An algorithmic overview of surface registration techniques for medical imaging

Audette, Michel; Ferrie, Frank P.; Peters, Terry M.

doi:10.1016/s1361-8415(00)00014-1

Cited by 352 publications

(208 citation statements)

References 76 publications

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“…Various automatic registration methods are conceivable 26, 27, 28 and should be compared particularly in terms of their applicability to patient data. In this phantom study, we have selected the rigid coherent point drift registration (CPD),29 which only translates and rotates the dataset of the determined dwell positions by an iterative registration routine minimizing the 3D distance of the dwell position pairs.…”

Section: Methodsmentioning

confidence: 99%

Electromagnetic tracking (EMT) technology for improved treatment quality assurance in interstitial brachytherapy

Kellermeier

Herbolzheimer

Kreppner

et al. 2017

J Applied Clin Med Phys

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Electromagnetic Tracking (EMT) is a novel technique for error detection and quality assurance (QA) in interstitial high dose rate brachytherapy (HDR‐iBT). The purpose of this study is to provide a concept for data acquisition developed as part of a clinical evaluation study on the use of EMT during interstitial treatment of breast cancer patients. The stability, accuracy, and precision of EMT‐determined dwell positions were quantified. Dwell position reconstruction based on EMT was investigated on CT table, HDR table and PDR bed to examine the influence on precision and accuracy in a typical clinical workflow. All investigations were performed using a precise PMMA phantom. The track of catheters inserted in that phantom was measured by manually inserting a 5 degree of freedom (DoF) sensor while recording the position of three 6DoF fiducial sensors on the phantom surface to correct motion influences. From the corrected data, dwell positions were reconstructed along the catheter's track. The accuracy of the EMT‐determined dwell positions was quantified by the residual distances to reference dwell positions after using a rigid registration. Precision and accuracy were investigated for different phantom‐table and sensor‐field generator (FG) distances. The measured precision of the EMT‐determined dwell positions was ≤ 0.28 mm (95th percentile). Stability tests showed a drift of 0.03 mm in the first 20 min of use. Sudden shaking of the FG or (large) metallic objects close to the FG degrade the precision. The accuracy with respect to the reference dwell positions was on all clinical tables < 1 mm at 200 mm FG distance and 120 mm phantom‐table distance. Phantom measurements showed that EMT‐determined localization of dwell positions in HDR‐iBT is stable, precise, and sufficiently accurate for clinical assessment. The presented method may be viable for clinical applications in HDR‐iBT, like implant definition, error detection or quantification of uncertainties. Further clinical investigations are needed.

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Section: Methodsmentioning

confidence: 99%

Electromagnetic tracking (EMT) technology for improved treatment quality assurance in interstitial brachytherapy

Kellermeier

Herbolzheimer

Kreppner

et al. 2017

J Applied Clin Med Phys

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“…Automatic selection of correspondences for nonparametric shape representations has been explored in the context of surface registration [6], but because such methods are typically limited to pairwise correspondences and assume a fixed set of surface point samples, they are not su cient for the analysis of sets of segmented volumes. While the sliding landmark method of Dalal, et al does not assume fixed surface correspondences, it still relies on a pair-wise registrations to a fixed template, which must be chosen by another procedure in advance.…”

Section: Shape Representationmentioning

confidence: 99%

Shape Modeling and Analysis with Entropy-Based Particle Systems

Cates

Fletcher

Styner

et al. 2007

Lecture Notes in Computer Science

139

224

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Many important fields of basic research in medicine and biology routinely employ tools for the statistical analysis of collections of similar shapes. Biologists, for example, have long relied on homologous, anatomical landmarks as shape models to characterize the growth and development of species. Increasingly, however, researchers are exploring the use of more detailed models that are derived computationally from three-dimensional images and surface descriptions. While computationally-derived models of shape are promising new tools for biomedical research, they also present some significant engineering challenges, which existing modeling methods have only begun to address.In this dissertation, I propose a new computational framework for statistical shape modeling that significantly advances the state-of-the-art by overcoming many of the limitations of existing methods. The framework uses a particle-system representation of shape, with a fast correspondence-point optimization based on information content. The optimization balances the simplicity of the model (compactness) with the accuracy of the shape representations by using two commensurate entropy metrics and no free parameters. The idea is to maximize both the geometric accuracy and the statistical simplicity of the shape model, in accordance with the principle of parsimony in model selection. The nonparametric representation allows the method to be applied to a larger class of problems than existing methods, including nonspherical surfaces, open surfaces, and sets of multiple surfaces.The relative simplicity of the surface representation and the low number of free parameters results in a framework that is easy to use and can operate directly on image segmentations. In collaboration with scientists from several important areas of biomedicine, I have demonstrated that the proposed method is indeed an e↵ective tool for scientific research.The specific research contributions of this dissertation are as follows. First, I describe a mathematical framework and a robust numerical algorithm for computing optimized correspondence-point shape models using an entropy-based optimization and particle-system technology. Second, I develop a series of extensions of the framework to more general classes of shape analysis problems, including the analysis of multiple-object complexes, the generalization to correspondence based on generic functions of position, an extension to handle surfaces with open boundaries, and shape modeling with simple regression. Third, I describe the application of statistical hypothesis testing, regression analysis, and multiple-analysis of covariance to the proposed shape models. I also introduce new techniques for visualization and interpretation of these statistics. Finally, in cooperation with biomedical researchers, I present validation of the above research contributions by their successful application to real-world research problems.

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“…The majority of (semi-) automatic approaches for registering the endoscopic image data with 3D anatomical data acquired pre-or intra-operatively are either marker-based (Baumhauer et al, 2008;Falk et al, 2005;Ieiri et al, 2011;Marvik et al, 2004;Megali et al, 2008;Mourgues et al, 2003;Simpfendorfer et al, 2011;Suzuki et al, 2008) or use external tracking devices that are initially calibrated with respect to the imaging modality (Ukimura and Gill, 2008;Konishi et al, 2007;Shekhar et al, 2010;Feuerstein et al, 2008;Konishi et al, 2007;Feuerstein et al, 2007;Leven et al, 2005;Blackall et al, 2000)). In an alternative approach, reconstructed surface data may be used to perform the registration with pre-operative models (Audette et al, 2000). Comprehensive reviews on shape matching in general have been published by the computer vision community (cf.…”

Section: Intra-operative Registration For Augmented Reality Guidancementioning

confidence: 99%

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

Maier-Hein

Mountney

Bartoli

et al. 2013

Medical Image Analysis

242

130

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One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-operative morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon's navigation capabilites by observing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted instruments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D optical imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions.

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An algorithmic overview of surface registration techniques for medical imaging

Cited by 352 publications

References 76 publications

Electromagnetic tracking (EMT) technology for improved treatment quality assurance in interstitial brachytherapy

Electromagnetic tracking (EMT) technology for improved treatment quality assurance in interstitial brachytherapy

Shape Modeling and Analysis with Entropy-Based Particle Systems

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

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