Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT

Dirk-Jan Kroon, Cornelis H. Slump, Thomas J.J. Maal

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

44 Citations (Scopus)
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Abstract

Cone-beam computed tomography (CBCT) is an important image modality for dental surgery planning, with high resolution images at a relative low radiation dose. In these scans the mandibular canal is hardly visible, this is a problem for implant surgery planning. We use anisotropic diffusion filtering to remove noise and enhance the mandibular canal in CBCT scans. For the diffusion tensor we use hybrid diffusion with a continuous switch (HDCS), suitable for filtering both tubular as planar image structures. We focus in this paper on the diffusion discretization schemes. The standard scheme shows good isotropic filtering behavior but is not rotational invariant, the diffusion scheme of Weickert is rotational invariant but suffers from checkerboard artifacts. We introduce a new scheme, in which we numerically optimize the image derivatives. This scheme is rotational invariant and shows good isotropic filtering properties on both synthetic as real CBCT data.
Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2010
Subtitle of host publication13th International Conference, Beijing, China, September 20-24, 2010: Proceedings
EditorsTianzi Jiang, Nassir Navab, Josien P.W. Pluim, Max A. Viergever
Place of PublicationBerlin
PublisherSpringer
Pages221-228
Number of pages8
ISBN (Electronic)978-3-642-15711-0
ISBN (Print)978-3-642-15710-3
DOIs
Publication statusPublished - 17 Sep 2010
Event13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 - Beijing, China, China
Duration: 20 Sep 201024 Sep 2010
Conference number: 13

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume6363
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
Abbreviated titleMICCAI
CountryChina
CityBeijing, China
Period20/09/1024/09/10

Fingerprint

Cones
Tomography
Canals
Surgery
Planning
Image resolution
Dosimetry
Tensors
Switches
Derivatives

Keywords

  • METIS-275683
  • CBCT
  • Cone Beam Computed tomography
  • EWI-18677
  • anisotropic Diffusion filtering
  • Image Processing
  • discretization scheme
  • IR-74098

Cite this

Kroon, D-J., Slump, C. H., & Maal, T. J. J. (2010). Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT. In T. Jiang, N. Navab, J. P. W. Pluim, & M. A. Viergever (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010: Proceedings (pp. 221-228). (Lecture Notes in Computer Science; Vol. 6363). Berlin: Springer. https://doi.org/10.1007/978-3-642-15711-0_28
Kroon, Dirk-Jan ; Slump, Cornelis H. ; Maal, Thomas J.J. / Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010: Proceedings. editor / Tianzi Jiang ; Nassir Navab ; Josien P.W. Pluim ; Max A. Viergever. Berlin : Springer, 2010. pp. 221-228 (Lecture Notes in Computer Science).
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abstract = "Cone-beam computed tomography (CBCT) is an important image modality for dental surgery planning, with high resolution images at a relative low radiation dose. In these scans the mandibular canal is hardly visible, this is a problem for implant surgery planning. We use anisotropic diffusion filtering to remove noise and enhance the mandibular canal in CBCT scans. For the diffusion tensor we use hybrid diffusion with a continuous switch (HDCS), suitable for filtering both tubular as planar image structures. We focus in this paper on the diffusion discretization schemes. The standard scheme shows good isotropic filtering behavior but is not rotational invariant, the diffusion scheme of Weickert is rotational invariant but suffers from checkerboard artifacts. We introduce a new scheme, in which we numerically optimize the image derivatives. This scheme is rotational invariant and shows good isotropic filtering properties on both synthetic as real CBCT data.",
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Kroon, D-J, Slump, CH & Maal, TJJ 2010, Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT. in T Jiang, N Navab, JPW Pluim & MA Viergever (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010: Proceedings. Lecture Notes in Computer Science, vol. 6363, Springer, Berlin, pp. 221-228, 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010, Beijing, China, China, 20/09/10. https://doi.org/10.1007/978-3-642-15711-0_28

Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT. / Kroon, Dirk-Jan; Slump, Cornelis H.; Maal, Thomas J.J.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010: Proceedings. ed. / Tianzi Jiang; Nassir Navab; Josien P.W. Pluim; Max A. Viergever. Berlin : Springer, 2010. p. 221-228 (Lecture Notes in Computer Science; Vol. 6363).

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

TY - GEN

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AU - Slump, Cornelis H.

AU - Maal, Thomas J.J.

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Y1 - 2010/9/17

N2 - Cone-beam computed tomography (CBCT) is an important image modality for dental surgery planning, with high resolution images at a relative low radiation dose. In these scans the mandibular canal is hardly visible, this is a problem for implant surgery planning. We use anisotropic diffusion filtering to remove noise and enhance the mandibular canal in CBCT scans. For the diffusion tensor we use hybrid diffusion with a continuous switch (HDCS), suitable for filtering both tubular as planar image structures. We focus in this paper on the diffusion discretization schemes. The standard scheme shows good isotropic filtering behavior but is not rotational invariant, the diffusion scheme of Weickert is rotational invariant but suffers from checkerboard artifacts. We introduce a new scheme, in which we numerically optimize the image derivatives. This scheme is rotational invariant and shows good isotropic filtering properties on both synthetic as real CBCT data.

AB - Cone-beam computed tomography (CBCT) is an important image modality for dental surgery planning, with high resolution images at a relative low radiation dose. In these scans the mandibular canal is hardly visible, this is a problem for implant surgery planning. We use anisotropic diffusion filtering to remove noise and enhance the mandibular canal in CBCT scans. For the diffusion tensor we use hybrid diffusion with a continuous switch (HDCS), suitable for filtering both tubular as planar image structures. We focus in this paper on the diffusion discretization schemes. The standard scheme shows good isotropic filtering behavior but is not rotational invariant, the diffusion scheme of Weickert is rotational invariant but suffers from checkerboard artifacts. We introduce a new scheme, in which we numerically optimize the image derivatives. This scheme is rotational invariant and shows good isotropic filtering properties on both synthetic as real CBCT data.

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KW - IR-74098

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BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010

A2 - Jiang, Tianzi

A2 - Navab, Nassir

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A2 - Viergever, Max A.

PB - Springer

CY - Berlin

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Kroon D-J, Slump CH, Maal TJJ. Optimized Anisotropic Rotational Invariant Diffusion Scheme on Cone-Beam CT. In Jiang T, Navab N, Pluim JPW, Viergever MA, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010: Proceedings. Berlin: Springer. 2010. p. 221-228. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-642-15711-0_28