Model library for deformable model-based segmentation of 3-D brain MR-images

Juha Koikkalainen, Jyrki Lötjönen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

5 Citations (Scopus)

Abstract

A novel method to use model libraries in segmentation is introduced. Using similarity measures one model from model library is selected. This model is then used in model-based segmentation. The proposed method is simple, straightforward and fast. Various similarity measures, both voxel and edge measures, were examined. Two different segmentation methods were used for validating the functionality of the proposed procedure. Results show that a statistically significant improvement in segmentation accuracy was achieved in each study case.
Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention
Subtitle of host publicationMICCAI 2002
PublisherSpringer
Pages540-547
ISBN (Electronic)978-3-540-45786-2
ISBN (Print)978-3-540-44224-0
DOIs
Publication statusPublished - 2002
MoE publication typeA4 Article in a conference publication
Event5th International Conference on Medical Imagae Computing and Computer-Assisted Intervention (MICCAI 2002) - Tokyo, Japan
Duration: 25 Sep 200228 Sep 2002
Conference number: 5

Publication series

SeriesLecture Notes in Computer Science
Volume2488
ISSN0302-9743

Conference

Conference5th International Conference on Medical Imagae Computing and Computer-Assisted Intervention (MICCAI 2002)
Abbreviated titleMICCAI 2002
CountryJapan
CityTokyo
Period25/09/0228/09/02

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Koikkalainen, J., & Lötjönen, J. (2002). Model library for deformable model-based segmentation of 3-D brain MR-images. In Medical Image Computing and Computer-Assisted Intervention: MICCAI 2002 (pp. 540-547). Springer. Lecture Notes in Computer Science, Vol.. 2488 https://doi.org/10.1007/3-540-45786-0_67
Koikkalainen, Juha ; Lötjönen, Jyrki. / Model library for deformable model-based segmentation of 3-D brain MR-images. Medical Image Computing and Computer-Assisted Intervention: MICCAI 2002. Springer, 2002. pp. 540-547 (Lecture Notes in Computer Science, Vol. 2488).
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abstract = "A novel method to use model libraries in segmentation is introduced. Using similarity measures one model from model library is selected. This model is then used in model-based segmentation. The proposed method is simple, straightforward and fast. Various similarity measures, both voxel and edge measures, were examined. Two different segmentation methods were used for validating the functionality of the proposed procedure. Results show that a statistically significant improvement in segmentation accuracy was achieved in each study case.",
author = "Juha Koikkalainen and Jyrki L{\"o}tj{\"o}nen",
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Koikkalainen, J & Lötjönen, J 2002, Model library for deformable model-based segmentation of 3-D brain MR-images. in Medical Image Computing and Computer-Assisted Intervention: MICCAI 2002. Springer, Lecture Notes in Computer Science, vol. 2488, pp. 540-547, 5th International Conference on Medical Imagae Computing and Computer-Assisted Intervention (MICCAI 2002), Tokyo, Japan, 25/09/02. https://doi.org/10.1007/3-540-45786-0_67

Model library for deformable model-based segmentation of 3-D brain MR-images. / Koikkalainen, Juha; Lötjönen, Jyrki.

Medical Image Computing and Computer-Assisted Intervention: MICCAI 2002. Springer, 2002. p. 540-547 (Lecture Notes in Computer Science, Vol. 2488).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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AB - A novel method to use model libraries in segmentation is introduced. Using similarity measures one model from model library is selected. This model is then used in model-based segmentation. The proposed method is simple, straightforward and fast. Various similarity measures, both voxel and edge measures, were examined. Two different segmentation methods were used for validating the functionality of the proposed procedure. Results show that a statistically significant improvement in segmentation accuracy was achieved in each study case.

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Koikkalainen J, Lötjönen J. Model library for deformable model-based segmentation of 3-D brain MR-images. In Medical Image Computing and Computer-Assisted Intervention: MICCAI 2002. Springer. 2002. p. 540-547. (Lecture Notes in Computer Science, Vol. 2488). https://doi.org/10.1007/3-540-45786-0_67