Medical ultrasound beamforming based on eigenspace analysis and region detection

Cheng Chen, Xing Zeng, Yuanyuan Wang, Tianjie Li, Yongping Zheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

The eigenspace-based minimum variance (ESBMV) beamformer may greatly improve ultrasound image contrast. However, it results in empty space around strong scatterers, which destroys the intrinsic speckle pattern. A novel method is proposed based on eigenspace analysis and region detection. Exploiting a pre-scanned delay-and-sum beamformed image, the new method decides whether the desired signal comes from a hypoechoic region based on eigenspace analysis. Different processing methods are used for different regions. For image points inside a hypoechoic region, the traditional ESBMV beamformer is used while for those outside the hypoechoic regions, the proposed modified ESBMV beamformer is used. Simulated and experimental results based on plane wave imaging show that the proposed method greatly reduces artifacts and preserves the intrinsic speckle pattern, and simultaneously achieve almost the same contrast (much higher than the original minimum variance approach) as the traditional ESBMV. Therefore, it is more effective as a high-contrast beamformer.
Original languageEnglish
Pages (from-to)80-83
Number of pages4
JournalYi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument
Volume34
Issue number6 SUPPL.
Publication statusPublished - 1 Jan 2013

Keywords

  • Beamforming
  • Eigenspace
  • Medical ultrasound imaging
  • Region detection

ASJC Scopus subject areas

  • Instrumentation

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