1.3D reconstruction of HIFU lesion area based on level set
Yanling FENG ; Zhencheng CHEN ; Jishan HE ; Yangde ZHANG ; Shenyou QIAN
Chinese Medical Equipment Journal 2003;0(11):-
Objective To design a computer aided method in HIFU treatment system to monitor the size,shape and location of HIFU lesion automatically.Methods According to ultrasound image's characters of high noise,low resolution and weak edge,a double zero level set,double speed approach was proposed to extract the contour of organ and lesion area.The serial "lice" contours were used to reconstruct three dimension(3D) HIFU lesion area in the sample.Results Experiments show that level set contour extraction method based 3D reconstruction is helpful in monitoring the size,shape and location in the organ.Conclusion This method has the feasibility to be introduced as an auxiliary technique monitoring HIFU lesion area automatically.
2.Changes of endothelin and atrial natriuretic peptide in rats of chronic hypoxic pulmonary hypertension
Xinwen YANG ; Zemin MA ; Wenjun YUAN ; Zhencheng HE ;
Academic Journal of Second Military Medical University 1982;0(01):-
To observe the changes of endothelin(ET) and atrial natriuretic peptide(ANP) lev-els in chronic hypoxic pulmonary hypertensive rats and discuss their mechanism. Methods: We duplicatedthe models of chronic hyp0xic pulmonary hypertensive rats and tested the concentrations of ET and ANP ofplasma and cardiac tissue by radioimmunoassey. Results: In pulmonary hypertension group, plasma ET,plasma ANP and myocardial ET levels increased more significantly than those of controls,except that my-ocardial ANP concentration decreased. There were positive c0rrelati0ns between plasma ET level and plas-ma ANP level and between plasma ET level and myocardial ET level, but a negative correlation betweenplasma ANP level and myocardial ANP level. C0nclusion: It is suggested that the synthesis and secretionof ET and ANP increase in pulmonary hypertension,and therefore provides reference to clinical diagnosisand therapy.
3.Establishment and practice of clinical diagnostics teaching system
Jian ZHONG ; Bin WANG ; Fang SUN ; Zhencheng YAN ; Hongbo HE ; Zhiming ZHU ; Yinxing NI
Chinese Journal of Medical Education Research 2012;11(10):1030-1032
The improvement of diagnostics teaching system,including the establishment of curriculum system and evaluation system,is the base of promoting clinical- medicine teaching.Our study showed that the theoretical knowledge and clinical skill of medical students could be improved by constructing clinical diagnostics curriculum system and improving organization management and assessment system,which could pave the way for the transition from medical students to clinicians.
4.Interventional therapy combined with multifactorial intervention in diabetes with lower-limb vascular disease
Zhencheng YAN ; Zhigang ZHAO ; Hongbo HE ; Yong JIN ; Jing CHEN ; Yinxing NI ; Jian ZHONG ; Yingsha LI ; Qinjin HU ; Zhiming ZHU
Chinese Journal of Endocrinology and Metabolism 2010;26(7):577-578
The effect of interventional therapy combined with multifactorial intervention on critical limb ischemia in patients with diabetes mellitus was investigated. The patency rate and limb salvage rate were followed up. Interventional therapy is effective in treating diabetic foot with critical limb ischemia. Multifactorial intervention was helpful for reducing amputation.
5.Support vector machine based high intensity focused ultrasound beam lesion degree classification and recognition.
Yanling FENG ; Zhencheng CHEN ; Jishan HE ; Shengyou QIAN
Journal of Biomedical Engineering 2010;27(5):978-983
Ultrasound based tissue thermal lesion non-invasive detection is of great significance in high intensity focused ultrasound (HIFU) clinical application. In this paper, we propose a sub-pixel method to quantify the ultrasound image change caused by HIFU as correlation-distance. The support vector machine (SVM) was trained by using correlation distance as samples, and the recognition effect was tested. Results showed that sub-pixel cross-correlation vector field could reflect the ablation lesions position. SVM based classification method can recognize HIFU beam lesion degree effectively.
Algorithms
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Diagnostic Imaging
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methods
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High-Intensity Focused Ultrasound Ablation
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adverse effects
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Humans
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Pattern Recognition, Automated
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methods
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Support Vector Machine