4D vessel segmentation and tracking in Ultrasound

Kedar A. Patwardhan; Yongjian Yu; Sandeep Gupta; Aaron Dentinger; David Mills

doi:10.1109/ICIP.2012.6467360

4D vessel segmentation and tracking in Ultrasound

Kedar A. Patwardhan, Yongjian Yu, Sandeep Gupta, Aaron Dentinger, David Mills

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

2 Scopus citations

Abstract

In this paper we describe a fast method to segment and track a vessel of interest in 4D (i.e. 3D + time) Ultrasound images. An initial 2D seed is used to initialize a single spatial Kalman-Filter tracker which tracks the vessel center-line in 3D. The 3D vessel is then segmented using a fast area weighted active contour method. This segmented 3D vessel is then tracked across multiple time-points using a set of temporal Kalman- Filters which track the movement of the center of the vessel in each 2D slice. The vessel boundaries are estimated by growing an area weighted active contour outward from the centerline. Based on qualitative as well as quantitative performance measures, the proposed method shows promising tracking results on numerous phantom as well as patient datasets.

Original language	English (US)
Title of host publication	Proceedings - International Conference on Image Processing, ICIP
Pages	2317-2320
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2012.6467360
State	Published - 2012
Externally published	Yes
Event	2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States Duration: Sep 30 2012 → Oct 3 2012

Other

Other	2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country/Territory	United States
City	Lake Buena Vista, FL
Period	9/30/12 → 10/3/12

Keywords

4D
Kalman filter
real-time 3D
segmentation
tracking
ultrasound
vessel

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems

Access to Document

10.1109/ICIP.2012.6467360

Cite this

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title = "4D vessel segmentation and tracking in Ultrasound",

abstract = "In this paper we describe a fast method to segment and track a vessel of interest in 4D (i.e. 3D + time) Ultrasound images. An initial 2D seed is used to initialize a single spatial Kalman-Filter tracker which tracks the vessel center-line in 3D. The 3D vessel is then segmented using a fast area weighted active contour method. This segmented 3D vessel is then tracked across multiple time-points using a set of temporal Kalman- Filters which track the movement of the center of the vessel in each 2D slice. The vessel boundaries are estimated by growing an area weighted active contour outward from the centerline. Based on qualitative as well as quantitative performance measures, the proposed method shows promising tracking results on numerous phantom as well as patient datasets.",

keywords = "4D, Kalman filter, real-time 3D, segmentation, tracking, ultrasound, vessel",

author = "Patwardhan, {Kedar A.} and Yongjian Yu and Sandeep Gupta and Aaron Dentinger and David Mills",

year = "2012",

doi = "10.1109/ICIP.2012.6467360",

language = "English (US)",

isbn = "9781467325332",

pages = "2317--2320",

booktitle = "Proceedings - International Conference on Image Processing, ICIP",

note = "2012 19th IEEE International Conference on Image Processing, ICIP 2012 ; Conference date: 30-09-2012 Through 03-10-2012",

}

TY - GEN

T1 - 4D vessel segmentation and tracking in Ultrasound

AU - Patwardhan, Kedar A.

AU - Yu, Yongjian

AU - Gupta, Sandeep

AU - Dentinger, Aaron

AU - Mills, David

PY - 2012

Y1 - 2012

N2 - In this paper we describe a fast method to segment and track a vessel of interest in 4D (i.e. 3D + time) Ultrasound images. An initial 2D seed is used to initialize a single spatial Kalman-Filter tracker which tracks the vessel center-line in 3D. The 3D vessel is then segmented using a fast area weighted active contour method. This segmented 3D vessel is then tracked across multiple time-points using a set of temporal Kalman- Filters which track the movement of the center of the vessel in each 2D slice. The vessel boundaries are estimated by growing an area weighted active contour outward from the centerline. Based on qualitative as well as quantitative performance measures, the proposed method shows promising tracking results on numerous phantom as well as patient datasets.

AB - In this paper we describe a fast method to segment and track a vessel of interest in 4D (i.e. 3D + time) Ultrasound images. An initial 2D seed is used to initialize a single spatial Kalman-Filter tracker which tracks the vessel center-line in 3D. The 3D vessel is then segmented using a fast area weighted active contour method. This segmented 3D vessel is then tracked across multiple time-points using a set of temporal Kalman- Filters which track the movement of the center of the vessel in each 2D slice. The vessel boundaries are estimated by growing an area weighted active contour outward from the centerline. Based on qualitative as well as quantitative performance measures, the proposed method shows promising tracking results on numerous phantom as well as patient datasets.

KW - 4D

KW - Kalman filter

KW - real-time 3D

KW - segmentation

KW - tracking

KW - ultrasound

KW - vessel

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U2 - 10.1109/ICIP.2012.6467360

DO - 10.1109/ICIP.2012.6467360

M3 - Conference contribution

AN - SCOPUS:84875849603

SN - 9781467325332

SP - 2317

EP - 2320

BT - Proceedings - International Conference on Image Processing, ICIP

T2 - 2012 19th IEEE International Conference on Image Processing, ICIP 2012

Y2 - 30 September 2012 through 3 October 2012

ER -

4D vessel segmentation and tracking in Ultrasound

Abstract

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Keywords

ASJC Scopus subject areas

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