Volume-specific parameter optimization of 3D local phase features for improved extraction of bone surfaces in ultrasound
Background Accurate localization of bone surfaces remains a challenge hampering adoption of ultrasound guidance in computer‐assisted orthopaedic surgery. Local phase image features have recently been proven efficacious for segmenting bone surfaces from ultrasound images, but the quality of the proce...
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Published in | The international journal of medical robotics + computer assisted surgery Vol. 10; no. 4; pp. 461 - 473 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
Blackwell Publishing Ltd
01.12.2014
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | Background
Accurate localization of bone surfaces remains a challenge hampering adoption of ultrasound guidance in computer‐assisted orthopaedic surgery. Local phase image features have recently been proven efficacious for segmenting bone surfaces from ultrasound images, but the quality of the processing depends on numerous filter parameters that are currently set through a trial and error process that is tedious, unintuitive and subject to large inter‐user variability.
Methods
A method is presented for automatically selecting parameters of Log‐Gabor filters used to extract bone surfaces from 3D ultrasound volumes that is based on properties estimated directly from the specific image.
Results
A 15% and 69% average improvement in bone surface localization accuracy on phantom and clinical data, respectively, is demonstrated compared with empirically‐set parameters.
Conclusions
These findings imply that Log‐Gabor filter parameter optimization is necessary for accurate extraction of bone surfaces from ultrasound data. Copyright © 2014 John Wiley & Sons, Ltd. |
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Bibliography: | ark:/67375/WNG-0RDJ6LGT-B istex:B65B44DF7611D1C967C5DB6BE66CB557C2091FE5 ArticleID:RCS1552 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1478-5951 1478-596X 1478-596X |
DOI: | 10.1002/rcs.1552 |