Eigen-based clutter filter design for ultrasound color flow imaging: A review

Proper suppression of tissue clutter is a prerequisite for visualizing flow accurately in ultrasound color flow imaging. Among various clutter suppression methods, the eigen- based filter has shown potential because it can theoretically adapt its stopband to the actual clutter characteristics even when tissue motion is present. This paper presents a formative review on how eigen-based filters should be designed to improve their practical efficacy in adaptively suppressing clutter without affecting the blood flow echoes. Our review is centered around a comparative assessment of two eigen-filter design considerations: 1) eigen-component estimation approach (single-ensemble vs. multi-ensemble formulations), and 2) filter order selection mechanism (eigenvalue-based vs. frequencybased algorithms). To evaluate the practical efficacy of existing eigen-filter designs, we analyzed their clutter suppression level in two in vivo scenarios with substantial tissue motion (intra-operative coronary imaging and thyroid imaging). Our analysis shows that, as compared with polynomial regression filters (with or without instantaneous clutter downmixing), eigen-filters that use a frequency-based algorithm for filter order selection generally give Doppler power images with better contrast between blood and tissue regions. Results also suggest that both multi-ensemble and single-ensemble eigen-estimation approaches have their own advantages and weaknesses in different imaging scenarios. It may be beneficial to develop an algorithmic way of defining the eigen-filter formulation so that its performance advantages can be better realized. © 2010 IEEE.published_or_final_versio

Eigen-based clutter filters for color flow imaging: Single-ensemble vs. multi-ensemble approaches

In designing eigen-based clutter filters for color flow imaging, one of the challenges is to develop an accurate way of estimating the eigen-components that represent clutter in slow-time ensembles. To provide new insights on the problem, this paper presents a comparative analysis on how eigen-filters perform when using eigen-estimation methods that involve multiple ensembles or a single ensemble. The analysis consists of two parts: 1) a comparative review on the principles behind different eigen-estimation methods; 2) an eigen-filtering experiment done with coronary flow imaging data acquired from a porcine during bypass graft operation. For an imaging case containing tissue motion due to myocardial contraction, our analysis showed that the single-ensemble eigen-filter shared similar performance with a multi-ensemble eigen-filter that uses small (5×5) ensemble windows (with about 1 dB difference in clutter suppression level). Results also showed that a multi-ensemble eigen-filter with large (20x20) ensemble windows yielded poorer performance (clutter suppression level was 3 to 6 dB lower). © 2007 IEEE.published_or_final_versionThe 2007 IEEE Ultrasonics Symposium, New York, N.Y., 28-31 October 2007. In Conference Proceedings of IEEE Ultrasonics Symposium, 2007, p. 1101-110

In vivo investigation of filter order influence in eigen-based clutter filtering for color flow imaging

Eigen-based adaptive filters have shown potential for providing a superior attenuation of clutter in color flow imaging. Critical for the success of this technique is the correct selection of filter order. In this work we review and compare filter order selection schemes for eigen-based filters in an in vivo context. Data was acquired from a thyroid tumor (PRF = 250 Hz, ensemble size = 12), where substantial tissue movement was present due to carotid artery pulsations, respiratory movements, and probe navigation. Eigen-filtering performance was evaluated for 1) an eigenvalue spectrum threshold, 2) a threshold on the ratio of successive eigenvalues, and 3) a threshold on eigenvector mean frequency estimated by the autocorrelation approach. Based on the observed eigenvalue and eigen-frequency distributions in analytical and in vivo examples, all filter order algorithms investigated suffered from potential pitfalls in specific Doppler scenarios. In the in vivo examples, the fixed order eigenfilter gave a sufficient suppression of clutter, but also removed substantial blood signal. Thresholding the ratio of eigenvalues better retained signal from blood, but also spurious artifacts was observed. The most consistent results were achieved by thresholding the mean frequency of the eigenvectors. The results demonstrate that given a suitable filter order algorithm, robust filtering can be achieved with the eigen-based approach. © 2007 IEEE.published_or_final_versio

Developing a new sonoporation treatment model using plants: cellular mechanism analysis

Poster Session P2Aa. a - Bio-effects: no. P2Aa-2Plant cells (BY-2 tobacco) are used in this work as a new cellular model for investigating the biological mechanisms behind sonoporation-induced cytotoxic effects. We show that sonoporation may lead to chronic depolarization of plasma membrane and depolarization of mitochondrial membrane: both of which are known to be linked to a cell’s programmed cell death protocol. These findings are obtained in-vitro from BY-2 cell suspensions that were exposed to pulsed ultrasound for 1 min. (1 MHz ultrasound frequency, 10% duty cycle, 1 kHz pulse repetition frequency, 0.4 or 0.9 MPa peak negative pressure, 1% v/v microbubbles). Two potentio-dependent fluorescence probes (DiBAC4(3) and TMRE) were used to analyze the changes in the plasma membrane and mitochondrial membrane potential of the sonoporated cells at four post-exposure time points (0 h, 2 h, 4 h, 6 h). These changes were monitored by confocal and fluorescence microscopy, and they were quantified using a spectrofluorometer. The membrane depolarization effects are generally found to be more significant at higher peak negative pressures (0.9 MPa in our case).published_or_final_versionThe 2011 IEEE International Ultrasonics Symposium (IUS), Orlando, FL., 18-21 October 2011. In IEEE International Ultrasonics Symposium Proceedings, 2011, p. 616-61

Implementasi Model Pembelajaran Kooperatif Talking Chips dan Fan-n-pick dalam Meningkatkan Motivasi dan Hasil Belajar IPS

