The Key Technology Research Of Medical Imaging Diagnosis Of Coronary Heart Disease

Medical image diagnosis is an interdisciplinary and crossing-fusion research field,involving radiology,diagnostic imaging,statistics,computer graphics,digital image processing,pattern recognition and artificial intelligence and many other disciplines,which has a wide range of areas of expertise.With the continuous improvement of computer processing speed and the expansion of application fields,medical image diagnosis technology based on computer image processing has been discovered and improved.In recent years,the diagnosis of coronary heart disease medical image has become one of the hot spots,and its theoretical innovation and technical breakthrough will have a profound impact on the industrialization of computer image processing.Most existing researches focus on medical image of coronary heart disease are mostly single and isolated,these problems will not solve the series,and the severity of coronary artery stenosis and accurate measurement is still a worldwide problem.Therefore,this study focus on the diagnosis of coronary heart disease in medical image process a series of key technical problems and give further research and discussion,including image automatic segmentation,image interpolation,image 3D reconstruction and measuring the degree of coronary artery stenosis problems.And specifically,the main contributions of this study are listed as follows.1.In the aspect of automatic segmentation of medical images of coronary heart disease,this study gives an algorithm which proposed the use of the normal distribution curve fitting histogram dynamic segmentation algorithm to find seed point based on grey histogram of DICOM images at first.Moreover,it focuses on the use of the fitting algorithm for image segmentation and extraction target field with the experimental demonstration of real clinical cases of image data.The proposed algorithm has get a target of finding the seed point automatically segmentation the ill-parts completely and visualization of the medical images.It not only increases the doctor in a timely manner,keen to find small compared to the early,and in the hidden part of the lesion probability,but also in all directions and the side of the subtle observation and analysis of these lesions is more scientifically and accurately judged condition,optimal individualized treatment plan design provides new possibilities.2.In the aspect of medical image interpolation of coronary heart disease,this study provides a new edge matching interpolation algorithm based on wavelet decomposition of CTA.Combining the real clinical image data,this study mainly introduces how to search for proportional factor and use the root mean square operator to find a mean value.Furthermore,we re-synthesize the high frequency and low frequency parts of the processed image by wavelet inverse operation,and get the final interpolation image.This method can make up for the shortage of the conventional Computed Tomography(CT)and Magnetic Resonance Imaging(MRI)examination.The radiation absorption and the time to check through the proposed synthesized image were significantly reduced.Clinically,it can help doctor to find hidden lesions in time.Simultaneously,the patients get less economic burden as well as less radiation exposure absorbed.3.In the aspect of three dimensional reconstruction of coronary heart disease,this study proposes an improved algorithm of ray projection.On one hand,according to the observer viewpoint and the distance between different images,this study used surface normal line and focused on the point of tangency of the partial derivative with viewpoint and point distance ratio to adjust the sampling frequency which through the three-dimensional data field in each ray.The observer can get more detailed model representation when the object distance is close to meet the viewpoint.On the other hand,some rays which are not reaching the screen were not involved in the synthesis of ray opacity and color value calculation.The improved algorithm in this study not only can effectively improve the image rendering speed,but also avoid the generation of artifacts,which can improve the quality of the image to a certain extent.4.In the aspect of accuracy of measurement of partial stenosis degree of coronary artery disease,this study proposes a new method of measuring the degree of coronary artery stenosis by using the definite integral.First of all,Visualization Toolkit(VTK)and Insight Segmentation and Registration Toolkit(ITK)are used to 3D reconstruction of the vessels.Then,a coronary artery centerline extraction algorithm based on point tracking is used to extract the center line of the target vessel.Next,based on the coronal of the three-dimensional model of the blood vessels in the center line for the origin of a Cartesian coordinate system,the image is divided into four quadrants.In each quadrant,this study calculates the area surrounded by vascular blood flow in the region and the coordinate system.Finally,vascular stenosis is calculated by the ratio of the difference of inside and outside and the cross-sectional area of the coronary arteries.This algorithm has good effectiveness and accuracy,and it is helpful to the early detection,diagnosis and treatment of coronary heart disease.Accordingly,it improves the survival rate and quality of life of patients with coronary heart disease.In short,this study has discussed four aspects of image interpolation,image from image matching and 3D reconstruction of coronary artery stenosis degree measurement.By combining the real clinical image data experiments show that these proposed algorithms have good effectiveness and accuracy.It is helpful to the early diagnosis,diagnosis and treatment of coronary heart disease,which provides an effective basis for clinical diagnosis and preoperative planning.