Biomedical Image Processing / Medical Image Processing
Fateme Nazem; Alireza Ahmadian; Mohammad Javad Abolhasani; Nasim Dadashi; Masoume Gity; Mohammad Bagher Shiran
Volume 5, Issue 4 , June 2011, , Pages 351-358
Abstract
Abstract: Image guided liver surgery based on intra-operative ultrasound images has received much attention in recent years. Using an efficient point-based registration method to improve both the accuracy and computational time for registration of pre-deformation CT liver images to post-deformation Ultrasound ...
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Abstract: Image guided liver surgery based on intra-operative ultrasound images has received much attention in recent years. Using an efficient point-based registration method to improve both the accuracy and computational time for registration of pre-deformation CT liver images to post-deformation Ultrasound images is of great concern during surgical procedure. Although, Iterative Closest Point (ICP) algorithm is widely used in surface-based registration, its performance is strongly dependent on existence of noise and initial alignment. The registration technique based on the Unscented Kalman Filter (UKF) proposed recently can be a solution to overcome to noise and outliers on an incremental registration basis but it suffers from computational complexity. To overcome the limitations of ICP and UKF algorithms we proposed an incremental two-stage registration algorithm based on the combination of ICP and UKF algorithm to update the registration process based on arrival of intra-operative images. The two-stage algorithm is examined on phantom data sets. The results of phantom study confirm that the two-stage algorithm outperforms the accuracy of ICP and UKF by 23% and 13%, respectively and reduces the running time of UKF by 60%.
Mohammad Javad Abolhassani; Yousef Salimpour; Parisa Rangraz
Volume 4, Issue 3 , June 2010, , Pages 249-256
Abstract
An otoacoustic emission is a low-level acoustic signal which is generated in cochlea. It could be recorded with a sensitive probe in the outer ear canal. OAEs are considered to be related to the amplification function of the cochlea. Outer hair cells are the elements that enhance cochlear sensitivity ...
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An otoacoustic emission is a low-level acoustic signal which is generated in cochlea. It could be recorded with a sensitive probe in the outer ear canal. OAEs are considered to be related to the amplification function of the cochlea. Outer hair cells are the elements that enhance cochlear sensitivity and frequency selectivity and hence act as the energy sources for amplification. Otoacoustic emission is transmitted through oval window to the outer ear canal, the distortion effects of middle ear and outer ear on the recorded signal are inevitable. Currently all clinical applications of otoacoustic emission are based on distorted measurement. For estimating the original otoacoustic emission produced in cochlea the middle ear and the outer ear effects must be compensated. The computational model of the auditory periphery is used to design a compensation filter for the estimation of the otoacoustic emission right after production and before entering the middle ear. Using Middle ear reverse transfer function and primary input signal Fourier transforms, OAE estimation before middle ear was obtained. The results of comparison of the estimated signal with the recorded one indicate that, due to the noise reduction and increase in reproducibility as a main criteria in hearing screening, the assessment based on the estimated otoacoustic emission is closer to the real response of the auditory system.
Biomedical Image Processing / Medical Image Processing
Bahram Momen Mehrabani; Mohammad Javad Abolhassani; Alireza Ahmadian; Javad Alirezaie
Volume 3, Issue 1 , June 2009, , Pages 47-54
Abstract
The main purpose of this work is introducing a novel method of temperature monitoring using B-Mode Ultrasound digital images. Thermal dependence of sound speed causes a virtual displacement of scatterer particles. The virtual displacement is computed using speckle tracking methods. Horn-Shunck algorithm ...
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The main purpose of this work is introducing a novel method of temperature monitoring using B-Mode Ultrasound digital images. Thermal dependence of sound speed causes a virtual displacement of scatterer particles. The virtual displacement is computed using speckle tracking methods. Horn-Shunck algorithm was applied to a tissue mimicking phantom to measure the virtual displacement. A heating resistor was used in this phantom to generate temperature elevation. The DICOM ultrasound images were acquired using commercial SIMENES ultrasound imaging system with 10MHz linear probe. The accuracy of noninvasive temperature estimation was measured comparing with invasive temperature measurement. The phantom is warmed up to the 8. The mean error of temperature estimation was found to be 0.4°C and peak error 0.9°C. Fast temperature estimation can be achieved using Optical-Flow methods. This Method is a differential based motion estimation method that estimates displacement by calculating the optical pattern changes caused by movements between two frames. Noise sensitivity is the main infirmity of Horn-Schunck method.
Cardiovascular Biomechanics
Nima Hemati; Mohammad Javad Abolhassani
Volume -2, Issue 1 , July 2005, , Pages 35-46
Abstract
Nowadays, various methods have been suggested to measure and monitor blood velocity variation in arteries and veins. Ultrasonic velocimetry is one of these methods, which is based on Doppler shift frequency measurement and the blood flow velocity calculation using Doppler shift signal. Using velocity-time ...
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Nowadays, various methods have been suggested to measure and monitor blood velocity variation in arteries and veins. Ultrasonic velocimetry is one of these methods, which is based on Doppler shift frequency measurement and the blood flow velocity calculation using Doppler shift signal. Using velocity-time curves or frequency spectrum which is system outputs, the abnormal cases and the stenosis degree can be determined. In this study, the design and prototyping of a pulsed Doppler system are investigated. The design consists of analog and digital circuits. The analog section includes Master oscillator, stimulus generator, transmitter, receiver, RF amplifier, demodulator and signal sampling circuits. Analog Doppler signal is then converted to digital codes and transferred to PC via an analog to digital converter card. The controlling of analog circuits is also implemented by the digital control unit. After data being transferred to the PC, data analysis such as fast fourier transform (FFT), monitoring of blood velocity variation with time and computation of two dimensional spectrogram are implemented by a software which was written in the Visual C++6 environment. In order to test the system, a string Doppler phantom with full electronic control was built. This phantom also can be used to test and control the quality of the other clinical ultrasonic Doppler systems.
