A LEVEL-SET APPROACH FOR TRACKING OBJECTS IN IMAGE SEQUENCES USING A LEVEL CONSERVATION CONSTRAINT: APPLICATION TO CARDIAC SEQUENCES

被引：0

作者：

Dietenbeck, T. ^{[1
,2
,3
,4
,5
,6
,7
]}

Barbosa, D. ^{[3
,4
,5
,6
,7
,8
]}

Alessandrini, M. ^{[8
]}

D'hooge, J. ^{[8
]}

Friboulet, D. ^{[3
,4
,5
,6
,7
]}

Bernard, O. ^{[3
,4
,5
,6
,7
]}

机构：

[1] Univ Auvergne, Clermont Univ, ISIT, F-63000 Clermont Ferrand, France

[2] CNRS, UMR6284, F-63000 Clermont Ferrand, France

[3] Univ Lyon, CREATIS, Lyon, France

[4] CNRS, UMR5220, F-75700 Paris, France

[5] INSERM, U1044, F-75654 Paris 13, France

[6] INSA Lyon, Lyon, France

[7] Univ Lyon 1, F-69622 Villeurbanne, France

[8] Katholieke Univ Leuven, Cardiovasc Imaging & Dynam, Leuven, Belgium

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2014年

关键词：

Segmentation; tracking; active contour; level-set; shape prior; motion prior; cardiac imaging; SEGMENTATION;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Tracking of moving objects in an image sequence is an important task in many application (e.g. medical imaging, robotics). However, this task is usually difficult due to inherent problems that could happen in sequences (i.e. possible occlusion of the object, large interframe motion). In this paper, we describe a new approach to integrate a priori motion information into a level-set-based active contour approach. Specifically, we introduce a new constraint that enforces the conservation of the levels of the implicit function along the image sequence. This constraint is formulated as a motion prior energy and is used in a tracking algorithm. The method is validated quantitatively on a clinical application based on 10 echocardiographic and 5 cine-MRI sequences (approximate to 700 images).

引用

页码：863 / 866

页数：4

共 50 条

[31] Automatic Segmentation of Polyps in Endoscopic Image Using Level-Set Formulation
Dutta, Soumayan
Sasmal, Pradipta
Bhuyan, M. K.
Iwahori, Yuji
2018 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET), 2018,
[32] A level-set method with a multiplicative-additive constraint model for image segmentation and bias correction
Li, Zhixiang
Tang, Shaojie
Zeng, Yang
Chai, Shijie
Ye, Wenguang
Yang, Fuqiang
Huang, Kuidong
KNOWLEDGE-BASED SYSTEMS, 2024, 297
[33] A level-set method for inhomogeneous image segmentation with application to breast thermography images
Shamsi Koshki, Asma
Ahmadzadeh, M. R.
Zekri, M.
Sadri, S.
Mahmoudzadeh, E.
IET IMAGE PROCESSING, 2021, 15 (07) : 1439 - 1458
[34] A level-set algorithm for tracking discontinuities in hyperbolic conservation laws I. Scalar equations
Aslam, TD
JOURNAL OF COMPUTATIONAL PHYSICS, 2001, 167 (02) : 413 - 438
[35] Fast Image Segmentation Based on Single-parametric Level-Set Approach
Xie, Qiang-Jun
Zhang, Hua-Rong
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 1788 - 1791
[36] Color object segmentation and tracking using flexible statistical model and level-set
Sami Bourouis
Ines Channoufi
Roobaea Alroobaea
Saeed Rubaiee
Murad Andejany
Nizar Bouguila
Multimedia Tools and Applications, 2021, 80 : 5809 - 5831
[37] Color object segmentation and tracking using flexible statistical model and level-set
Bourouis, Sami
Channoufi, Ines
Alroobaea, Roobaea
Rubaiee, Saeed
Andejany, Murad
Bouguila, Nizar
MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (04) : 5809 - 5831
[38] Variational Level-Set Segmentation and Tracking of Left Ventricle Using Field Prior
Afshin, Mariam
Ben Ayed, Ismail
Islam, Ali
Ross, Ian
Peters, Terry
Li, Shuo
MEDICAL IMAGING 2011: IMAGE PROCESSING, 2011, 7962
[39] An advection velocity correction scheme for interface tracking using the level-set method
Satheesh, Kiran
Srinivas, Gowtham
Hemchandra, Santosh
COMPUTERS & FLUIDS, 2018, 168 : 232 - 244
[40] Application of gcForest to visual tracking using UAV image sequences
Liu, Fang
Yang, Anzhe
MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (19) : 27933 - 27956

← 1 2 3 4 5 →