Spherical Object Reconstruction Using Star-Shaped Simplex
Meshes

D 2001

Spherical Object Reconstruction Using Star-Shaped Simplex Meshes

MATULA, Pavel and David SVOBODA

Basic information

Original name

Spherical Object Reconstruction Using Star-Shaped Simplex Meshes

Authors

MATULA, Pavel (203 Czech Republic, guarantor) and David SVOBODA (203 Czech Republic)

Edition

Berlin, Heidelberg, New York, Energy Minimization Methods in Computer Vision and Pattern Recognition, p. 608-620, 2001

Publisher

Springer-Verlag

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

RIV identification code

RIV/00216224:14330/01:00004584

Organization unit

Faculty of Informatics

ISBN

3-540-42523-3

UT WoS

000180456900040

Keywords in English

Simplex meshes; object reconstruction; cell nuclei segmentation

Abstract

V originále

Spherical object reconstruction is of great importance, especially in the field of cell biology, since cells as well as cell nuclei mostly have the shape of a deformed sphere. Fast, reliable and precise procedure is needed for automatic measuring of topographical parameters of the large number of cells or cell nuclei. This paper presents a new method for spherical object reconstruction. The method springs from Delingette general object reconstruction algorithm which is based on the deformation of simplex meshes. However, the unknown surface is searched only within the subclass of simplex meshes, which have the shape of a star. Star-shaped simplex meshes are suitable for modelling of spherical or ellipsoidal objects. In our approach, the law of motion was altered so that it preserves the star-shape during deformation. The proposed method is easier than the general method and therefore faster. In addition, it uses more computationally stable expressions than a method, strictly implemented according to Delingette's paper. It is also shown how to partly avoid the occasional instability of the Delingette method. The accuracy of both methods is comparable. The star-shaped method achieves a stable state more often.

Links

IBS5004010, research and development project

Name: Vývoj nových diagnostických technik pro onkologii

Investor: Academy of Sciences of the Czech Republic, Development of new diagnostic teniques for oncology

MSM 143300002, plan (intention)

Name: Využití počítačové analýzy obrazu v optické mikroskopii

Investor: Ministry of Education, Youth and Sports of the CR, Application of computer image analysis in optical microscopy

Citovat

MATULA, Pavel and David SVOBODA. Spherical Object Reconstruction Using Star-Shaped Simplex Meshes. In Energy Minimization Methods in Computer Vision and Pattern Recognition. Berlin, Heidelberg, New York: Springer-Verlag, 2001, p. 608-620. ISBN 3-540-42523-3.

@inproceedings{372994,
   author = {Matula, Pavel and Svoboda, David},
   address = {Berlin, Heidelberg, New York},
   booktitle = {Energy Minimization Methods in Computer Vision and Pattern Recognition},
   keywords = {Simplex meshes; object reconstruction; cell nuclei segmentation},
   language = {eng},
   location = {Berlin, Heidelberg, New York},
   isbn = {3-540-42523-3},
   note = {LNCS 2134},
   pages = {608-620},
   publisher = {Springer-Verlag},
   title = {Spherical Object Reconstruction Using Star-Shaped Simplex Meshes},
   url = {http://dx.doi.org/10.1007/3-540-44745-8_40},
   year = {2001}
}

TY  - JOUR
ID  - 372994
AU  - Matula, Pavel - Svoboda, David
PY  - 2001
TI  - Spherical Object Reconstruction Using Star-Shaped Simplex Meshes
PB  - Springer-Verlag
CY  - Berlin, Heidelberg, New York
SN  - 3540425233
N1  - LNCS 2134
KW  - Simplex meshes
KW  - object reconstruction
KW  - cell nuclei segmentation
UR  - http://dx.doi.org/10.1007/3-540-44745-8_40
N2  - Spherical object reconstruction is of great importance, especially in the field of cell biology, since cells as well as cell nuclei mostly have the shape of a deformed sphere. Fast, reliable and precise procedure is needed for automatic measuring of topographical parameters of the large number of cells or cell nuclei. This paper presents a new method for spherical object reconstruction. The method springs from Delingette general object reconstruction algorithm which is based on the deformation of simplex meshes. However, the unknown surface is searched only within the subclass of simplex meshes, which have the shape of a star. Star-shaped simplex meshes are suitable for modelling of spherical or ellipsoidal objects. In our approach, the law of motion was altered so that it preserves the star-shape during deformation. The proposed method is easier than the general method and therefore faster. In addition, it uses more computationally stable expressions than a method, strictly implemented according to Delingette's paper. It is also shown how to partly avoid the occasional instability of the Delingette method. The accuracy of both methods is comparable. The star-shaped method achieves a stable state more often.
ER  -

MATULA, Pavel and David SVOBODA. Spherical Object Reconstruction Using Star-Shaped Simplex Meshes. In \textit{Energy Minimization Methods in Computer Vision and Pattern Recognition}. Berlin, Heidelberg, New York: Springer-Verlag, 2001, p.~608-620. ISBN~3-540-42523-3.

Detailed Information on Publication Record