A medical imaging analysis system for trigger finger using an adaptive texture-based active shape model (ATASM) in ultrasound images

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

研究成果: Article

1 引文 (Scopus)

摘要

Trigger finger has become a prevalent disease that greatly affects occupational activity and daily life. Ultrasound imaging is commonly used for the clinical diagnosis of trigger finger severity. Due to image property variations, traditional methods cannot effectively segment the finger joint’s tendon structure. In this study, an adaptive texture-based active shape model method is used for segmenting the tendon and synovial sheath. Adapted weights are applied in the segmentation process to adjust the contribution of energy terms depending on image characteristics at different positions. The pathology is then determined according to the wavelet and co-occurrence texture features of the segmented tendon area. In the experiments, the segmentation results have fewer errors, with respect to the ground truth, than contours drawn by regular users. The mean values of the absolute segmentation difference of the tendon and synovial sheath are 3.14 and 4.54 pixels, respectively. The average accuracy of pathological determination is 87.14%. The segmentation results are all acceptable in data of both clear and fuzzy boundary cases in 74 images. And the symptom classifications of 42 cases are also a good reference for diagnosis according to the expert clinicians’ opinions.

原文English
文章編號e0187042
期刊PloS one
12
發行號10
DOIs
出版狀態Published - 2017 十月

指紋

Tendons
Medical imaging
Diagnostic Imaging
tendons
Fingers
synovial sheaths
Textures
Ultrasonics
texture
image analysis
Finger Joint
Expert Testimony
Pathology
joints (animal)
ultrasonography
signs and symptoms (animals and humans)
Ultrasonography
Pixels
Imaging techniques
Weights and Measures

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

引用此文

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abstract = "Trigger finger has become a prevalent disease that greatly affects occupational activity and daily life. Ultrasound imaging is commonly used for the clinical diagnosis of trigger finger severity. Due to image property variations, traditional methods cannot effectively segment the finger joint’s tendon structure. In this study, an adaptive texture-based active shape model method is used for segmenting the tendon and synovial sheath. Adapted weights are applied in the segmentation process to adjust the contribution of energy terms depending on image characteristics at different positions. The pathology is then determined according to the wavelet and co-occurrence texture features of the segmented tendon area. In the experiments, the segmentation results have fewer errors, with respect to the ground truth, than contours drawn by regular users. The mean values of the absolute segmentation difference of the tendon and synovial sheath are 3.14 and 4.54 pixels, respectively. The average accuracy of pathological determination is 87.14{\%}. The segmentation results are all acceptable in data of both clear and fuzzy boundary cases in 74 images. And the symptom classifications of 42 cases are also a good reference for diagnosis according to the expert clinicians’ opinions.",
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AU - Jou, I. Ming

AU - Lin, Wei

AU - Sun, Yung Nien

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