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Probabilistic registration of an unbiased statistical shape model to ultrasound images of the spine. Rasoulian, Abtin; Rohling, Robert N.; Abolmaesumi, Purang
Abstract
The placement of an epidural needle is among the most difficult regional anesthetic techniques. Ultrasound has been proposed to improve success of placement. However, it has not become the standard-of-care because of limitations in the depictions and interpretation of the key anatomical features. We propose to augment the ultrasound images with a registered statistical shape model of the spine to aid interpretation. The model is created with a novel deformable group-wise registration method which utilizes a probabilistic approach to register groups of point sets. The method is compared to a volume-based model building technique and it demonstrates better generalization and compactness. We instantiate and register the shape model to a spine surface probability map extracted from the ultrasound images. Validation is performed on human subjects. The achieved registration accuracy (2-4 mm) is sufficient to guide the choice of puncture site and trajectory of an epidural needle. Copyright 2012 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Item Metadata
Title |
Probabilistic registration of an unbiased statistical shape model to ultrasound images of the spine.
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Creator | |
Publisher |
Society of Photo-Optical Instrumentation Engineers (SPIE)
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Date Issued |
2012
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Description |
The placement of an epidural needle is among the most difficult regional anesthetic techniques. Ultrasound has been proposed
to improve success of placement. However, it has not become the standard-of-care because of limitations in the depictions and
interpretation of the key anatomical features. We propose to augment the ultrasound images with a registered statistical shape
model of the spine to aid interpretation. The model is created with a novel deformable group-wise registration method which
utilizes a probabilistic approach to register groups of point sets. The method is compared to a volume-based model building
technique and it demonstrates better generalization and compactness. We instantiate and register the shape model to a spine
surface probability map extracted from the ultrasound images. Validation is performed on human subjects. The achieved registration
accuracy (2-4 mm) is sufficient to guide the choice of puncture site and trajectory of an epidural needle.
Copyright 2012 Society of Photo-Optical Instrumentation Engineers.
One print or electronic copy may be made for personal use only. Systematic reproduction and distribution,
duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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Genre | |
Type | |
Language |
eng
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Date Available |
2012-03-05
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0107563
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URI | |
Affiliation | |
Citation |
Rasoulian, Abtin; Rohling, Robert N.; Abolmaesumi, Purang. Probabilistic registration of an unbiased statistical shape model to ultrasound images of the spine. Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, edited by David R. Holmes III, Kenneth H. Wong Proceedings of SPIE, Volume 8316, 83161P, 2012.
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Publisher DOI |
10.1117/12.911742
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty
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Copyright Holder |
Rohling, Robert N.
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International