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Manifold learning for image-based breathing gating with application to 4D ultrasound.
Med Image Comput Comput Assist Interv. 2010; 13(Pt 2):26-33.MI

Abstract

Breathing motion leads to a significant displacement and deformation of organs in the abdominal region. This makes the detection of the breathing phase for numerous applications necessary. We propose a new, purely image-based respiratory gating method for ultrasound. Further, we use this technique to provide a solution for breathing affected 4D ultrasound acquisitions with a wobbler probe. We achieve the gating with Laplacian eigenmaps, a manifold learning technique, to determine the low-dimensional manifold embedded in the high-dimensional image space. Since Laplacian eigenmaps assign each ultrasound frame a coordinate in low-dimensional space by respecting the neighborhood relationship, they are well suited for analyzing the breathing cycle. For the 4D application, we perform the manifold learning for each angle, and consecutively, align all the local curves and perform a curve fitting to achieve a globally consistent breathing signal. We performed the image-based gating on several 2D and 3D ultrasound datasets over time, and quantified its very good performance by comparing it to measurements from an external gating system.

Authors+Show Affiliations

Computer Aided Medical Procedures (CAMP), TUM, Munich, Germany. wachinge@cs.tum.eduNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

20879295

Citation

Wachinger, Christian, et al. "Manifold Learning for Image-based Breathing Gating With Application to 4D Ultrasound." Medical Image Computing and Computer-assisted Intervention : MICCAI ... International Conference On Medical Image Computing and Computer-Assisted Intervention, vol. 13, no. Pt 2, 2010, pp. 26-33.
Wachinger C, Yigitsoy M, Navab N. Manifold learning for image-based breathing gating with application to 4D ultrasound. Med Image Comput Comput Assist Interv. 2010;13(Pt 2):26-33.
Wachinger, C., Yigitsoy, M., & Navab, N. (2010). Manifold learning for image-based breathing gating with application to 4D ultrasound. Medical Image Computing and Computer-assisted Intervention : MICCAI ... International Conference On Medical Image Computing and Computer-Assisted Intervention, 13(Pt 2), 26-33.
Wachinger C, Yigitsoy M, Navab N. Manifold Learning for Image-based Breathing Gating With Application to 4D Ultrasound. Med Image Comput Comput Assist Interv. 2010;13(Pt 2):26-33. PubMed PMID: 20879295.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Manifold learning for image-based breathing gating with application to 4D ultrasound. AU - Wachinger,Christian, AU - Yigitsoy,Mehmet, AU - Navab,Nassir, PY - 2010/10/1/entrez PY - 2010/10/1/pubmed PY - 2010/11/16/medline SP - 26 EP - 33 JF - Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention JO - Med Image Comput Comput Assist Interv VL - 13 IS - Pt 2 N2 - Breathing motion leads to a significant displacement and deformation of organs in the abdominal region. This makes the detection of the breathing phase for numerous applications necessary. We propose a new, purely image-based respiratory gating method for ultrasound. Further, we use this technique to provide a solution for breathing affected 4D ultrasound acquisitions with a wobbler probe. We achieve the gating with Laplacian eigenmaps, a manifold learning technique, to determine the low-dimensional manifold embedded in the high-dimensional image space. Since Laplacian eigenmaps assign each ultrasound frame a coordinate in low-dimensional space by respecting the neighborhood relationship, they are well suited for analyzing the breathing cycle. For the 4D application, we perform the manifold learning for each angle, and consecutively, align all the local curves and perform a curve fitting to achieve a globally consistent breathing signal. We performed the image-based gating on several 2D and 3D ultrasound datasets over time, and quantified its very good performance by comparing it to measurements from an external gating system. UR - https://www.unboundmedicine.com/medline/citation/20879295/Manifold_learning_for_image_based_breathing_gating_with_application_to_4D_ultrasound_ L2 - https://medlineplus.gov/ultrasound.html DB - PRIME DP - Unbound Medicine ER -