Abstract. In view of modern clinical treatment and care, venipuncture has a very important position, but in order to train a medical staff with high level skill of puncture need to spend a lot of time, human and material resources. For this reason, in this paper, an automatic system that can achieve venipuncture is proposed, which can replace the medical staff and achieve the puncture process. The automatic venipuncture system, combined with NIR imaging and ultrasound imaging technology, the overall plane information is obtained by NIR image, depth information and fine positioning of the plane information is obtained by ultrasound image. By way of image processing, the NIR image is enhanced and segmented, getting the spatial location of the vein. And the most suitable blood vessel segments were selected by piecewise straight fitting. Then the location ultrasonic probe should be placed is determined. Then the ultrasound image with the blood vessel in the vicinity of the longitudinal centreline can be obtained. All the information of blood vessel have been obtained, then the machine can be driven to achieve 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 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.
There are complex and perfect coagulation, anticoagulation and fibrinolysis systems in the human body and their fine regulatory mechanisms. Once the coagulation system and its regulatory mechanisms are destroyed, bleeding or thrombosis will occur very soon. In the blood coagulation, the blood viscoelasticity changes. Therefore, the thrombus elasticity measurement technology can be used to continuously monitor the changing blood viscoelasticity in order to study the process of coagulation. The results of the interaction among the various components of the blood can be obtained from coagulation to fibrinolysis by bedside detection. The traditional electromagnetic induction sensors, based on conventional coil inductance, are manufactured complexly, high cost and non-linear. Therefore, this paper proposes a non-Newtonian fluid viscoelasticity measurement method based on the piezoelectric effect. We use the piezoelectric bimorphs with the diameter of 21 mm and the total thickness of 0.38 mm and DSM coupling probes with the length of 3 mm, 5 mm and 7 mm to design the piezoelectric bimorphs driver. The viscoelasticity of different non-Newtonian fluids is tested. The vibration amplitudes of the piezoelectric bimorphs and liquid surfaces range from 0.43 μm to 3.52 μm. Consequently, the feasibility of in vitro detection of thrombus is confirmed in principle and the above scheme is validated theoretically and experimentally, which provides the basis for the measurement of blood viscoelasticity, the in vitro detection of thrombus and the manufacture of blood coagulation instrument.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.