Xu;Tengfei Xue;Dongnan Liu;Fan Zhang;Carl-Fredrik Westin;Ron Kikinis;Lauren J. O’Donnell;Weidong Cai

Year: 2023 | Conference Paper |

A Review of Low-Cost Ultrasound Compatible Phantoms

Leah A. Groves;Mohamed Keita;Saidou Talla;Ron Kikinis;Gabor Fichtinger;Parvin Mousavi;Mamadou Camara

IEEE Transactions on Biomedical Engineering
Year: 2023 | Volume: 70, Issue: 12 | Journal Article |
Cited by: Papers (1)
Ultrasound-compatible phantoms are used to develop novel US-based systems and train simulated medical interventions. The price difference between lab-made and commercially available ultrasound-compatible phantoms lead to the publication of many papers categorized as low-cost in the literature. The aim of this review was to improve the phantom selection process by summarizing the pertinent literatu...Show More

A Review of Low-Cost Ultrasound Compatible Phantoms

Leah A. Groves;Mohamed Keita;Saidou Talla;Ron Kikinis;Gabor Fichtinger;Parvin Mousavi;Mamadou Camara

Year: 2023 | Volume: 70, Issue: 12 | Journal Article |

Open Source Platform for Transperineal In-Bore MRI-Guided Targeted Prostate Biopsy

Christian Herz;Kyle MacNeil;Peter A. Behringer;Junichi Tokuda;Alireza Mehrtash;Parvin Mousavi;Ron Kikinis;Fiona M. Fennessy;Clare M. Tempany;Kemal Tuncali;Andriy Fedorov

IEEE Transactions on Biomedical Engineering
Year: 2020 | Volume: 67, Issue: 2 | Journal Article |
Cited by: Papers (1)
Objective: Accurate biopsy sampling of the suspected lesions is critical for the diagnosis and clinical management of prostate cancer. Transperineal in-bore MRI-guided prostate biopsy (tpMRgBx) is a targeted biopsy technique that was shown to be safe, efficient, and accurate. Our goal was to develop an open source software platform to support evaluation, refinement, and translation of this biopsy ...Show More

Open Source Platform for Transperineal In-Bore MRI-Guided Targeted Prostate Biopsy

Christian Herz;Kyle MacNeil;Peter A. Behringer;Junichi Tokuda;Alireza Mehrtash;Parvin Mousavi;Ron Kikinis;Fiona M. Fennessy;Clare M. Tempany;Kemal Tuncali;Andriy Fedorov

Year: 2020 | Volume: 67, Issue: 2 | Journal Article |

Automatic Needle Segmentation and Localization in MRI With 3-D Convolutional Neural Networks: Application to MRI-Targeted Prostate Biopsy

Alireza Mehrtash;Mohsen Ghafoorian;Guillaume Pernelle;Alireza Ziaei;Friso G. Heslinga;Kemal Tuncali;Andriy Fedorov;Ron Kikinis;Clare M. Tempany;William M. Wells;Purang Abolmaesumi;Tina Kapur

IEEE Transactions on Medical Imaging
Year: 2019 | Volume: 38, Issue: 4 | Journal Article |
Cited by: Papers (45)
Image guidance improves tissue sampling during biopsy by allowing the physician to visualize the tip and trajectory of the biopsy needle relative to the target in MRI, CT, ultrasound, or other relevant imagery. This paper reports a system for fast automatic needle tip and trajectory localization and visualization in MRI that has been developed and tested in the context of an active clinical resear...Show More

Automatic Needle Segmentation and Localization in MRI With 3-D Convolutional Neural Networks: Application to MRI-Targeted Prostate Biopsy

Alireza Mehrtash;Mohsen Ghafoorian;Guillaume Pernelle;Alireza Ziaei;Friso G. Heslinga;Kemal Tuncali;Andriy Fedorov;Ron Kikinis;Clare M. Tempany;William M. Wells;Purang Abolmaesumi;Tina Kapur

Year: 2019 | Volume: 38, Issue: 4 | Journal Article |

Train the Trainers: Medical Technology for the Sustainable Development of Africa

Juan Ruiz-Alzola;Asmaa Skareb;Ahmedou Moulaye Idriss;Babacar Diao;Joseane Da Rosa De Pina Ferreira;María Alexandra Fernandes Rodrigues;Luis López Rivero;Ron Kikinis

