Effective quantum dust collapse via surface matching

AbstractStudying the changes of shape is a common concern in many scientific fields. We address here two problems: (1) quantifying the deformation between two given shapes and (2) transporting this deformation to morph a third shape. These operations can be done with or without point correspondence, depending on the availability of a surface matching algorithm, and on the type of mathematical procedure adopted. In computer vision, the re-targeting of emotions mapped on faces is a common application. We contrast here four different methods used for transporting the deformation toward a target once it was estimated upon the matching of two shapes. These methods come from very different fields such as computational anatomy, computer vision and biology. We used the large diffeomorphic deformation metric mapping and thin plate spline, in order to estimate deformations in a deformational trajectory of a human face experiencing different emotions. Then we use naive transport (NT), linear shift (LS), direct transport (DT) and fanning scheme (FS) to transport the estimated deformations toward four alien faces constituted by 240 homologous points and identifying a triangulation structure of 416 triangles. We used both local and global criteria for evaluating the performance of the 4 methods, e.g., the maintenance of the original deformation. We found DT, LS and FS very effective in recovering the original deformation while NT fails under several aspects in transporting the shape change. As the best method may differ depending on the application, we recommend carefully testing different methods in order to choose the best one for any specific application.

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A Numerical Framework for Elastic Surface Matching, Comparison, and Interpolation

International Journal of Computer Vision ◽

10.1007/s11263-021-01476-6 ◽

2021 ◽

Author(s):

Martin Bauer ◽

Nicolas Charon ◽

Philipp Harms ◽

Hsi-Wei Hsieh

Keyword(s):

Surface Matching ◽

Elastic Surface

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Structure prediction of epitaxial inorganic interfaces by lattice and surface matching with Ogre

The Journal of Chemical Physics ◽

10.1063/5.0051343 ◽

2021 ◽

Vol 155 (3) ◽

pp. 034111

Author(s):

Saeed Moayedpour ◽

Derek Dardzinski ◽

Shuyang Yang ◽

Andrea Hwang ◽

Noa Marom

Keyword(s):

Structure Prediction ◽

Surface Matching

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Fast Nonsupervised 3D Registration of PET and MR Images of the Brain

Journal of Cerebral Blood Flow & Metabolism ◽

10.1038/jcbfm.1994.96 ◽

1994 ◽

Vol 14 (5) ◽

pp. 749-762 ◽

Cited By ~ 66

Author(s):

Jean-François Mangin ◽

Vincent Frouin ◽

Isabelle Bloch ◽

Bernard Bendriem ◽

Jaime Lopez-Krahe

Keyword(s):

Three Dimensional ◽

Magnetic Resonance Images ◽

Surface Matching ◽

3D Registration ◽

Matching Algorithm ◽

Distance Map ◽

Brain Surface ◽

Discrete Surfaces ◽

Positron Emission ◽

The Brain

We propose a fully nonsupervised methodology dedicated to the fast registration of positron emission tomography (PET) and magnetic resonance images of the brain. First, discrete representations of the surfaces of interest (head or brain surface) are automatically extracted from both images. Then, a shape-independent surface-matching algorithm gives a rigid body transformation, which allows the transfer of information between both modalities. A three-dimensional (3D) extension of the chamfer-matching principle makes up the core of this surface-matching algorithm. The optimal transformation is inferred from the minimization of a quadratic generalized distance between discrete surfaces, taking into account between-modality differences in the localization of the segmented surfaces. The minimization process is efficiently performed via the precomputation of a 3D distance map. Validation studies using a dedicated brain-shaped phantom have shown that the maximum registration error was of the order of the PET pixel size (2 mm) for the wide variety of tested configurations. The software is routinely used today in a clinical context by the physicians of the Service Hospitalier Frédéric Joliot (>150 registrations performed). The entire registration process requires ∼5 min on a conventional workstation.

