Fengrong Sun

Improved T-Snake Model Based Edge Detection of the Coronary Arterial Walls in Intravascular Ultrasound Images

Accurately detecting edges of the coronary arterial walls in intravascular ultrasound (IVUS) images plays an important role in quantitative assessments of the coronary artery diseases, though it may be a challenge to medical image analysis. This paper presented a method to extract the edges, main characteristics of which were summarized as: 1) The method was based on an improved topologically adaptable snake model (T- Snake model). This proposed T-Snake model could successfully address the significant problem of conventional T-Snakes when dealing with the model self-intersection. 2) The method worked in conjunction with an adaptive homomorphic spatial/temporal filtering technique. This proposed filtering technique was capable of effectively reducing the strong blood speckle noise in IVUS images. The experimental results indicated the proposed method was accurate and robust in detecting edges of the coronary arterial walls in IVUS images, as well as reproducible for sequential IVUS frames.

Region of Interest Tracking in Real-Time Myocardial Contrast Echocardiography

The real-time myocardial contrast echocardiography (RT MCE) is a new echocardiography technology, which allows clinicians to noninvasively evaluate the perfusion of myocardial capillary of patients, using the quantitative analysis of RT MCE. But the accurate analysis requires tracking the position of region of interest (ROI) within the myocardial area, so as to compensate for the translation or rotation offsets, which are due to such uncontrollable factors as heart motion. We used diamond search method and Brox’s coarse-to-fine warping optical flow technique for this ROI tracking problem. We validated our methods by comparing the quantitative analysis results of RT MCE using our methods with those using Lucas & Kanade’s optical flow technique, which had been report to be accurate enough for this ROI tracking. We finally present some examples of animal experiment to show the effectiveness and the clinical application value of our ROI tracking methods.

Numerical Methods and Workstation for the Quantitative Analysis of Real-Time Myocardial Contrast Echocardiography

Using the quantitative analysis of real-time myocardial contrast echocardiography (RT MCE), clinicians can assess the myocardial perfusion of patients, noninvasively and accurately. We designed a workstation to assist clinicians to automatically implement the accurate analysis of RT MCE. The workstation can compute some hemodynamic parameters of myocardial microcirculation, e.g., myocardial blood flow, myocardial blood flow mean velocity, and myocardial blood volume. Our new methods involved in the quantitative analysis of RT MCE are summarized as follows. 1) A novel orthogonal array optimization (OAO) technique was proposed and used to estimate the unknown parameters of the nonlinear model to guarantee numerical stability. 2) Broxs coarse-to-fine warping optical flow technique was employed to automatically track the region of interest located inside the myocardial area to ensure the accuracy of the quantitative analysis. Finally, we illustrate some examples of clinical studies to indicate the effectiveness of the system and the reliability of the methods.

Thresholding-Based Image Denoising Using Two-Dimensional S-Transform

S-transform is an effective time-frequency analysis technique which can provide simultaneous time and frequency distribution information similar to the wavelet transform. It is a multi-resolution analysis method applicable to image denoising and is expected to become a powerful processing tool in this field. We introduce the ideas of wavelet transform denoising into S-transform and propose thresholding-based image denoising using two-dimensional S-transform. Simulation experimental results illustrate the favorable application performance of the method, while its successful implementation in myocardial contrast echocardiography image denoising demonstrates its clinical value.

Feature-Space-Based fMRI Analysis Using the Optimal Linear Transformation

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Development of a new real-time MCE-based quantitative analysis system

The quantitative analysis system for real time myocardial contrast echocardiography can measure the values of A(microvascular cross-sectional area or myocardial blood volume)and β(myocardial microbubble velocity), A·β(myocardial blood flow), A-EER (endo-epi ratio of A ), β-EER and A·β-EER from the signal intensity of real-time 2-D grayscale images and power Doppler images, draw the time-intensity curves to indicate the variation of the intensity of micro-bubbles scattering in subendocardial layer and subepicardial layer with the varying of myocardial segments, and estimate the hemodynamic parameters by nonlinear regression analysis. The system also conformed to the digital imaging and communications in medicine (DICOM) standard and could be integrated into the picture archiving and communication system (PACS). The examples of clinical study indicated the clinical effectiveness of the system and the reliability of the quantitative analysis techniques employed in the system.

Image Denoising Using Discrete Orthonormal S-Transform

S-transform is an effective time-frequency analysis technique, which can provide simultaneous time and frequency distribution information similar to the wavelet transform (WT). Discrete orthonormal S-transform (DOST) can reduce the redundancy of S-transform further. We introduce the ideas of wavelet transform-based image denoising into DOST domain and propose the soft-thresholding-based image denoising method using DOST. Simulations and the application in myocardial contrast echocardiography (MCE) image denoising illustrate the good performance of the proposed method and its application prospects.

Measurement of left ventricular torsion using block-matching-based speckle tracking for two-dimensional echocardiography

Abstract. Left ventricular (LV) torsion is a sensitive and global index of LV systolic and diastolic function, but how to noninvasively measure it is challenging. Two-dimensional echocardiography and the block-matching based speckle tracking method were used to measure LV torsion. Main advantages of the proposed method over the previous ones are summarized as follows: (1) The method is automatic, except for manually selecting some endocardium points on the end-diastolic frame in initialization step. (2) The diamond search strategy is applied, with a spatial smoothness constraint introduced into the sum of absolute differences matching criterion; and the reference frame during the search is determined adaptively. (3) The method is capable of removing abnormal measurement data automatically. The proposed method was validated against that using Doppler tissue imaging and some preliminary clinical experimental studies were presented to illustrate clinical values of the proposed method.

Surface reconstruction of the coronary arterial walls from intravascular ultrasound images

Three-dimensional surface reconstruction of the coronary arterial from intravascular ultrasound (IVUS) images plays an important role in diagnosis and treatment of the atherosclerosis. A simplified 3-D topologically adaptable snake model (3-D T-snake) is proposed; nevertheless, it can successfully address the significant problem of conventional T-snakes when dealing with the model self-intersections. A method of surface reconstruction of IVUS coronary arterial walls based on the simplified 3-D T-snake is presented. The experimental results indicate that the method is accurate and robust, and the simplified 3-D T-Snake is feasible and valid.