2018 IEEE Global Humanitarian Technology Conference (GHTC)
Year: 2018 | Conference Paper |
Cited by: Papers (3)
The role of technology as a key driver of sustainable development has long been recognized. Technology leverages total-factor productivity and contributes to the growth of welfare. The lack of adequate financial and human capital hampers the adoption of technology in many parts of Africa. On September 2015, the General Assembly of United Nations adopted as a consensus resolution the 2030 Developme...Show More

Train the Trainers: Medical Technology for the Sustainable Development of Africa

Juan Ruiz-Alzola;Asmaa Skareb;Ahmedou Moulaye Idriss;Babacar Diao;Joseane Da Rosa De Pina Ferreira;María Alexandra Fernandes Rodrigues;Luis López Rivero;Ron Kikinis

Year: 2018 | Conference Paper |

Large Scale Cloud-Based Deformable Registration for Image Guided Therapy

Shahram Mohrehkesh;Andriy Fedorov;Arun Brahmavar Vishwanatha;Fotis Drakopoulos;Ron Kikinis;Nikos Chrisochoides

2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
Year: 2016 | Conference Paper |
We present a feasibility study using cloud resources for computing the deformable registration or non-rigid registration (NRR) of brain MR images for Image Guided Neurosurgery (IGNS). We consider the use of cloud resources in two scenarios. First, we describe a workflow implementation to enable speculative computation of registration to improve confidence in the result and assist in retrospective ...Show More

Large Scale Cloud-Based Deformable Registration for Image Guided Therapy

Shahram Mohrehkesh;Andriy Fedorov;Arun Brahmavar Vishwanatha;Fotis Drakopoulos;Ron Kikinis;Nikos Chrisochoides

Year: 2016 | Conference Paper |

Pairwise Latent Semantic Association for Similarity Computation in Medical Imaging

Fan Zhang;Yang Song;Weidong Cai;Sidong Liu;Siqi Liu;Sonia Pujol;Ron Kikinis;Yong Xia;Michael J. Fulham;David Dagan Feng;Alzheimer's Disease Neuroimaging Initiative

IEEE Transactions on Biomedical Engineering
Year: 2016 | Volume: 63, Issue: 5 | Journal Article |
Cited by: Papers (22)
Retrieving medical images that present similar diseases is an active research area for diagnostics and therapy. However, it can be problematic given the visual variations between anatomical structures. In this paper, we propose a new feature extraction method for similarity computation in medical imaging. Instead of the low-level visual appearance, we design a CCA-PairLDA feature representation me...Show More

Pairwise Latent Semantic Association for Similarity Computation in Medical Imaging

Fan Zhang;Yang Song;Weidong Cai;Sidong Liu;Siqi Liu;Sonia Pujol;Ron Kikinis;Yong Xia;Michael J. Fulham;David Dagan Feng;Alzheimer's Disease Neuroimaging Initiative

Year: 2016 | Volume: 63, Issue: 5 | Journal Article |

Subject-centered multi-view feature fusion for neuroimaging retrieval and classification

Sidong Liu;Weidong Cai;Siqi Liu;Sonia Pujol;Ron Kikinis;Dagan Feng

2015 IEEE International Conference on Image Processing (ICIP)
Year: 2015 | Conference Paper |
Cited by: Papers (2)
Multi-View neuroimaging retrieval and classification play an important role in computer-aided-diagnosis of brain disorders, as multi-view features could provide more insights of the disease pathology and potentially lead to more accurate diagnosis than single-view features. The large inter-feature and inter-subject variations make the multi-view neuroimaging analysis a challenging task. Many multi...Show More

Subject-centered multi-view feature fusion for neuroimaging retrieval and classification

Sidong Liu;Weidong Cai;Siqi Liu;Sonia Pujol;Ron Kikinis;Dagan Feng

Year: 2015 | Conference Paper |

Longitudinal brain MR retrieval with diffeomorphic demons registration: What happened to those patients with similar changes?

