||Development of an ultrasound image-based platform for guiding intravenous injection
||Institute of Computer Science and Information Engineering
vessel edge detection
To increase the accuracy of intravenous injection and blood sampling, medical personnel typically use a rubber band tied down the arm to make the vessel swell before inserting needle. However, the positional accuracy of inserting needle mainly depends on the experience of medical personnel. If the subject has such situations as atrophicans vasculare, small vessel, thick subcutaneous fat, etc., the position of vessel could be difficultly observed to affect the accuracy for inserting needle. Therefore, this study developed an ultrasound-guided needle system for assistive intravenous injection, which combined a needle assistive device and vessel detecting from ultrasound image during intravenous injection, to improve the injection accuracy. First, this system automatically detected the position of maximum vessel size by a series of ultrasound image processing included automatic ROI selection of image, contrast enhancement, filtering, thresholding, smoothing, initial edge extraction, edge deciding, and calculation of vascular size. Subsequently, the appropriate angle of needle insertion was calculated by trigonometric functions to assist needle inserting. In addition, the wavelet thresholding method was used to reduce the artifact from needle to enhance the recognition of needle on ultrasound image. The results showed the percentage error is depend on the frequency (or resolution) of the transducer. If use higher frequency (or resolution) of the transducer, then the percentage error can be reduced; in the part of artifact reduction, the result image will change with brightness prominent threshold value. By comparing with the contrast value, we select the value 0.7 to be the brightness prominent threshold. This study demonstrated that the ultrasound-guided needle system could immediately, accurately, safely and conveniently find the central position of vessel. Furthermore, the components of the system mainly consist of only a needle and transducer holder, and the developed software. Therefore, it tends to be cost-effective and may be applied to improve the accuracy of needle injection for resource-scarce communities.
Table of contents..... V
List of table..... VII
List of figure...... VIII
Chapter 1. Introduction..... 1
1.1 Review articles.... 1
1.1.1 Needle visualization in ultrasound.... 2
1.1.2 Vessel edge detection.... 8
1.2 Research objective..... 8
Chapter 2. Theoretical background... 10
2.1 Fundamentals of ultrasound.... 10
2.1.1 Fundamentals of acoustic propagation.. 10
2.1.2 Reflection and refraction... 10
2.1.3 Attenuation and absorption... 13
2.2 Ultrasonic transducers..... 15
2.3 Artifacts in ultrasound image.... 18
Chapter 3. Materials and methods.... 21
3.1 Experimental arrangement.... 21
3.1.1 Vessel size tracking.... 21
3.1.2 Needle visibility enhance... 28
3.2 Phantom..... 33
3.3 Verification.... 33
3.3.1 Vessel size tracking.... 33
3.3.2 Needle visibility enhance... 34
3.4 Ultrasound imaging system... 34
3.5 Guided needle intervention positioning.... 36
Chapter 4. Results and discussion... 37
4.1 Vessel size tracking..... 37
4.1.1 Vessel size tracking results by 7.5 MHz linear array transducer.. 39
4.1.2 Vessel size tracking results by 12 MHz linear array transducer. 42
4.2 Needle insertion and needle visibility enhance... 45
4.2.1 The needle visibility enhance result by 7.5 MHz linear array transducer .. 45
4.2.2 The needle visibility enhance result by 12 MHz linear array transducer . 52
Chapter 5. Conclusions and future works... 59
5.1 Conclusions..... 59
5.2 Future works.... 60
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