Precise 3D image alignment in micro-axial tomography

J 2003

Precise 3D image alignment in micro-axial tomography

MATULA, Petr, Michal KOZUBEK, Florian STAIER and Michael HAUSMANN

Basic information

Original name

Precise 3D image alignment in micro-axial tomography

Authors

MATULA, Petr (203 Czech Republic, guarantor), Michal KOZUBEK (203 Czech Republic), Florian STAIER (276 Germany) and Michael HAUSMANN (276 Germany)

Edition

Journal of Microscopy, Oxford, Blackwell Science, 2003, 0022-2720

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 1.779

RIV identification code

RIV/00216224:14330/03:00008544

Organization unit

Faculty of Informatics

UT WoS

000181298100008

Keywords in English

assignment; image fusion; image registration; Kuhn-Munkres algorithm; micro-axial tomography; resolution improvement

Abstract

V originále

Micro axial tomography is a challenging technique in microscopy which improves quantitative imaging especially in cytogenetic applications by means of defined sample rotation under the microscope objective. The advantage of micro-axial tomography is an effective improvement of the precision of distance measurements between point-like objects. Under certain circumstances, the effective (3D) resolution can be improved by optimized acquisition depending on subsequent, multi-perspective image recording of the same objects followed by reconstruction methods. This requires, however, a very precise alignment of the tilted views. We present a novel feature-based image alignment method with a precision better than the full width at half maximum of the point spread function. The features are the positions (centres of gravity) of all fluorescent objects observed in the images (e.g. cell nuclei, fluorescent signals inside cell nuclei, fluorescent beads, etc.). Thus, real alignment precision depends on the localization precision of these objects. The method automatically determines the corresponding objects in subsequently tilted perspectives using a weighted bipartite graph. The optimum transformation function is computed in a least squares manner based on the coordinates of the centres of gravity of the matched objects. The theoretically feasible precision of the method was calculated using computer-generated data and confirmed by tests on real image series obtained from data sets of 200 nm fluorescent nano-particles. The advantages of the proposed algorithm are its speed and accuracy, which means that if enough objects are included, the real alignment precision is better than the axial localization precision of a single object. The alignment precision can be assessed directly from the algorithm's output. Thus, the method can be applied not only for image alignment and object matching in tilted view series in order to reconstruct (3D) images, but also to validate the experimental performance (e.g. mechanical precision of the tilting). In practice, the key application of the method is an improvement of the effective spatial (3D) resolution, because the well-known spatial anisotropy in light microscopy can be overcome. This allows more precise distance measurements between point-like objects.

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, Petr, Michal KOZUBEK, Florian STAIER and Michael HAUSMANN. Precise 3D image alignment in micro-axial tomography. Journal of Microscopy. Oxford: Blackwell Science, 2003, vol. 209, No 2, p. 126-142. ISSN 0022-2720.

@article{484897,
   author = {Matula, Petr and Kozubek, Michal and Staier, Florian and Hausmann, Michael},
   article_location = {Oxford},
   article_number = {2},
   keywords = {assignment; image fusion; image registration; Kuhn-Munkres algorithm; micro-axial tomography; resolution improvement},
   language = {eng},
   issn = {0022-2720},
   journal = {Journal of Microscopy},
   title = {Precise 3D image alignment in micro-axial tomography},
   volume = {209},
   year = {2003}
}

TY  - JOUR
ID  - 484897
AU  - Matula, Petr - Kozubek, Michal - Staier, Florian - Hausmann, Michael
PY  - 2003
TI  - Precise 3D image alignment in micro-axial tomography
JF  - Journal of Microscopy
VL  - 209
IS  - 2
SP  - 126
EP  - 126
PB  - Blackwell Science
SN  - 00222720
KW  - assignment
KW  - image fusion
KW  - image registration
KW  - Kuhn-Munkres algorithm
KW  - micro-axial tomography
KW  - resolution improvement
N2  - Micro axial tomography is a challenging technique in microscopy which improves quantitative imaging especially in cytogenetic applications by means of defined sample rotation under the microscope objective. The advantage of micro-axial tomography is an effective improvement of the precision of distance measurements between point-like objects. Under certain circumstances, the effective (3D) resolution can be improved by optimized acquisition depending on subsequent, multi-perspective image recording of the same objects followed by reconstruction methods. This requires, however, a very precise alignment of the tilted views. We present a novel feature-based image alignment method with a precision better than the full width at half maximum of the point spread function. The features are the positions (centres of gravity) of all fluorescent objects observed in the images (e.g. cell nuclei, fluorescent signals inside cell nuclei, fluorescent beads, etc.). Thus, real alignment precision depends on the localization precision of these objects. The method automatically determines the corresponding objects in subsequently tilted perspectives using a weighted bipartite graph. The optimum transformation function is computed in a least squares manner based on the coordinates of the centres of gravity of the matched objects. The theoretically feasible precision of the method was calculated using computer-generated data and confirmed by tests on real image series obtained from data sets of 200 nm fluorescent nano-particles. The advantages of the proposed algorithm are its speed and accuracy, which means that if enough objects are included, the real alignment precision is better than the axial localization precision of a single object. The alignment precision can be assessed directly from the algorithm's output. Thus, the method can be applied not only for image alignment and object matching in tilted view series in order to reconstruct (3D) images, but also to validate the experimental performance (e.g. mechanical precision of the tilting). In practice, the key application of the method is an improvement of the effective spatial (3D) resolution, because the well-known spatial anisotropy in light microscopy can be overcome. This allows more precise distance measurements between point-like objects.
ER  -

MATULA, Petr, Michal KOZUBEK, Florian STAIER and Michael HAUSMANN. Precise 3D image alignment in micro-axial tomography. \textit{Journal of Microscopy}. Oxford: Blackwell Science, 2003, vol.~209, No~2, p.~126-142. ISSN~0022-2720.

Detailed Information on Publication Record