Model-based tendon segmentation from ultrasound images

Bo I. Chuang, Yung Nien Sun, Tai Hwa Yang, Fong Chin Su, Li Chieh Kuo, I. Ming Jou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


In orthopedics, trigger finger is one of the popular occupational hazards in recent years. Ultrasound images are usually used for diagnosing the severity of trigger finger clinically. Finger ultrasound image has two important characteristics: the shape of tendon is close to an ellipse, and the tendon boundaries vary significantly in image appearance. The traditional segmentation methods usually cannot segment the tendon well. In this study, we develop an ultrasound image detection and estimation system that can assist clinician to locate and evaluate the area of tendon and synovial sheath automatically. An adaptive texture-based active shape model (ATASM) method is proposed to overcome the complex segmentation problems with the proposed shape model by minimizing the objective function based on gradient and texture information. Considering the segmentation may have many local solutions due to various image qualities, the genetic algorithm (GA) is adopted to search for the best shape parameters. In the experiments, the results of tendon segmentation are found with small segmentation errors and similar to the contour drawn by trained users.

Original languageEnglish
Title of host publicationProceedings - 2014 40th Annual Northeast Bioengineering Conference, NEBEC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479937288
Publication statusPublished - 2014 Dec 2
Event2014 40th Annual Northeast Bioengineering Conference, NEBEC 2014 - Boston, United States
Duration: 2014 Apr 252014 Apr 27

Publication series

NameProceedings of the IEEE Annual Northeast Bioengineering Conference, NEBEC
ISSN (Print)1071-121X
ISSN (Electronic)2160-7001


Other2014 40th Annual Northeast Bioengineering Conference, NEBEC 2014
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Bioengineering


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