Siqi Liu;Sidong Liu;Fan Zhang;Weidong Cai;Sonia Pujol;Ron Kikinis;Dagan Feng

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)
Year: 2015 | Conference Paper |
Cited by: Papers (10)
Current medical content-based retrieval (MCBR) systems for neuroimaging data mainly focus on retrieving the cross-sectional neuroimaging data with similar regional or global measurements. The longitudinal pathological changes along different time-points are usually neglected in such MCBR systems. We propose the cross-registration based retrieval for longitudinal MR data to retrieve patients with s...Show More

Longitudinal brain MR retrieval with diffeomorphic demons registration: What happened to those patients with similar changes?

Siqi Liu;Sidong Liu;Fan Zhang;Weidong Cai;Sonia Pujol;Ron Kikinis;Dagan Feng

Year: 2015 | Conference Paper |

Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease

Siqi Liu;Sidong Liu;Weidong Cai;Hangyu Che;Sonia Pujol;Ron Kikinis;Dagan Feng;Michael J. Fulham;ADNI

IEEE Transactions on Biomedical Engineering
Year: 2015 | Volume: 62, Issue: 4 | Journal Article |
Cited by: Papers (418)
The accurate diagnosis of Alzheimer's disease (AD) is essential for patient care and will be increasingly important as disease modifying agents become available, early in the course of the disease. Although studies have applied machine learning methods for the computer-aided diagnosis of AD, a bottleneck in the diagnostic performance was shown in previous methods, due to the lacking of efficient s...Show More

Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease

Siqi Liu;Sidong Liu;Weidong Cai;Hangyu Che;Sonia Pujol;Ron Kikinis;Dagan Feng;Michael J. Fulham;ADNI

Year: 2015 | Volume: 62, Issue: 4 | Journal Article |

A 3D difference-of-Gaussian-based lesion detector for brain PET

Weidong Cai;Sidong Liu;Yang Song;Sonia Pujol;Ron Kikinis;Dagan Feng

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)
Year: 2014 | Conference Paper |
Cited by: Papers (12)
Positron emission tomography (PET) plays an important role in neurodegenerative disorder diagnosis and neurooncology applications, especially detecting the early metabolism anomalies in human brains. Current lesion detection algorithms can be roughly classified into voxel-based, region of interest (ROI)-based, and global algorithms. These methods may capture the scale and/or location of the lesion...Show More

A 3D difference-of-Gaussian-based lesion detector for brain PET

Weidong Cai;Sidong Liu;Yang Song;Sonia Pujol;Ron Kikinis;Dagan Feng

Year: 2014 | Conference Paper |

Propagation graph fusion for multi-modal medical content-based retrieval

Sidong Liu;Siqi Liu;Sonia Pujol;Ron Kikinis;Dagan Feng;Weidong Cai

2014 13th International Conference on Control Automation Robotics & Vision (ICARCV)
Year: 2014 | Conference Paper |
Cited by: Papers (10)
Medical content-based retrieval (MCBR) plays an important role in computer aided diagnosis and clinical decision support. Multi-modal imaging data have been increasingly used in MCBR, as they could provide more insights of the diseases and complement the deficiencies of single-modal data. However, it is very challenging to fuse data in different modalities since they have different physical fundam...Show More

Propagation graph fusion for multi-modal medical content-based retrieval

Sidong Liu;Siqi Liu;Sonia Pujol;Ron Kikinis;Dagan Feng;Weidong Cai

Year: 2014 | Conference Paper |

Latent Semantic Association for Medical Image Retrieval

Fan Zhang;Yang Song;Sidong Liu;Sonia Pujol;Ron Kikinis;Dagan Feng;Weidong Cai

2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
Year: 2014 | Conference Paper |
Cited by: Papers (2)
In this work, we propose a Latent Semantic Association Retrieval(LSAR) method to break the bottleneck of the low-level feature based medical image retrieval. The method constructs the high-level semantic correlations among patients based on the low-level feature set extracted from the images. Specifically, a Pair-LDA model is firstly designed to refine the topic generation process of traditional L...Show More

Latent Semantic Association for Medical Image Retrieval

Fan Zhang;Yang Song;Sidong Liu;Sonia Pujol;Ron Kikinis;Dagan Feng;Weidong Cai

Year: 2014 | Conference Paper |

Early diagnosis of Alzheimer's disease with deep learning

Siqi Liu;Sidong Liu;Weidong Cai;Sonia Pujol;Ron Kikinis;Dagan Feng

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)
Year: 2014 | Conference Paper |
Cited by: Papers (319)
The accurate diagnosis of Alzheimer's disease (AD) plays a significant role in patient care, especially at the early stage, because the consciousness of the severity and the progression risks allows the patients to take prevention measures before irreversible brain damages are shaped. Although many studies have applied machine learning methods for computer-aided-diagnosis (CAD) of AD recently, a b...Show More

