High-quality reconstruction of four-dimensional cone beam CT from motion registration prior image / 南方医科大学学报

Four-dimensional cone beam CT (4D-CBCT) imaging can provide accurate location information of real-time breathing for imaging-guided radiotherapy. How to improve the accuracy of 4D-CBCT reconstruction image is a hot topic in current studies. PICCS algorithm performs remarkably in all 4D-CBCT reconstruction algorithms based on CS theory. The improved PICCS algorithm proposed in this paper improves the prior image on the basis of the traditional PICCS algorithm. According to the location information of each phase, the corresponding prior image is constructed, which completely eliminates the motion blur of the reconstructed image caused by the mismatch of the projection data. Meanwhile, the data fidelity model of the proposed method is consistent with the traditional PICCS algorithm. The experimental results showed that the reconstructed image using the proposed method had a clearer organization boundary compared with that of images reconstructed using the traditional PICCS algorithm. This proposed method significantly reduced the motion artifact and improved the image resolution.

Palm vein recognition based on end-to-end convolutional neural network / 南方医科大学学报

We propose a novel palm-vein recognition model based on the end-to-end convolutional neural network. In this model, the convolutional layer and the pooling layer were alternately connected to extract the image features, and the categorical attribute was estimated simultaneously via the neural network classifier. The classification error was minimized via the mini-batch stochastic gradient descent algorithm with momentum to optimize the feature descriptor along with the direction of the gradient descent. Four strategies including data augmentation, batch normalization, dropout, and L2 parameter regularization were applied in the model to reduce the generalization error. The experimental results showed that for classifying 500 subjects form PolyU database and a self-established database, this model achieved identification rates of 99.90% and 98.05%, respectively, with an identification time for a single sample less than 9 ms. The proposed approach, as compared with the traditional method, could improve the accuracy of palm vein recognition in clincal applications and provides a new approach to palm vein recognition.

Automatic extraction of the pennation angle of the gastrocnemius muscles from ultrasound radiofrequency signals / 南方医科大学学报

<p><b>OBJECTIVE</b>We propose a cross-correlation method for automatic extraction of the pennation angle (PA) of the gastrocnemius (GM) muscle from ultrasound radiofrequency (RF) signals.</p><p><b>METHODS</b>The ultrasound RF signals of the GM muscles in tension condition from normal subjects and the simulated ultrasound signals were collected. After the starting point of tracking, a fascicle was selected in the reconstructed GM ultrasound image from the RF signals, and the fascicle and deep aponeurosis could be automatically tracked using the cross-correlation algorithm. The lines of the fascicle and deep aponeurosis were then drawn and the PA was calculated. The reproducibility of the proposed method and its consistency with the manual measurement method were tested.</p><p><b>RESULTS</b>The angles of the simulated fascicles were precisely extracted automatically. The difference between the experimental measurement and the theoretical values was less than 1°. The PA measured automatically and manually was 20.48°∓0.47° and 21.49°∓1.79°, respectively. The coefficient of variation (CV) of the two methods was less than 3% and the root-mean square error (RMSE) was less than 1°. Bland-Altman plot showed a good agreement between the proposed automatic method and the manual method.</p><p><b>CONCLUSION</b>The proposed cross-correlation automatic measurement method can detect the orientation of the fascicle and deep aponeurosis and measure the PA based on ultrasound RF signals with serious speckle noise.</p>

Brain image segmentation based on multi-weighted probabilistic atlas / 南方医科大学学报

We propose a multi-weighted probabilistic atlas to obtain accurate, robust, and reliable segmentation. The local similarity measure is used as the weight to compute the probabilistic atlas, and the distance field is used as the weight to incorporate the locality information of the atlas; the self-similarity is used as the weight to incorporate the local information of target image to refine the probabilistic atlas. Experimental results with brain MRI images showed that the proposed algorithm outperforms the common brain image segmentation methods and achieved a median Dice coefficient of 87.1% on the left hippocampus and 87.6% on the right.

An automatic subregion delineation method for T2 measurement of articular cartilage in the knee / 南方医科大学学报

<p><b>OBJECTIVE</b>To propose a new method for automatic segmentation of manually determined knee articular cartilage into 9 subregions for T2 measurement.</p><p><b>METHODS</b>The middle line and normal line were automatically obtained based on the outline of articular cartilage manually drawn by experienced radiologists. The region of articular cartilage was then equidistantly divided into 3 layers along the direction of the normal line, and each layer was further equidistantly divided into 3 segments along the direction of the middle line. Finally the mean T2 value of each subregion was calculated. Bland-Altman analysis was used to evaluate the agreement between the proposed and manual subregion segmentation methods.</p><p><b>RESULTS</b>The 95% limits of agreement of manual and automatic methods ranged from -3.04 to 3.20 ms, demonstrating a narrow 95% limits of agreement (less than half of the minimum average). The coefficient of variation between the manual and proposed subregion methods was 4.04%.</p><p><b>CONCLUSION</b>The proposed subregion segmentation method shows a good agreement with the manual segmentation method and minimizes potential subjectivity of the manual method.</p>

