ABSTRACT
The registration of preoperative magnetic resonance (MR) images and intraoperative ultrasound (US) images is very important in the planning of brain tumor surgery and during surgery. Considering that the two-modality images have different intensity range and resolution, and the US images are degraded by lots of speckle noises, a self-similarity context (SSC) descriptor based on local neighborhood information was adopted to define the similarity measure. The ultrasound images were considered as the reference, the corners were extracted as the key points using three-dimensional differential operators, and the dense displacement sampling discrete optimization algorithm was adopted for registration. The whole registration process was divided into two stages including the affine registration and the elastic registration. In the affine registration stage, the image was decomposed using multi-resolution scheme, and in the elastic registration stage, the displacement vectors of key points were regularized using the minimum convolution and mean field reasoning strategies. The registration experiment was performed on the preoperative MR images and intraoperative US images of 22 patients. The overall error after affine registration was (1.57 ± 0.30) mm, and the average computation time of each pair of images was only 1.36 s; while the overall error after elastic registration was further reduced to (1.40 ± 0.28) mm, and the average registration time was 1.53 s. The experimental results show that the proposed method has prominent registration accuracy and high computational efficiency.
Subject(s)
Humans , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Ultrasonography/methods , Algorithms , Surgery, Computer-Assisted/methodsABSTRACT
Due to the advancements in information and communication technologies, the electronic transfer of formal documents such as business deals, etc is inevitable. Therefore a DWT based authentication method is proposed in this paper. The formal text document is watermarked by embedding the fingerprint image of the authenticated personnel. DWT is being widely considered in watermarking applications because of its efficient multi-resolution in frequency domain. The lifting based 2D-DWT with two levels of computation is implemented. The 2D-DWT can be implemented by performing 1D DWT row-wise and column wise. Hence with the help of DWT filters both document and the fingerprint image are compressed and it’s divided into sub-bands and the fingerprint is watermarked in the document. The complete system is implemented on FPGA.
ABSTRACT
Objective:Heart rate variability (HRV) contains a lot of information concerning the cardiovascular regulation,and can be an important indicator,quantitatively reflecting of autonomic nervous function and the normal heart activity,also can play an important role in cardiovascular regulation.Therefore,HRV signals are analyzed using common HRV analysis methods.Methods:Decompose HRV signals of congestive heart failure and normal persons into 6 scales using Multi-resolution analysis.The wavelet coefficient energy is calculated,especially the frequency energy of cd3 to cd6.Results:Energy is mainly concerned in the lower band of high frequency band and low frequency band,where the energy differences between the two groups are more evidence.It's more precise compared to the result with frequency-domain analysis.Conclusions:To gain results with universal law,more different analysis methods need to be improved and lots of researches are necessary.
ABSTRACT
Objective In order to investigate the comlex course of electricity and mechanism of erosive gastritis(EG) and its relative factors,and to extract gastric motility feature indexes.Methods 30 volunteers of erosive gastritis were selected.The signal processing device was designed by Chongqing University of Posts and Telecommunications.By the means of spectrum analysis technic,the signals could be classified according to the dominant power and dominant frequency.Some indexes such as frequency of EGG and IGM,signal power spectrum and dynamic spectrum,the rates of rhythm and power for the normal EGG and IGM and so on could also be calculated.Results The power ratio in 2~4 cpm was 59.2?4.4,the frequency ratio was 70.4?25.5,the frequency instability coefficient was 0.182?0.059,and the power instability coefficient was 1.576?0.481.The parameters changed signifcantly between health adult and patient(P0.05).Conclusion The results of the experiments show that the method based on the synchronous measurement of EGG and IGM can provide a non-invasive way to investigate and evaluate erosive gastritis corresponding to gastrointestinal physiology and pathology conditions.
ABSTRACT
Object detection systems are widely used in many fields. To speed up object detection, a rapid method based on color feature is presented in this paper. Artificial neural network is used for color classification. A series of original objects are gained through searching the most outstanding feature of the marker based on multi-resolution. A set of features obtained from these original objects in the original image, and artificial neural network are used for object classification. Experimental results prove the effectiveness of this method.
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Objecive To discuss a denoise method of gastric impedance signal based on wavelet transform and Stein Unbiased Risk Estimation rule.Methods Firstly,the signal was decomposed by Multi-resolution Analysis(MRA).Secondly,the signal was denoised by Stein Unbiased Risk Estimation rule,whose threshold was adaptive.Results The experimentation results demonstrated that breathing and blood flowing impedance interference could be cancelled effectively by using this method.Conclusion Wavelet analysis provides a new method for further study of gastric motility signal parameter extraction.