Least biased target selection in probabilistic atlas construction

Hyunjin Park; Peyton H. Bland; Alfred O. Hero; Charles R. Meyer

doi:10.1007/11566489_52

Least biased target selection in probabilistic atlas construction

Hyunjin Park
, Peyton H. Bland
, Alfred O. Hero
, Charles R. Meyer

University of Michigan, Ann Arbor

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

68 Scopus citations

Abstract

Probabilistic atlas has broad applications in medical image segmentation and registration. The most common problem building a probabilistic atlas is picking a target image upon which to map the rest of the training images. Here we present a method to choose a target image that is the closest to the mean geometry of the population under consideration as determined by bending energy. Our approach is based on forming a distance matrix based on bending energies of all pair-wise registrations and performing multidimensional scaling (MDS) on the distance matrix.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings
Publisher	Springer Verlag
Pages	419-426
Number of pages	8
ISBN (Print)	3540293264, 9783540293262
DOIs	https://doi.org/10.1007/11566489_52
State	Published - 2005
Externally published	Yes
Event	8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - Palm Springs, CA, United States Duration: 26 Oct 2005 → 29 Oct 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3750 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005
Country/Territory	United States
City	Palm Springs, CA
Period	26/10/05 → 29/10/05

Access to Document

10.1007/11566489_52

Cite this

Park, H., Bland, P. H., Hero, A. O., & Meyer, C. R. (2005). Least biased target selection in probabilistic atlas construction. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings (pp. 419-426). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3750 LNCS). Springer Verlag. https://doi.org/10.1007/11566489_52

Park, Hyunjin ; Bland, Peyton H. ; Hero, Alfred O. et al. / Least biased target selection in probabilistic atlas construction. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. Springer Verlag, 2005. pp. 419-426 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{f72ffc2bf2db44f897466db3f6f9c878,

title = "Least biased target selection in probabilistic atlas construction",

abstract = "Probabilistic atlas has broad applications in medical image segmentation and registration. The most common problem building a probabilistic atlas is picking a target image upon which to map the rest of the training images. Here we present a method to choose a target image that is the closest to the mean geometry of the population under consideration as determined by bending energy. Our approach is based on forming a distance matrix based on bending energies of all pair-wise registrations and performing multidimensional scaling (MDS) on the distance matrix.",

author = "Hyunjin Park and Bland, \{Peyton H.\} and Hero, \{Alfred O.\} and Meyer, \{Charles R.\}",

year = "2005",

doi = "10.1007/11566489\_52",

language = "English",

isbn = "3540293264",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "419--426",

booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings",

note = "8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 ; Conference date: 26-10-2005 Through 29-10-2005",

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Park, H, Bland, PH, Hero, AO & Meyer, CR 2005, Least biased target selection in probabilistic atlas construction. in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3750 LNCS, Springer Verlag, pp. 419-426, 8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005, Palm Springs, CA, United States, 26/10/05. https://doi.org/10.1007/11566489_52

Least biased target selection in probabilistic atlas construction. / Park, Hyunjin; Bland, Peyton H.; Hero, Alfred O. et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. Springer Verlag, 2005. p. 419-426 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3750 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Hero, Alfred O.

AU - Meyer, Charles R.

PY - 2005

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N2 - Probabilistic atlas has broad applications in medical image segmentation and registration. The most common problem building a probabilistic atlas is picking a target image upon which to map the rest of the training images. Here we present a method to choose a target image that is the closest to the mean geometry of the population under consideration as determined by bending energy. Our approach is based on forming a distance matrix based on bending energies of all pair-wise registrations and performing multidimensional scaling (MDS) on the distance matrix.

AB - Probabilistic atlas has broad applications in medical image segmentation and registration. The most common problem building a probabilistic atlas is picking a target image upon which to map the rest of the training images. Here we present a method to choose a target image that is the closest to the mean geometry of the population under consideration as determined by bending energy. Our approach is based on forming a distance matrix based on bending energies of all pair-wise registrations and performing multidimensional scaling (MDS) on the distance matrix.

UR - https://www.scopus.com/pages/publications/33744819488

U2 - 10.1007/11566489_52

DO - 10.1007/11566489_52

M3 - Conference contribution

C2 - 16685987

AN - SCOPUS:33744819488

SN - 3540293264

SN - 9783540293262

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 419

EP - 426

BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings

PB - Springer Verlag

T2 - 8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005

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ER -

Park H, Bland PH, Hero AO, Meyer CR. Least biased target selection in probabilistic atlas construction. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. Springer Verlag. 2005. p. 419-426. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11566489_52

Least biased target selection in probabilistic atlas construction

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