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Yao Y.,Northeastern University China | Hao L.,Liaoning Medical University | Geng N.,Northeastern University China | Jin Y.,Northeastern University China | And 3 more authors.
Proceedings of the World Congress on Intelligent Control and Automation (WCICA) | Year: 2015

Carotid pressure waveform is often used to substitute the central aortic pressure waveform, which conveys lots of information regarding cardiovascular system. Thus, a method was proposed to reconstruct the carotid pressure waveform from the radial pressure waveform which can be more conveniently monitored in comparison with the carotid pressure waveform. The reconstruction method was using Finite Impulse Response (FIR) model to calculate mathematical transfer function (TF) between the radial pressure waveform and the carotid pressure waveform. Pulse pressure waveforms of 5 subjects were recorded to test the performance of the TF. Except for some details, the reconstructed carotid pressure waveform is acceptable with the best percent root-mean-square difference (PRD) of 13.60%. © 2014 IEEE.

Yu E.,Northeastern University China | He D.,Northeastern University China | Su Y.,Northeastern University China | Zheng L.,Northeastern University China | And 3 more authors.
2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013 | Year: 2013

Objective: To judge whether the pulse rate variability can be used as a surrogate of heart rate variability, as well as investigate the quantitative relationship between them. Methods: Being simultaneously acquired, the pulse wave and ECG data were denoised, removed baseline drift. Then the pulse rate intervals and heart rate intervals were extracted. Finally, the relationship between the heart rate variability and pulse rate variability were studied in the time domain, frequency domain, and nonlinear analysis. Conclusion: By studying the pulse rate variabilities and heart rate variabilities of 30 healthy adolescents, we find that heart rate variability and pulse rate variability is correlated, but the difference is relatively small, in a resting condition, the difference of time domain is less than 3%, the Frequency domain is less than 9%, the nonlinear is less than 9%, which in a certain extent can replace each other. Furthermore, the influence from the neural regulation and respiration caused the delay of PRV in comparison with HRV, ranging from 6% to 20% of a heartbeat period. The breathing more greatly influences the PRV than HRV. © 2013 IEEE.

Jiang H.,Northeastern University China | Jiang H.,Key Laboratory of Medical Image Computing | Zhao D.,Northeastern University China | Feng T.,Northeastern University China | And 2 more authors.
Computational and Mathematical Methods in Medicine | Year: 2013

A novel method is proposed to establish the classifier which can classify the pancreatic images into normal or abnormal. Firstly, the brightness feature is used to construct high-order tensors, then using multilinear principal component analysis (MPCA) extracts the eigentensors, and finally, the classifier is constructed based on support vector machine (SVM) and the classifier parameters are optimized with quantum simulated annealing algorithm (QSA). In order to verify the effectiveness of the proposed algorithm, the normal SVM method has been chosen as comparing algorithm. The experimental results show that the proposed method can effectively extract the eigenfeatures and improve the classification accuracy of pancreatic images. © 2013 Huiyan Jiang et al.

Jia T.,Northeastern University China | Jia T.,Key Laboratory of Medical Image Computing | Zhang H.,Northeastern University China | Meng H.,Northeastern University China
Bio-Medical Materials and Engineering | Year: 2014

Lung vessels often interfere with the detection of lung nodules. In this paper, a novel computer-Aided lung nodule detection scheme on vessel segmentation is proposed. This paper describes an active contour model which can combine image region mean gray value and image edge energy. It is used to segment and remove lung vessels. A selective shape filter based on Hessian Matrix is used to detect suspicious nodules and remove omitted lung vessels. This paper extracts density, shape and position features of suspicious nodules, and uses a Rule-Based Classification (RBC) method to identify true positive nodules. In the experiment results, the detection sensitivity is about 90% and FP is 1/scan. © 2014 - IOS Press and the authors.

Jiang H.,Northeastern University China | Jiang H.,Key Laboratory of Medical Image Computing | Ma Z.,Northeastern University China | Hu Y.,Northeastern University China | And 2 more authors.
Computational Intelligence and Neuroscience | Year: 2012

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality. © 2012 Huiyan Jiang et al.

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