This study is aimed to describe how Talking Chips and Fan-N-Pick learning model to improve VIII D class students\u27 motivation and learning outcomes at SMP Kristen Citra Bangsa Kota Kupang. The study is a Classroom Action Research (CAR) study. The study consists of four phases, i.e. plan, action, observation, and reflection. The phases in CAR are conducted in 2 cycles. The subject of the study is 20 VIII D class students of SMP Kristen Citra Bangsa Kota Kupang. The collected data consists of students\u27 motivation and learning result test. The result of the study shows that there is an improvement on students\u27 motivation in the first cycle and the high criteria is improved to very high criteria in the end of the second cycle. The improvement is also occurred in students\u27 learning outcome and implementation whether it is from the students or the teacher.Penelitian ini bertujuan untuk mendeskripsikan bagaimana penerapan model pembelajaran Talking Chips dan Fan-N-Pick untuk meningkatkan motivasi dan hasil belajar siswa kelas VIII-D di SMP Kristen Citra Bangsa Kota Kupang. Jenis penelitian ini adalah Penelitian Tindakan Kelas (PTK). Penelitian ini terdiri atas empat tahap, yaitu tahap perencanaan, pelaksanaan, pengamatan/observasi dan refleksi. Tahapan dalam PTK ini dilaksanakan dalam dua siklus. Subjek dalam penelitian ini ialah siswa kelas VIII-D SMP Kristen Citra Bangsa Kupang yang berjumlah 20 orang. Data yang dikumpulkan dalam penelitian ini adalah motivasi siswa dan tes hasil belajar. Hasil penelitian menunjukan terjadinya peningkatan motivasi siswa pada siklus I dengan kriteria tinggi meningkat menjadi sangat tinggi pada akhir siklus II. Peningkatan juga terjadi pada hasil belajar siswa dan keterlaksanaan pembelajaran baik oleh guru dan siswa

Adaptive clutter filter design for micro-ultrasound color flow imaging of small blood vessels

In micro-ultrasound, which uses imaging frequencies above 20 MHz, obtainingcolor flow images (CFI) of small blood vessels using is not a trivial taskbecause it is more challenging to suppress tissue clutter properly given thestronger blood signal power at high imaging frequencies and the slow bloodvelocity inside the microcirculation. To improve clutter suppression inmicro-ultrasound CFI, this paper presents an adaptive clutter filtering approachthat is based on a two-stage eigen-analysis of slow-time ensemblecharacteristics. The approach first identifies tissue pixels in the imaging viewby examining whether high-frequency contents are absent in the principalslow-time eigen-components for each pixel as computed from single-ensembleeigen-decomposition. It then computes the filtered slow-time ensemble for eachpixel by finding the least-squares projection residual between the pixel'sslow-time ensemble and the clutter eigen-components estimated from amulti-ensemble eigen-decomposition of tissue slow-time ensembles within aspatial window. In this filtering approach, the clutter eigen-components arechosen based on whether their mean frequency lies within a spectral band. Toanalyze the efficacy of the proposed adaptive filter, both in-vitro experimentsand Field II simulations were carried out. For the experiments, raw CFI datawere acquired using a 64-element, 33 MHz linear array prototype (pulse duration:2 cycles, PRF: 1 kHz, transmit focus: 8mm, F-number: 5). Their imaging viewcorresponded to the cross-section of a 0.9mm-diameter tube that was placed ontop of an unsuspended table where ambient vibrations may appear; flow velocity(5, 7, 10, 15 mm/s) within the tube was controlled using a syringe pump. For thesimulations, raw CFI data was computed for both plug and parabolic flowprofiles, and tissue motion was modeled as 0.5 mm/s sinusoidal vibrations. Forall flow velocities tested in our in-vitro study, the proposed adaptive filterimproved the flow detection sensitivity as compared to existing ones. In theslow-flow case (5 mm/s), we observed over 70% increase in flow detectionsensitivity (assuming a 5% false alarm rate). This effectively reduced flashingartifacts in the resulting CFIs and gave a more consistent visualization of theflow tube. © 2010 IEEE.published_or_final_versionThe 2010 IEEE International Ultrasonics Symposium, San Diego, CA.,, 11-14 October 2010. In Proceedings of IEEE IUS, 2010, p. 1206-120

Design of a programmable micro-ultrasound research platform

To foster innovative uses of micro-ultrasound in biomedicine, it is beneficial to develop flexible research-purpose systems that allow researchers to easily reconfigure its system-level operations such as transmit firing sequence and receive processing. In this paper, we present the development of a programmable micro-ultrasound research platform that is capable of realizing various micro-imaging algorithms. The research platform comprises a linear-array-based scanning front-end and a PC-based data processing back-end, which employs a graphical processing unit (GPU) as the processor core. The front-end operations can be configured from the PC via the parallel port and the two blocks are synchronized by an external clock. Acquired data from the front-end is first digitized and relayed to the PC through an data acquisition card (200 MHz, 14-bit). They are then transferred to the GPU (GTX 275) in which the image formation is carried out via multi-thread processing. Results are displayed on-screen in real-time and can be saved to the PC's hard disk for offline analysis. Through a module-based programming approach, this platform can facilitate realization of custom-designed imaging algorithms developed by researchers. In this work, B-mode imaging and adaptive color flow imaging have been implemented as demonstrations of the research platform's programmability. The performance results show that real-time processing frame rates can be achieved for both imaging modes. © 2010 IEEE.published_or_final_versionThe 2010 IEEE International Ultrasonics Symposium, San Diego, CA., 11-14 October 2010. In Proceedings of IEEE IUS, 2010, p. 1980-198