Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps

Cosmas Mwikirize; John L. Nosher; Ilker Hacihaliloglu

doi:https://doi.org/10.1007/978-3-319-46720-7_42

Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps

Cosmas Mwikirize, John L. Nosher, Ilker Hacihaliloglu

School of Engineering, Biomedical Engineering

Rutgers, The State University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

New methods for needle tip and shaft enhancement in 2D curvilinear ultrasound are proposed. Needle tip enhancement is achieved using an image regularization method that utilizes ultrasound signal transmission maps to model inherent signal loss due to attenuation. Shaft enhancement is achieved by optimizing the proposed signal transmission map using the information based on trajectory constrained boundary statistics derived from phase oriented features. The enhanced tip is automatically localized using spatially distributed image statistics from the estimated shaft trajectory. Validation results from 100 ultrasound images of bovine,porcine,kidney and liver ex vivo reveal a mean localization error of 0.3±0.06 mm,a 43% improvement in localization over previous state of the art.

Original language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
Editors	Sebastian Ourselin, Leo Joskowicz, Mert R. Sabuncu, William Wells, Gozde Unal
Publisher	Springer Verlag
Pages	362-369
Number of pages	8
ISBN (Print)	9783319467191
DOIs	https://doi.org/10.1007/978-3-319-46720-7_42
State	Published - 2016
Event	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece Duration: Oct 21 2016 → Oct 21 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9900 LNCS

Other

Other	1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/Territory	Greece
City	Athens
Period	10/21/16 → 10/21/16

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Keywords

Confidence maps
Image regularization
Local phase
Needle enhancement
Ultrasound

Access to Document

https://doi.org/10.1007/978-3-319-46720-7_42

Cite this

Mwikirize, C., Nosher, J. L., & Hacihaliloglu, I. (2016). Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps. In S. Ourselin, L. Joskowicz, M. R. Sabuncu, W. Wells, & G. Unal (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings (pp. 362-369). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46720-7_42

Mwikirize, Cosmas ; Nosher, John L. ; Hacihaliloglu, Ilker. / Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. editor / Sebastian Ourselin ; Leo Joskowicz ; Mert R. Sabuncu ; William Wells ; Gozde Unal. Springer Verlag, 2016. pp. 362-369 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps",

abstract = "New methods for needle tip and shaft enhancement in 2D curvilinear ultrasound are proposed. Needle tip enhancement is achieved using an image regularization method that utilizes ultrasound signal transmission maps to model inherent signal loss due to attenuation. Shaft enhancement is achieved by optimizing the proposed signal transmission map using the information based on trajectory constrained boundary statistics derived from phase oriented features. The enhanced tip is automatically localized using spatially distributed image statistics from the estimated shaft trajectory. Validation results from 100 ultrasound images of bovine,porcine,kidney and liver ex vivo reveal a mean localization error of 0.3±0.06 mm,a 43% improvement in localization over previous state of the art.",

keywords = "Confidence maps, Image regularization, Local phase, Needle enhancement, Ultrasound",

author = "Cosmas Mwikirize and Nosher, {John L.} and Ilker Hacihaliloglu",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 ; Conference date: 21-10-2016 Through 21-10-2016",

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pages = "362--369",

editor = "Sebastian Ourselin and Leo Joskowicz and Sabuncu, {Mert R.} and William Wells and Gozde Unal",

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Mwikirize, C, Nosher, JL & Hacihaliloglu, I 2016, Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps. in S Ourselin, L Joskowicz, MR Sabuncu, W Wells & G Unal (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9900 LNCS, Springer Verlag, pp. 362-369, 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, Athens, Greece, 10/21/16. https://doi.org/10.1007/978-3-319-46720-7_42

Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps. / Mwikirize, Cosmas; Nosher, John L.; Hacihaliloglu, Ilker.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. ed. / Sebastian Ourselin; Leo Joskowicz; Mert R. Sabuncu; William Wells; Gozde Unal. Springer Verlag, 2016. p. 362-369 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9900 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps

AU - Mwikirize, Cosmas

AU - Nosher, John L.

AU - Hacihaliloglu, Ilker

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - New methods for needle tip and shaft enhancement in 2D curvilinear ultrasound are proposed. Needle tip enhancement is achieved using an image regularization method that utilizes ultrasound signal transmission maps to model inherent signal loss due to attenuation. Shaft enhancement is achieved by optimizing the proposed signal transmission map using the information based on trajectory constrained boundary statistics derived from phase oriented features. The enhanced tip is automatically localized using spatially distributed image statistics from the estimated shaft trajectory. Validation results from 100 ultrasound images of bovine,porcine,kidney and liver ex vivo reveal a mean localization error of 0.3±0.06 mm,a 43% improvement in localization over previous state of the art.

AB - New methods for needle tip and shaft enhancement in 2D curvilinear ultrasound are proposed. Needle tip enhancement is achieved using an image regularization method that utilizes ultrasound signal transmission maps to model inherent signal loss due to attenuation. Shaft enhancement is achieved by optimizing the proposed signal transmission map using the information based on trajectory constrained boundary statistics derived from phase oriented features. The enhanced tip is automatically localized using spatially distributed image statistics from the estimated shaft trajectory. Validation results from 100 ultrasound images of bovine,porcine,kidney and liver ex vivo reveal a mean localization error of 0.3±0.06 mm,a 43% improvement in localization over previous state of the art.

KW - Confidence maps

KW - Image regularization

KW - Local phase

KW - Needle enhancement

KW - Ultrasound

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DO - https://doi.org/10.1007/978-3-319-46720-7_42

M3 - Conference contribution

SN - 9783319467191

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 362

EP - 369

BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings

A2 - Ourselin, Sebastian

A2 - Joskowicz, Leo

A2 - Sabuncu, Mert R.

A2 - Wells, William

A2 - Unal, Gozde

PB - Springer Verlag

T2 - 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016

Y2 - 21 October 2016 through 21 October 2016

ER -

Mwikirize C, Nosher JL, Hacihaliloglu I. Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps. In Ourselin S, Joskowicz L, Sabuncu MR, Wells W, Unal G, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings. Springer Verlag. 2016. p. 362-369. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: https://doi.org/10.1007/978-3-319-46720-7_42

Enhancement of needle tip and shaft from 2D ultrasound using signal transmission maps

Abstract

Publication series

Other

ASJC Scopus subject areas

Keywords

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