Early diagnosis of Alzheimer's disease with deep learning

Siqi Liu;Sidong Liu;Weidong Cai;Sonia Pujol;Ron Kikinis;Dagan Feng

Year: 2014 | Conference Paper |

Co-neighbor multi-view spectral embedding for medical content-based retrieval

Hangyu Che;Sidong Liu;Weidong Cai;Sonia Pujol;Ron Kikinis;Dagan Feng

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)
Year: 2014 | Conference Paper |
Cited by: Papers (9)
Multimodal medical data from various information sources are often used to depict patients. We refer to each source as a `view'. Multi-view features could provide complementary information to each other; thus by fusing the multi-view features, we could greatly enhance the current medical content-based retrieval framework. In this paper, we propose a Co-neighbor Multi-view Spectral Embedding (CMSE)...Show More

Co-neighbor multi-view spectral embedding for medical content-based retrieval

Hangyu Che;Sidong Liu;Weidong Cai;Sonia Pujol;Ron Kikinis;Dagan Feng

Year: 2014 | Conference Paper |

Application of Tolerance Limits to the Characterization of Image Registration Performance

Andriy Fedorov;William M. Wells;Ron Kikinis;Clare M. Tempany;Mark G. Vangel

IEEE Transactions on Medical Imaging
Year: 2014 | Volume: 33, Issue: 7 | Journal Article |
Cited by: Papers (3)
Deformable image registration is used increasingly in image-guided interventions and other applications. However, validation and characterization of registration performance remain areas that require further study. We propose an analysis methodology for deriving tolerance limits on the initial conditions for deformable registration that reliably lead to a successful registration. This approach res...Show More

Application of Tolerance Limits to the Characterization of Image Registration Performance

Andriy Fedorov;William M. Wells;Ron Kikinis;Clare M. Tempany;Mark G. Vangel

Year: 2014 | Volume: 33, Issue: 7 | Journal Article |

Localized Sparse Code Gradient in Alzheimer's disease staging

Sidong Liu;Weidong Cai;Yang Song;Sonia Pujol;Ron Kikinis;Lingfeng Wen;David Dagan Feng

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2013 | Conference Paper |
Cited by: Papers (6)
The accurate diagnosis of Alzheimer's disease (AD) at different stages is essential to identify patients at high risk of dementia and plan prevention or treatment measures accordingly. In this study, we proposed a new AD staging method for the entire spectrum of AD including the AD, Mild Cognitive Impairment with and without AD conversions, and Cognitive Normal groups. Our method embedded the high...Show More

Localized Sparse Code Gradient in Alzheimer's disease staging

Sidong Liu;Weidong Cai;Yang Song;Sonia Pujol;Ron Kikinis;Lingfeng Wen;David Dagan Feng

Year: 2013 | Conference Paper |

High-resolution electroencephalographic forward modeling in traumatic brain injury using the finite element method

S.Y. Matthew Goh;Andrei Irimia;Carinna M. Torgerson;Ron Kikinis;Paul M. Vespa;John D. Van Horn

2013 IEEE 10th International Symposium on Biomedical Imaging
Year: 2013 | Conference Paper |
Localization of electrical brain activity via electroencephalography (EEG) remains a challenging task in traumatic brain injury (TBI) patients, partly due to the complexity of structural brain changes resulting from neurological insult. When localizing EEG-recorded brain activity, the failure to account for pathology-related changes in tissue conductivities may cause forward model inaccuracies whi...Show More

High-resolution electroencephalographic forward modeling in traumatic brain injury using the finite element method

S.Y. Matthew Goh;Andrei Irimia;Carinna M. Torgerson;Ron Kikinis;Paul M. Vespa;John D. Van Horn

Year: 2013 | Conference Paper |

Automatic airway analysis for genome-wide association studies in COPD

Raul San José Estépar;James C. Ross;Gordon L. Kindlmann;Alejandro Diaz;Yuka Okajima;Ron Kikinis;Carl-Fredrik Westin;Edwin K. Silverman;George G. Washko

