A Novel Method for Low-Contrast and High-Noise Vessel Segmentation and Location in Venipuncture

Blood sampling is the most common medical technique, and vessel detection is of crucial interest for automated venipuncture systems. In this paper, we propose a new convex-regional-based gradient model that uses contextually related regional information, including vessel width size and gray distribu...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 2017-11, Vol.36 (11), p.2216-2227
Main Authors: Li, Yuhe, Qiao, Zhendong, Zhang, Shaoqin, Wu, Zhenhuan, Mao, Xueqin, Kou, Jiahua, Qi, Hong
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Automation
Biomedical imaging
Blood vessels
Blood Vessels - diagnostic imaging
Continuity (mathematics)
convex function optimization
Extreme values
Humans
Image analysis
Image contrast
Image edge detection
Image processing
Image Processing, Computer-Assisted - methods
Image segmentation
Infrared imagery
Medical imaging
Model testing
Noise
noise independence
Noise measurement
Phlebotomy
Phlebotomy - methods
regional-gradient
ROC Curve
Smoothness
Spectroscopy, Near-Infrared - methods
Veins
venipuncture system
Vessel segmentation
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Summary:Blood sampling is the most common medical technique, and vessel detection is of crucial interest for automated venipuncture systems. In this paper, we propose a new convex-regional-based gradient model that uses contextually related regional information, including vessel width size and gray distribution, to segment and locate vessels in a near-infrared image. A convex function with the interval size of vessel width is constructed and utilized for its edge-preserving superiority. Moreover, white and linear noise independences are derived. The region-based gradient decreases the number of local extreme in the cross-sectional profile of the vessel to realize its single global minimum in a low-contrast, noisy image. We demonstrate the performance of the proposed model via quantitative tests and comparisons between different methods. Results show the advantages of the model on the continuity and smoothness of segmented vessel. The proposed model is evaluated with receiver operating characteristic curves, which have a corresponding area under the curve of 88.8%. The proposed model will be a powerful method in automated venipuncture system and medical image analysis.
ISSN:0278-0062
1558-254X
DOI:10.1109/TMI.2017.2732481