Segmenting Cardiac MRI Tagging Lines using Gabor Filter Banks

Zhen Qian, Albert Montillo, Dimitri Metaxas, Leon Axel

Research output: Contribution to journalConference article

30 Citations (Scopus)

Abstract

This paper describes a new method for the automated segmentation and extraction of cardiac MRI tagging lines. Our method is based on the novel use of a 2D Gabor filter bank. By convolving the tagged input image with our Gabor filters, the tagging lines are automatically enhanced and segmented out. We design the Gabor filter bank based on the input image's spatial and frequency characteristics. The final result is a combination of each filter's response in the Gabor filter bank. We demonstrate that compared to bandpass filter methods such as HARP, this method results in robust and accurate segmentation of the tagging lines.

Original languageEnglish (US)
Pages (from-to)630-633
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
StatePublished - Dec 1 2003
EventA New Beginning for Human Health: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico
Duration: Sep 17 2003Sep 21 2003

Fingerprint

Gabor filters
Filter banks
Magnetic resonance imaging
Bandpass filters

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Keywords

  • Gabor filter bank
  • Tagged MRI images
  • Tagging line segmentation

Cite this

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Segmenting Cardiac MRI Tagging Lines using Gabor Filter Banks. / Qian, Zhen; Montillo, Albert; Metaxas, Dimitri; Axel, Leon.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 1, 01.12.2003, p. 630-633.

Research output: Contribution to journalConference article

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AU - Qian, Zhen

AU - Montillo, Albert

AU - Metaxas, Dimitri

AU - Axel, Leon

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N2 - This paper describes a new method for the automated segmentation and extraction of cardiac MRI tagging lines. Our method is based on the novel use of a 2D Gabor filter bank. By convolving the tagged input image with our Gabor filters, the tagging lines are automatically enhanced and segmented out. We design the Gabor filter bank based on the input image's spatial and frequency characteristics. The final result is a combination of each filter's response in the Gabor filter bank. We demonstrate that compared to bandpass filter methods such as HARP, this method results in robust and accurate segmentation of the tagging lines.

AB - This paper describes a new method for the automated segmentation and extraction of cardiac MRI tagging lines. Our method is based on the novel use of a 2D Gabor filter bank. By convolving the tagged input image with our Gabor filters, the tagging lines are automatically enhanced and segmented out. We design the Gabor filter bank based on the input image's spatial and frequency characteristics. The final result is a combination of each filter's response in the Gabor filter bank. We demonstrate that compared to bandpass filter methods such as HARP, this method results in robust and accurate segmentation of the tagging lines.

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