Literature DB >> 28285340

Enhancement of bone shadow region using local phase-based ultrasound transmission maps.

Ilker Hacihaliloglu1,2.   

Abstract

PURPOSE: Ultrasound is increasingly being employed in different orthopedic procedures as an imaging modality for real-time guidance. Nevertheless, low signal-to-noise-ratio and different imaging artifacts continue to hamper the success of ultrasound-based procedures. Bone shadow region is an important feature indicating the presence of bone/tissue interface in the acquired ultrasound data. Enhancement and automatic detection of this region could improve the sensitivity of ultrasound for imaging bone and result in improved guidance for various orthopedic procedures.
METHODS: In this work, a method is introduced for the enhancement of bone shadow regions from B-mode ultrasound data. The method is based on the combination of three different image phase features: local phase tensor, local weighted mean phase angle, and local phase energy. The combined local phase image features are used as an input to an [Formula: see text] norm-based contextual regularization method which emphasizes uncertainty in the shadow regions. The enhanced bone shadow images are automatically segmented and compared against expert segmentation.
RESULTS: Qualitative and quantitative validation was performed on 100 in vivo US scans obtained from five subjects by scanning femur and vertebrae bones. Validation against expert segmentation achieved a mean dice similarity coefficient of 0.88.
CONCLUSIONS: The encouraging results obtained in this initial study suggest that the proposed method is promising enough for further evaluation. The calculated bone shadow maps could be incorporated into different ultrasound bone segmentation and registration approaches as an additional feature.

Keywords:  Bone; Enhancement; Local energy; Local phase; Segmentation; Ultrasound

Mesh:

Year:  2017        PMID: 28285340     DOI: 10.1007/s11548-017-1556-y

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  25 in total

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4.  Non-iterative partial view 3D ultrasound to CT registration in ultrasound-guided computer-assisted orthopedic surgery.

Authors:  Ilker Hacihaliloglu; David R Wilson; Michael Gilbart; Michael A Hunt; Purang Abolmaesumi
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-05-25       Impact factor: 2.924

5.  Fast and Accurate Data Extraction for Near Real-Time Registration of 3-D Ultrasound and Computed Tomography in Orthopedic Surgery.

Authors:  Anna Brounstein; Ilker Hacihaliloglu; Pierre Guy; Antony Hodgson; Rafeef Abugharbieh
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6.  Automated bone contour detection in ultrasound B-mode images for minimally invasive registration in computer-assisted surgery-an in vitro evaluation.

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7.  Automatic extraction of bone surfaces from 3D ultrasound images in orthopaedic trauma cases.

Authors:  Ilker Hacihaliloglu; Pierre Guy; Antony J Hodgson; Rafeef Abugharbieh
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-01-01       Impact factor: 2.924

8.  Local phase tensor features for 3-D ultrasound to statistical shape+pose spine model registration.

Authors:  Ilker Hacihaliloglu; Abtin Rasoulian; Robert N Rohling; Purang Abolmaesumi
Journal:  IEEE Trans Med Imaging       Date:  2014-06-26       Impact factor: 10.048

9.  Bone surface localization in ultrasound using image phase-based features.

Authors:  Ilker Hacihaliloglu; Rafeef Abugharbieh; Antony J Hodgson; Robert N Rohling
Journal:  Ultrasound Med Biol       Date:  2009-07-17       Impact factor: 2.998

Review 10.  Computer-Assisted Orthopedic Surgery: Current State and Future Perspective.

Authors:  Guoyan Zheng; Lutz P Nolte
Journal:  Front Surg       Date:  2015-12-23
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Review 2.  Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging.

Authors:  Masaaki Komatsu; Akira Sakai; Ai Dozen; Kanto Shozu; Suguru Yasutomi; Hidenori Machino; Ken Asada; Syuzo Kaneko; Ryuji Hamamoto
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