MUTUAL INFORMATION BASED 3D NON-RIGID REGISTRATION OF CT/MR ABDOMEN IMAGES

A mutual information based 3D non-rigid registration approach was proposed for the registration of deformable CT/MR body abdomen images. The Parzen Windows Density Estimation (PWDE) method is adopted to calculate the mutual information between the two modals of CT and MRI abdomen images. By maximizing MI between the CT and MR volume images, the overlapping part of them reaches the biggest, which means that the two body images of CT and MR matches best to each other. Visible Human Project (VHP) Male abdomen CT and MRI Data are used as experimental data sets. The experimental results indicate that this approach of non-rigid 3D registration of CT/MR body abdominal images can be achieved effectively and automatically, without any prior processing procedures such as segmentation and feature extraction, but has a main drawback of very long computation time.

A Novel Model of F0 Contours Prediction for Continuous Speech

F0 (fundamental frequency) contour was studied under different prosodic environment in continuous speech and a novel model of F0 contours prediction was proposed. It describes syllabic F0 contour with two points, one curve and duration. The curve represents two optimal points of controlling parameters. The duration represents the syllabic duration. The prosodic characters of controlling parameters were analyzed by CART (Class and Regression Tree). A set of cont rolling parameters was analyzed, which reflects the linguistic environment and prosodic structure. Then it sets up the model of F0 contours prediction with the two optimal controlling parameters and F0 templates. The end pitch value of previous syllable as special prosodic parameters was used to keep the continuity of fore-and-aft syllable. It focuses on looking out the main prosodic clues hiding in F0 contours and applying it to simplify the model for prediction. The results of s ynthesis experiment show that the performance of the prediction method is apprec iated.

PERFORMANCE COMPARISON OF ECG COMPRESSION ALGORITHMS BASED ON CLINICAL DIAGNOSIS

This paper reviewed the recent progress in the field of electrocardiogram (ECG) compression and compared the efficiency of some compression algorithms. By experimenting on the 500 cases of ECG signals from the ECG database of China, it obtained the numeral indexes for each algorithm. Then by using the automatic diagnostic program developed by Shanghai Zhongshan Hospital, it also got the parameters of the reconstructed signals from linear approximation distance threshold (LADT), wavelet transform (WT), differential pulse code modulation (DPCM) and discrete cosine transform (DCT) algorithm. The results show that when the index of percent of root mean square difference(PRD) is less than 2.5%, the diagnostic agreement ratio is more than 90%; the index of PRD cannot completely show the damage of significant clinical information; the performance of wavelet algorithm exceeds other methods in the same compression ratio (CR). For the statistical result of the parameters of various methods and the clinical diagnostic results, it is of certain value and originality in the field of ECG compression research.

Monitoring Thermal Coagulation with Ultrasonic Textures

The feasibility of using B-mode ultrasound image textures and pattern recognition technique to characterize the thermal coagulation in vitro during radiofrequency ablation was investigated. The changes of ultrasonic textures in the different regions of samples varied with the heating time in the in-vitro experiments, which would result in that the coagulated and noncoagulated regions of tissue had different ultrasonic textures. Using support vector machine to extract the ultrasonic texture features and characterize the state of tissue, the size and boundaries of thermal lesions could be detected and measured more exactly than only using the gray scale information of B-mode ultrasound image. The proposed method would be applied to the image-guided radiofrequency ablation (IGRA) procedure for monitoring the thermal coagulation.

Design Consideration and Reconstruction Method for Double-source Double-multislice Spiral CT

To accelerate the scan speed and improve the image quality, a new type of CT configuration, "double-source double-multislice spiral CT" (DSDMS-CT), which is based on two sets of single-source multislice spiral CT was proposed with a special reconstruction algorithm. Simulation results using the fan-beam filtered backprojection algorithm with a special interpolation method were presented for both single-source multislice spiral CT and DSDMS-CT. The results of new CT model show that it scans faster than the traditional spiral CT and has a better slice sensitivity profile (SSP) with larger pitch value.

Measuring System Regularity Using Fuzzy Similarity-based Approximate Entropy

Approximate entropy (ApEn), a measure quantifying regularity and complexity, is believed to be an effective analyzing method of diverse settings that include both deterministic chaotic and stochastic processes, particularly operative in the analysis of physiological signals that involve relatively small amount of data. However, the similarity definition of vectors based on Heaviside function, of which the boundary is discontinuous and hard, may cause some problems in the validity and accuracy of ApEn. To overcome these problems, a modified ApEn based on fuzzy similarity (mApEn) was proposed. The performance on the MIX stochastic model, as well as those on the Logistic map and the Hennon map with noise, shows that the fuzzy similarity-based ApEn gets more satisfying results than the standard ApEn when characterizing systems with different regularities.