2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)
Year: 2012 | Conference Paper |
Cited by: Papers (4)
We present an image pipeline for airway phenotype extraction suitable for large-scale genetic and epidemiological studies including genome-wide association studies (GWAS) in Chronic Obstructive Pulmonary Disease (COPD). We use scale-space particles to densely sample intraparenchymal airway locations in a large cohort of high-resolution CT scans. The particle methodology is based on a constrained e...Show More

Automatic airway analysis for genome-wide association studies in COPD

Raul San José Estépar;James C. Ross;Gordon L. Kindlmann;Alejandro Diaz;Yuka Okajima;Ron Kikinis;Carl-Fredrik Westin;Edwin K. Silverman;George G. Washko

Year: 2012 | Conference Paper |

3D Slicer as a tool for interactive brain tumor segmentation

Ron Kikinis;Steve Pieper

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2011 | Conference Paper |
Cited by: Papers (41)
User interaction is required for reliable segmentation of brain tumors in clinical practice and in clinical research. By incorporating current research tools, 3D Slicer provides a set of interactive, easy to use tools that can be efficiently used for this purpose. One of the modules of 3D Slicer is an interactive editor tool, which contains a variety of interactive segmentation effects. Use of the...Show More

3D Slicer as a tool for interactive brain tumor segmentation

Ron Kikinis;Steve Pieper

Year: 2011 | Conference Paper |

Ontological Labels for Automated Location of Left Ventricular Remodeling

Shane Steinert-Threlkeld;Siamak Ardekani;Jose L.V. Mejino;Landon T. Detwiler;James F. Brinkley;Michael Halle;Ron Kikinis;Raimond L. Winslow;Michael I. Miller;J. Tilak Ratnanather

2011 IEEE Fifth International Conference on Semantic Computing
Year: 2011 | Conference Paper |
In a previous study, Ardekani et. al. used the Large Deformation Diffeomorphic Metric Mapping (LDDMM) image registration algorithm to analyze the left ventricle of 25 human subjects at both end systole (ES) and end diastole (ED) phases of the cardiac cycle. Of these 25 subjects, 12 had nonischemic cardiomyopathy (NICM) and 13 had ischemic cardiomyopathy (ICM). An average template image at each of ...Show More

Ontological Labels for Automated Location of Left Ventricular Remodeling

Shane Steinert-Threlkeld;Siamak Ardekani;Jose L.V. Mejino;Landon T. Detwiler;James F. Brinkley;Michael Halle;Ron Kikinis;Raimond L. Winslow;Michael I. Miller;J. Tilak Ratnanather

Year: 2011 | Conference Paper |

Real-Time Non-rigid Registration of Medical Images on a Cooperative Parallel Architecture

Yixun Liu;Andriy Fedorov;Ron Kikinis;Nikos Chrisochoides

2009 IEEE International Conference on Bioinformatics and Biomedicine
Year: 2009 | Conference Paper |
Cited by: Papers (8)
Unacceptable execution time of Non-rigid registration (NRR) often presents a major obstacle to its routine clinical use. Parallel computing is an effective way to accelerate NRR. However, development of efficient parallel NRR codes is a very challenging task. One desirable approach is to map the existing sequential algorithm to the parallel architecture to gain speedup instead of designing a new p...Show More

Real-Time Non-rigid Registration of Medical Images on a Cooperative Parallel Architecture

Yixun Liu;Andriy Fedorov;Ron Kikinis;Nikos Chrisochoides

Year: 2009 | Conference Paper |

Monitoring slowly evolving tumors

E. Konukoglu;W. M. Wells;S. Novellas;N. Ayache;R. Kikinis;P. M. Black;K. M. Pohl

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Year: 2008 | Conference Paper |
Change detection is a critical task in the diagnosis of many slowly evolving pathologies. This paper describes an approach that semi-automatically performs this task using longitudinal medical images. We are specifically interested in meningiomas, which experts often find difficult to monitor as the tumor evolution can be obscured by image artifacts. We test the method on synthetic data with known...Show More

Monitoring slowly evolving tumors

E. Konukoglu;W. M. Wells;S. Novellas;N. Ayache;R. Kikinis;P. M. Black;K. M. Pohl

Year: 2008 | Conference Paper |

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