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Surface-based analysis of cortical thickness and volume loss in Alzheimer’s disease

Proceedings of IMPRS ◽

10.18060/23524 ◽

2019 ◽

Vol 2 (1) ◽

Author(s):

Emily Iannopollo ◽

Ryan Plunkett ◽

Kara Garcia

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Magnetic Resonance ◽

Cortical Thickness ◽

Surface Matching ◽

Cortical Surface ◽

Volume Loss ◽

Cortical Volume ◽

Human Connectome Project ◽

And Control

Background and Hypothesis: Magnetic resonance imaging (MRI) has become a useful tool in monitoring the progression of Alzheimer's disease. Previous surface-based analysis has focused on changes in cortical thickness associated with the disease1. The objective of this study is to analyze MRI-derived cortical reconstructions for patterns of atrophy in terms of both cortical thickness and cortical volume. We hypothesize that Alzheimer’s Disease progression will be associated with a more significant change in volume than thickness. Experimental Design or Project Methods: MRI data was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). All subjects with baseline and two-year 3T MRI scans were included. Segmentation of MRIs into gray and white matter was performed with FreeSurfer2,3,4,5. Subjects whose scans did not segment accurately were excluded. Surfaces were then registered to a common atlas with Ciftify6, and anatomically-constrained Multimodal Surface Matching (aMSM) was used to analyze longitudinal changes in each subject7. This produced continuous surface maps showing changes in cortical surface area and thickness. These maps were multiplied to create cortical volume maps8. Permutation Analysis of Linear Models (PALM) was used to perform two-sample t-tests comparing the maps of the Alzheimer’s and control groups9. Results: Preliminary analysis of nine Alzheimer’s subjects and nine control subjects produced surface maps displaying patterns that were expected given previous research findings10,11. There was increased volume and thickness loss in Alzheimer’s subjects relative to controls, with relatively high loss in structures of the medial temporal lobe. Future analysis of a larger sample will determine whether statistically significant differences exist between the Alzheimer’s and control groups in terms of thickness loss and volume loss. Conclusion and Potential Impact: If significant results are found, surface-based analysis of cortical volume may allow for detection of atrophy at an earlier stage in disease progression than would be possible based on cortical thickness. References 1. Clarkson MJ, Cardoso MJ, Ridgway GR, Modat M, Leung KK, Rohrer JD, Fox NC, Ourselin S. A comparison of voxel and surface based cortical thickness estimation methods. NeuroImage. 2011 Aug 1; 57(3):856-65. 2. Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage. 1999;9:179194. 3. Fischl B, Sereno M, Dale A. Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage. 1999;9:195–207. 4. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002;33:341-355. 5. Fischl B, Salat DH, van der Kouwe AJ, Makris N, Segonne F, Quinn BT, Dale AM. Sequence-independent segmentation of magnetic resonance images. Neuroimage 2004;23 Suppl 1:S69-84. 6. Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, Xu J, Jbabdi S, Webster M, Polimeni JR, Van Essen DC, Jenkinson M, WU-Minn HCP Consortium. The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage. 2013 Oct 15;80:105-24. 7. Robinson EC, Garcia K, Glasser MF, Chen Z, Coalson TS, Makropoulos A, Bozek J, Wright R, Schuh A, Webster M, Hutter J, Price A, Cordero Grande L, Hughes E, Tusor N, Bayly PV, Van Essen DC, Smith SM, Edwards AD, Hajnal J, Jenkinson M, Glocker B, Rueckert D. Multimodal surface matching with higher-order smoothness constraints. Neuroimage. 2018;167:453-65. 8. Marcus DS, Harwell J, Olsen T, Hodge M, Glasser MF, Prior F, Jenkinson M, Laumann T, Curtiss SW, Van Essen DC. Informatics and data mining tools and strategies for the human connectome project. Front Neuroinform 2011;5:4. 9. Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. NeuroImage, 2014;92:381-397 10. Matsuda, H. MRI morphometry in Alzheimer’s disease. Ageing Research Reviews. 2016 Sep;30:17-24. 11. Risacher SL, Shen L, West JD, Kim S, McDonald BC, Beckett LA, Harvey DJ, Jack CR Jr, Weiner MW, Saykin AJ. Alzheimer's Disease Neuroimaging Initiative (ADNI). Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort. Neurobiol Aging. 2010 Aug;31(8):1401-18.

