Automatic Extraction of Central Tendon of Rectus Femoris (CT-RF) in Ultrasound Images Using a New Intensity-Compensated Free-Form Deformation-Based Tracking Algorithm with Local Shape Refinement

Xiguang Wei, Jinyong Zhang, Shing Chow Chan, Ho Chun Wu, Yongjin Zhou, Yongping Zheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


Ultrasonography is an important diagnostic imaging technique for visualization of tendons, which provides useful health diagnostic and fundamental information in neuromuscular studies of human motion systems. Conventional ultrasonic-based tendon studies, however, are highly dependent on subjective experience of operators due to various impairments of ultrasound images. Dynamic changes of muscle and tendon deformation in a sequence can hardly be manually processed. Consequently, there is an urgent need for automatic analysis of tendon behavior. This paper proposes an automatic ultrasonic tendon tracking algorithm to extract the shape deformation of central tendon of rectus femoris (CT-RF) from ultrasonic image sequences. The tracking problem is complicated by the highly deformable tendon, time-varying brightness, and the inconspicuousness of the target. To address this difficult tracking problem, we proposed a new intensity-compensated free-form deformation (IC-FFD)-based tracking algorithm with local shape refinement (LSR). Experimental results and comparison show that the proposed IC-FFD-LSR algorithm outperforms IC-FFD and conventional methods such as MI-FFD in CT-RF tracking.
Original languageEnglish
Article number7491303
Pages (from-to)1058-1068
Number of pages11
JournalIEEE Journal of Biomedical and Health Informatics
Issue number4
Publication statusPublished - 1 Jul 2017


  • Free-form deformation (FFD)-based tracking
  • locally adaptive thresholding
  • rectus femoris
  • tendon
  • tracking and segmentation
  • ultrasound

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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