Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue

Chih Feng Chao, Ming Huwi Horng, Yu Chan Chen

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

Original languageEnglish
Article number343217
JournalComputational and Mathematical Methods in Medicine
Volume2015
DOIs
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • General Biochemistry,Genetics and Molecular Biology
  • General Immunology and Microbiology
  • Applied Mathematics

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