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Robust surface matching by integrating edge segments

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-ii-5-203-2014 ◽

2014 ◽

Vol II-5 ◽

pp. 203-210

Author(s):

N. Kochi ◽

T. Sasaki ◽

K. Kitamura ◽

S. Kaneko

Keyword(s):

High Precision ◽

High Speed ◽

Stereo Matching ◽

Direct Consequence ◽

Surface Matching ◽

Matching Process ◽

Edge Matching ◽

Edge Surface ◽

Image Area ◽

Left Image

This paper describes a novel area-based stereo-matching method which aims at reconstructing the shape of objects robustly, correctly, with high precision and with high density. Our goal is to reconstruct correctly the shape of the object by comprising also edges as part of the resulting surface. For this purpose, we need to overcome the problem of how to reconstruct and describe shapes with steep and sharp edges. Area-based matching methods set an image area as a template and search the corresponding match. As a direct consequence of this approach, it becomes not possible to correctly reconstruct the shape around steep edges. Moreover, in the same regions, discontinuities and discrepancies of the shape between the left and right stereo-images increase the difficulties for the matching process. In order to overcome these problems, we propose in this paper the approach of reconstructing the shape of objects by embedding reliable edge line segments into the area-based matching process with parallax estimation. We propose a robust stereo-matching (the extended Edge TIN-LSM) method which integrates edges and which is able to cope with differences in right and left image shape, brightness changes and occlusions. The method consists of the following three steps: (1) parallax estimation, (2) edge-matching, (3) edge-surface matching. In this paper, we describe and explain in detail the process of parallax estimation and the area-based surface-matching with integrated edges; the performance of the proposed method is also validated. The main advantage of this new method is its ability to reconstruct with high precision a 3D model of an object from only two images (for ex. measurement of a tire with 0.14 mm accuracy), thus without the need of a large number of images. For this reason, this approach is intrinsically simple and high-speed.

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Comparison of surface matching and target matching for image-guided pelvic radiation therapy for both supine and prone patient positions

Journal of Applied Clinical Medical Physics ◽

10.1120/jacmp.v17i3.5611 ◽

2016 ◽

Vol 17 (3) ◽

pp. 14-24 ◽

Cited By ~ 1

Author(s):

Hui Zhao ◽

Brian Wang ◽

Vikren Sarkar ◽

Prema Rassiah-Szegedi ◽

Y. Jessica Huang ◽

...

Keyword(s):

Radiation Therapy ◽

Surface Matching ◽

Pelvic Radiation ◽

Image Guided ◽

Target Matching

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Fast 3D Ear Recognition Based on Local Surface Matching and ICP Registration

2013 5th International Conference on Intelligent Networking and Collaborative Systems ◽

10.1109/incos.2013.141 ◽

2013 ◽

Cited By ~ 3

Author(s):

Heng Liu

Keyword(s):

Surface Matching ◽

Local Surface ◽

Ear Recognition

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Path Planning for Circular Cutter Envelop Milling of Steam Turbine Blade

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.989-994.2908 ◽

2014 ◽

Vol 989-994 ◽

pp. 2908-2912

Author(s):

Jian Jun Wang ◽

Ke Wang ◽

Qiong Wu

Keyword(s):

Steam Turbine ◽

Turbine Blade ◽

Tool Path ◽

Vertical Section ◽

Surface Matching ◽

Nurbs Surface ◽

Processing Efficiency ◽

Tool Paths ◽

Blade Machining ◽

Steam Turbine Blade

In order to solve the problem of poor steam turbine blade processing efficiency, and on the basis of analyzing the turbine blade surface and the existing processing methods, a model of circular cutter turbine blade machining is built. By comparing the tool paths of horizontal and vertical section envelope machining, choosing quasi-vertical cross section envelope machining method and utilizing the original datum and NURBS surface matching mathematic methods, this paper provides an algorithm of residual height calculating, and based on this, the tool path can be planned. Datum show that, the tool path of circular cutter machining blades is much longer than the tool path of ball-end cutter envelop milling machining blades, and the machining efficiency is also highly enhanced.

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