Decoupling of multi-channel RF coil and its application in the intraoperative MRI / 生物医学工程学杂志

The coupling from different elements of the multi-channel coil leads to the splitting of the resonance frequency and deviation from the Lamor frequency. Decoupling between different elements is the key technology in the design of the radiofrequency (RF) coil. The electrical decoupling circuits should vary with different arrangements of the elements. A novel method of decoupling for the RF coil used in the intraoperative MR-guided focused ultrasound system is reported in the paper. The prototype RF coil was made according to the proposed decoupling method. The bench test of the prototype showed that the performance of the decoupling of the coil was excellent. The images in vivo were acquired with the designed prototype RF coil.

A new algorithm for affine motion compensation in PROPELLER MRI based on image domain / 生物医学工程学杂志

Affine motion is common during PROPELLER magnetic resonance imaging (MRI) in abdomen or other soft tissues. The current algorithm, up till now, for affine motion compensation is based on frequency domain, which compensates the motion in k space and then reconstruct the final image based on gridding method. But aliasing and some tiny artifacts may exist. This paper proposed a new algorithm for affine motion compensation based on image domain. Firstly, exact affine motion information was obtained through the image registration, secondly k space coordinate was corrected for compensating the k space strips sampling density, then the images obtained from inverse FFT was compensated using motion information, finally the final results were composited after rotation. The experimental results showed that the proposed method could more effectively suppress the motion artifacts compared to the current algorithm.

Fast 3D Medical Image Segmentation Based on CUDA / 中国医学物理学杂志

Objective: 3D segmentation is an important part of medical image analysis and visualization. It also continues to be large challenge in the medical image segmentation. While level sets have demonstrated a great potential for 3D medical image segmentation, these algorithms have a large computational burden thus are not suitable for real time processing requirement. To solve this problem, we propose a parallel accerelated method based on CUDA. Methods: We implement C-V level set algorithm in the CUDA environment which is the NVIDIA's GPGPU model.The segmentation speed can greatly improved by using independence of image pixel and concurrence of partial differential equation .The paper shows the flow chart of the parallel computing and gives the detailed introduction of the C-V level set algorithm which is implemented in the CUDA environment. Results: Realizing the C-V level set parallel accerelated algorithm. This method has faster segmentation speed while preserving the qualitative results, Conclusions: This method is viable and makes the fast 3D medical image segmentation come hue.

2D, 3D Rigid Registration Algorithm Base on CUDA / 中国医学物理学杂志

Objective: Real time medical image registration technique is one of the key techniques in image based surgery navi-gation system. While in medical image analysis, image registration is usually a very time-cousuming operation, and this is not conducive to clinical real-time requirements. This paper studies and realizes the acceleration of the process of image registra-tion. Methods: In order to improve the regisWation rate, in this paper, we propose a new technology which is based on CUDA (Compute Unified Device Architecture) programming model to accelerate the process of registration in hardware, using paral-lel methods to achieve pixel coordinate transformation, linear interpolation, and calculate the corresponding pixel gray value residuals. Results: The registration is up to the sub-pixel level and the GPU-based registration is dozens or even hundreds of times faster than CPU-based registration. Conclusions: This method greatly enhances the speed of rigid registration without changing the alignment accuracy.

Segmentation of multiple sclerosis lesions based on Markov random fields model for MR images / 生物医学工程学杂志

Multiple sclerosis (MS) is an inflammatory demyelinating disease that would damage central nervous system. There is a growing attention to the segmentation algorithms of MS Lesions. An MRF-based algorithm for MS lesions segmentation of T2-weighted MR brain images is developed by utilizing the morphological characteristics of MS lesion tissues. The regions circumscribed by white matter are extracted at first by MRF-based segmentation and region growing methods; the abstracted regions are then segmented again using MRF-based algorithm. The segmented MS lesions of both simulated and clinical T2-weighted MR brain images are presented in the current work. The testing results show that the proposed algorithm is robust and accurate enough for clinical use.

Radiotherapy Optimization for Lung Cancer Based on Medical Image Analysis Technique / 医学研究杂志

Objective To evaluate the feasibility of using medical image analysis for adaptive radiotherapy of lung cancer by drawing the individual contours automatically or interactively and adjusting the planning target volume weekly for reducing the volume of the excessive irradiated normal lung tissue.Methods Many CT images of the GTV and dynamic X-ray fluoroscope data of 23 patients were acquired and all the data were used for working out the tumor radiotherapy plan(TPS) and positioning the patient and to measure reduction in GTV volume.A planning study was conducted to determine the amount of lung-sparing that could have been achieved if adaptive therapy had been used.Treatment plans were created in which the target volumes were reduced after tumor reduction was measured.Results A total of 6313 CT imaging sessions and 78 groups of X-ray dynamic fluoroscope data were performed on 23 lung patients.The GTV was reduced by 70%～80% during the course of treatment.Based on these treatment planning studies,the dose of ipsilateral lung can be reduced significantly by adapting the treatment delivery.Conclusion Medical image analysis can be used to position the GTV and CTV of the tumors.This technology can help to work out the individual TPS and adjust the radiotherapy treatment plan adaptively during the course of treatment and reduce the dose of normal tissues as well as insure the effect of tumor treatment.

