Browsing by Author "Muslu, Yavuz"

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    4,8 T/m manyetik parçacık görüntüleme tarayıcı tasarımı ve yapımı
    (IEEE, 2018) Ütkür, Mustafa; Muslu, Yavuz; Sarıtaş, Emine Ülkü
    Manyetik Parçacık Görüntüleme (MPG), ilk yayımlandığı 2005 yılından bu yana hızla gelişerek anjiyografi, kök hücre takibi ve kanser görüntüleme gibi uygulama alanlarında ciddi ilerlemeler kaydetmiştir. İyonlaştırıcı ışıma kullanmaması ve kullandığı izleyici maddelerin sağlığa zararlı olmayan demir oksit nanoparçacıkları olması sayesinde güvenli bir görüntüleme yöntemi olarak umut vaad etmektedir. Henüz insan boyutunda bir MPG tarayıcı yapılmamıs¸ olsa da yapılan preklinik araştırmalar MPG’nin milimetre altı çözünürlüğe sahip olduğunu göstermektedir. Bu çalışmada Bilkent Ulusal Manyetik Rezonans Araştırma Merkezi (UMRAM) bünyesinde geliştirdiğimiz ilk MPG tarayıcının tasarım ve yapım aşamaları sunulmaktadır. Bu MPG tarayıcı x-yönünde 4,8 T/m seçme alanı gradyanına sahiptir, ve 9,7 kHz eksitasyon alan frekansı kullanmaktadır.
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    Blind source separation for multi-color MPI
    (International Journal on Magnetic Particle Imaging, 2020) Kurt, Semih; Muslu, Yavuz; Sarıtaş, Emine Ülkü
    In magnetic particle imaging (MPI), different magnetic nanoparticles (MNPs) in the same field-of-view can be distinguished via color-MPI techniques. Existing system-function-based techniques require extensive calibration scans, whereas x-space-based approaches require either multiple scans at different drive field parameters, or rely on the underlying mirror symmetry of the adiabatic MPI signal. In this work, we propose a novel blind source separation technique for multi-color MPI, exploiting the distinct signal delays of different MNPs. The proposed technique blindly decomposes the MPI signals from different MNPs, which can then be individually reconstructed and assigned to separate color channels to form a multi-color MPI image.
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    Calibration-free relaxation-based multi-color magnetic particle imaging
    (Institute of Electrical and Electronics Engineers, 2018) Muslu, Yavuz; Utkur, Mustafa; Demirel, Ömer Burak; Sarıtaş, Emine Ülkü
    Magnetic particle imaging (MPI) is a novel imaging modality with important potential applications, such as angiography, stem cell tracking, and cancer imaging. Recently, there have been efforts to increase the functionality of MPI via multi-color imaging methods that can distinguish the responses of different nanoparticles, or nanoparticles in different environmental conditions. The proposed techniques typically rely on extensive calibrations that capture the differences in the harmonic responses of the nanoparticles. In this paper, we propose a method to directly estimate the relaxation time constant of the nanoparticles from the MPI signal, which is then used to generate a multi-color relaxation map. The technique is based on the underlying mirror symmetry of the adiabatic MPI signal when the same region is scanned back and forth. We validate the proposed method via simulations, and via experiments on our in-house magnetic particle spectrometer setup at 10.8 kHz and our in-house MPI scanner at 9.7 kHz. Our results show that nanoparticles can be successfully distinguished with the proposed technique, without any calibration or prior knowledge about the nanoparticles.
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    Effects of drive field parameters in magnetic particle imaging: A relaxometer study
    (IEEE, 2018) Bozkurt, Ecem; Ütkür, Mustafa; Muslu, Yavuz; Sarıtaş, Emine Ülkü
    In Magnetic Particle Imaging (MPI), it is possible to acquire signal from the nanoparticles via applying oscillating magnetic fields in the 1 kHz -150 kHz frequency range. Though 25 kHz is commonly used, there are not enough studies on determining the optimal excitation frequency and excitation strength for obtaining images of high quality. In this study, we observed nanoparticles' response and the effect on the point spread functions (PSF) at various field amplitudes and at 10 kHz, 25 kHz and 148.5 kHz excitation frequencies. Accordingly, at 10 kHz and 25 kHz both the harmonic response of the nanoparticles and the PSFs are largely similar. On the other hand, the frequency components at 148.5 kHz are decreasing rapidly at increasing harmonics. The larger full-width at half-maximum of the obtained PSF indicates that the image resolution of this image will be lower at this frequency.
