Local contrast‐enhanced MR images via high dynamic range processing.
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| Title: | Local contrast‐enhanced MR images via high dynamic range processing. |
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| Authors: | Chandra, Shekhar S.1 shekhar.chandra@uq.edu.au, Engstrom, Craig2, Fripp, Jurgen1,3, Neubert, Ales3, Jin, Jin1, Walker, Duncan4, Salvado, Olivier1,3, Ho, Charles5, Crozier, Stuart1 |
| Source: | Magnetic Resonance in Medicine. Sep2018, Vol. 80 Issue 3, p1206-1218. 13p. |
| Abstract: | Purpose: To develop a local contrast‐enhancing and feature‐preserving high dynamic range (HDR) image processing algorithm for multichannel and multisequence MR images of multiple body regions and tissues, and to evaluate its performance for structure visualization, bias field (correction) mitigation, and automated tissue segmentation. Methods: A multiscale‐shape and detail‐enhancement HDR‐MRI algorithm is applied to data sets of multichannel and multisequence MR images of the brain, knee, breast, and hip. In multisequence 3T hip images, agreement between automatic cartilage segmentations and corresponding synthesized HDR‐MRI series were computed for mean voxel overlap established from manual segmentations for a series of cases. Qualitative comparisons between the developed HDR‐MRI and standard synthesis methods were performed on multichannel 7T brain and knee data, and multisequence 3T breast and knee data. Results: The synthesized HDR‐MRI series provided excellent enhancement of fine‐scale structure from multiple scales and contrasts, while substantially reducing bias field effects in 7T brain gradient echo, T1 and T2 breast images and 7T knee multichannel images. Evaluation of the HDR‐MRI approach on 3T hip multisequence images showed superior outcomes for automatic cartilage segmentations with respect to manual segmentation, particularly around regions with hyperintense synovial fluid, across a set of 3D sequences. Conclusion: The successful combination of multichannel/sequence MR images into a single‐fused HDR‐MR image format provided consolidated visualization of tissues within 1 omnibus image, enhanced definition of thin, complex anatomical structures in the presence of variable or hyperintense signals, and improved tissue (cartilage) segmentation outcomes. [ABSTRACT FROM AUTHOR] |
| Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 129956287 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Local contrast‐enhanced MR images via high dynamic range processing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chandra%2C+Shekhar+S%2E%22">Chandra, Shekhar S.</searchLink><relatesTo>1</relatesTo><i> shekhar.chandra@uq.edu.au</i><br /><searchLink fieldCode="AR" term="%22Engstrom%2C+Craig%22">Engstrom, Craig</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Fripp%2C+Jurgen%22">Fripp, Jurgen</searchLink><relatesTo>1,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Neubert%2C+Ales%22">Neubert, Ales</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Jin%2C+Jin%22">Jin, Jin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Walker%2C+Duncan%22">Walker, Duncan</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Salvado%2C+Olivier%22">Salvado, Olivier</searchLink><relatesTo>1,3</relatesTo><br /><searchLink fieldCode="AR" term="%22Ho%2C+Charles%22">Ho, Charles</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Crozier%2C+Stuart%22">Crozier, Stuart</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Sep2018, Vol. 80 Issue 3, p1206-1218. 13p. – Name: Abstract Label: Abstract Group: Ab Data: Purpose: To develop a local contrast‐enhancing and feature‐preserving high dynamic range (HDR) image processing algorithm for multichannel and multisequence MR images of multiple body regions and tissues, and to evaluate its performance for structure visualization, bias field (correction) mitigation, and automated tissue segmentation. Methods: A multiscale‐shape and detail‐enhancement HDR‐MRI algorithm is applied to data sets of multichannel and multisequence MR images of the brain, knee, breast, and hip. In multisequence 3T hip images, agreement between automatic cartilage segmentations and corresponding synthesized HDR‐MRI series were computed for mean voxel overlap established from manual segmentations for a series of cases. Qualitative comparisons between the developed HDR‐MRI and standard synthesis methods were performed on multichannel 7T brain and knee data, and multisequence 3T breast and knee data. Results: The synthesized HDR‐MRI series provided excellent enhancement of fine‐scale structure from multiple scales and contrasts, while substantially reducing bias field effects in 7T brain gradient echo, T1 and T2 breast images and 7T knee multichannel images. Evaluation of the HDR‐MRI approach on 3T hip multisequence images showed superior outcomes for automatic cartilage segmentations with respect to manual segmentation, particularly around regions with hyperintense synovial fluid, across a set of 3D sequences. Conclusion: The successful combination of multichannel/sequence MR images into a single‐fused HDR‐MR image format provided consolidated visualization of tissues within 1 omnibus image, enhanced definition of thin, complex anatomical structures in the presence of variable or hyperintense signals, and improved tissue (cartilage) segmentation outcomes. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/mrm.27109 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 1206 Titles: – TitleFull: Local contrast‐enhanced MR images via high dynamic range processing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chandra, Shekhar S. – PersonEntity: Name: NameFull: Engstrom, Craig – PersonEntity: Name: NameFull: Fripp, Jurgen – PersonEntity: Name: NameFull: Neubert, Ales – PersonEntity: Name: NameFull: Jin, Jin – PersonEntity: Name: NameFull: Walker, Duncan – PersonEntity: Name: NameFull: Salvado, Olivier – PersonEntity: Name: NameFull: Ho, Charles – PersonEntity: Name: NameFull: Crozier, Stuart IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 07403194 Numbering: – Type: volume Value: 80 – Type: issue Value: 3 Titles: – TitleFull: Magnetic Resonance in Medicine Type: main |
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