System planning of characteristic education in biomedical engineering / 医疗卫生装备

The system planning of characteristic education in biomedical engineering was performed,in which such ideas were raised as clear-cut cultivation target,self-contained curricula system and flexible experimental technique.The system planning provided systematic knowledge structure and the induction from theory to practice for undergraduates in 5 majors in our school.Based on this system planning,the teaching quality is improved.

Medical image elastic registration smoothed by unconstrained optimized thin-plate spline / 生物医学工程学杂志

Elastic registration of medical image is an important subject in medical image processing. Previous work has concentrated on selecting the corresponding landmarks manually and then using thin-plate spline interpolating to gain the elastic transformation. However, the landmarks extraction is always prone to error, which will influence the registration results. Localizing the landmarks manually is also difficult and time-consuming. We the optimization theory to improve the thin-plate spline interpolation, and based on it, used an automatic method to extract the landmarks. Combining these two steps, we have proposed an automatic, exact and robust registration method and have gained satisfactory registration results.

A novel classification-coding scheme for medical image retrieval / 医疗卫生装备

A novel mono-hierarchical muti-axiel classification coding scheme for medical image retrieval is proposed.The so-called MOAB coding scheme consists of four axes with three to four positions ranging from0to9,from A to Z.In particular,the modality code M describes imaging modality and relevant technical detail,and the orientation code O models examined body orientation.The anatomy code A refers to the body region examined and the biology code B describes the biological system examined.The MOAB classification-coding scheme enables a unique classifi-cation of medical images so that medical image retrieval can be efficient.The code is flexible and easy to be ex-tended.

Research of Medical Virtual Endoscopy System Based on VTK / 医疗卫生装备

Objective To develop a virtual endoscopy system which can be integrated into PACS.Methods Key techniques on virtual endoscopy were researched and we implemented a virtual endoscopy system with the help of the Visualization Toolkit VTK.Results The Virtual endoscopy system was integrated into PACS and the post-processing function of PACS was advanced.Conclusion As a novel medical image post-processing technology,virtual endoscopy provides a completely non-invaded inspection,so it has broad application prospects in the computer-aided medical teaching,surgical navigation,surgical planning and clinical diagnosis.

Realizing generalized registration of medical sequence image using mutual information criterion / 中国医学物理学杂志

Mutual information(MI) is a tool of measuring the statistical dependence between two random variables. MI between two images, being considered as two random fields, can be calculated to determine the degree of information redundancy between the image intensities of corresponding pixels in both images. In this paper, we utilize the MI criterion to realize the generalized registration between two neighboring slices in a medical image sequence (CT, MR et al) and consider that they match with each other if the MI between them is maximal. Experimental results confirm performance of our algorithm.

Study on Experimental Platform Construction of BME Experimental Teaching Demonstration Center / 医疗卫生装备

According to the thoughts of experimental platform construction of the BME experimental teaching demonstration center,the education and institution construction relevant to concrete operating steps and methods are carried on.The engineering experimental platform featuring "Multiple-structure,Multiple-specialty,Integration,Open-type" are substantiated and perfected.A batch of advanced instruments for experimental teaching are purchased.The methods and measures for experimental teaching are improved.The scientific research is permeated into the student's experimental teaching for cultivation innovative talents.

Reform and Practice of Undergraduate Theses and Projects of Biomedical Engineering / 医疗卫生装备

To enhance the quality project,there are four ways to ensure the quality of the undergraduate thesis and project.The first way is to inaugurate new bases: from school to company.The second is a wide choice of projects.The third way is that the project can be taken ahead of schedule.Finally,two tutors are designated to ensure the quality of thesis.

Inhomogeneous magnetic resonance image segmentation by spatial model to fuzzy clustering / 医疗卫生装备

Fuzzy c-means (FCM) clustering algorithm is a popular model widely used in the segmentation of magnetic resonance image (MRI). The conventional FCM doesn't involve the spatial information of MRI and then unexpected segmentation results appear when it is applied to inhomogeneous MRI with noise and bias field. Modifying the objective function of FCM and introducing a variable as the parameter to control the tight degree of neighborhood effect present a spatial model to FCM clustering algorithm. The variable can reasonably use the spatial information of MRI. The experiment results show that the proposed algorithm can provide a powerful segmentation than the conventional FCM and others.