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    Partial FOV Center Imaging (PCI): a robust X-space image reconstruction for magnetic particle imaging
    (IEEE, 2020) Kurt, Semih; Muslu, Yavuz; Sarıtaş, Emine Ülkü
    Magnetic Particle Imaging (MPI) is an emerging medical imaging modality that images the spatial distribution of superparamagnetic iron oxide (SPIO) nanoparticles using their nonlinear response to applied magnetic fields. In standard x-space approach to MPI, the image is reconstructed by gridding the speed-compensated nanoparticle signal to the instantaneous position of the field free point (FFP). However, due to safety limits on the drive field, the field-of-view (FOV) needs to be covered by multiple relatively small partial field-of-views (pFOVs). The image of the entire FOV is then pieced together from individually processed pFOVs. These processing steps can be sensitive to non-ideal signal conditions such as harmonic interference, noise, and relaxation effects. In this work, we propose a robust x-space reconstruction technique, Partial FOV Center Imaging (PCI), with substantially simplified pFOV processing. PCI first forms a raw image of the entire FOV by mapping MPI signal directly to pFOV center locations. The corresponding MPI image is then obtained by deconvolving this raw image by a compact kernel, whose fully-known shape solely depends on the pFOV size. We analyze the performance of the proposed reconstruction via extensive simulations, as well as imaging experiments on our in-house FFP MPI scanner. The results show that PCI offers a trade-off between noise robustness and interference robustness, outperforming standard x-space reconstruction in terms of both robustness against non-ideal signal conditions and image quality.
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    Rapid relaxation-based color MPI
    (Infinite Science Publishing, 2020) Arslan, Musa Tunç; Kurt, Semih; Özaslan, Ali Alper; Muslu, Yavuz; Sarıtaş, Emine Ülkü
    Color magnetic particle imaging (MPI) techniques have recently gained popularity, with the purposes of distinguishing different nanoparticle types or nanoparticles in different environments. In this work, we extend a relaxation-based color MPI technique that we recently proposed, and make it applicable to rapid trajectories that distort the underlying mirror symmetry of the adiabatic MPI signal. We propose a method to recover the mirror symmetry, with delay and signal amplitude compensations. The proposed technique rapidly produces a relaxation map of the scanned region, without any prior information about the nanoparticles.
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    Relaxation mapping in magnetic particle imaging
    (2018-01) Muslu, Yavuz
    Magnetic Particle Imaging (MPI) is a novel biomedical imaging modality that shows great potential in terms of sensitivity, resolution, and contrast. Since its first introduction in 2005, several applications of MPI have already been demonstrated such as angiography, stem cell tracking, and cancer imaging. Recently, multi-color MPI techniques have been proposed to increase the functionality of MPI, where different nanoparticles are distinguished according to the differences in their responses to oscillating magnetic fields. These methods can also be extended to probe environmental factors such as viscosity and temperature, provided that the responses of different nanoparticles or nanoparticles in different environments are pre-calibrated. This thesis proposes a new multi-color MPI technique that does not require a calibration phase. This new technique directly estimates the relaxation time constants of nanoparticles to distinguish nanoparticle types and environmental factors from the MPI signal, and generates a multi-color relaxation map. The validity of the proposed technique is confirmed through an extensive experimental work with an in-house Magnetic Particle Spectrometer (MPS) at 10.8 kHz and an in-house MPI scanner at 9.7 kHz drive field frequencies, successfully distinguishing different nanoparticle types. The proposed calibration-free multi-color MPI technique is a promising method for future functional imaging applications of MPI.
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    Relaxation-based color magnetic particle imaging for viscosity mapping
    (American Institute of Physics, 2019) Utkur, Mustafa; Muslu, Yavuz; Sarıtaş, Emine Ülkü
    Magnetic particle imaging (MPI) uses superparamagnetic iron oxide (SPIO) nanoparticles as biomedical imaging tracers. The potential applications of MPI have recently been broadened by the introduction of “color” MPI techniques that can distinguish different nanoparticles and/or environments, e.g., by exploiting the relaxation behavior of SPIOs. One of the important applications of color MPI techniques is viscosity mapping. In this work, we show relaxation-based color MPI experiments that can distinguish the biologically relevant viscosity range of up to 5 mPa s. To find the optimal drive field parameters for viscosity, we compare color MPI results at three different frequencies. We show that frequencies around 10 kHz are well-suited for viscosity mapping using the multicore cluster Nanomag-MIP nanoparticles, providing a one-to-one mapping between the estimated relaxation time constant and viscosity.
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    Relaxation-based viscosity mapping for magnetic particle imaging
    (Institute of Physics Publishing, 2017) Utkur, Mustafa; Muslu, Yavuz; Sarıtaş, Emine Ülkü
    Magnetic particle imaging (MPI) has been shown to provide remarkable contrast for imaging applications such as angiography, stem cell tracking, and cancer imaging. Recently, there is growing interest in the functional imaging capabilities of MPI, where 'color MPI' techniques have explored separating different nanoparticles, which could potentially be used to distinguish nanoparticles in different states or environments. Viscosity mapping is a promising functional imaging application for MPI, as increased viscosity levels in vivo have been associated with numerous diseases such as hypertension, atherosclerosis, and cancer. In this work, we propose a viscosity mapping technique for MPI through the estimation of the relaxation time constant of the nanoparticles. Importantly, the proposed time constant estimation scheme does not require any prior information regarding the nanoparticles. We validate this method with extensive experiments in an in-house magnetic particle spectroscopy (MPS) setup at four different frequencies (between 250 Hz and 10.8 kHz) and at three different field strengths (between 5 mT and 15 mT) for viscosities ranging between 0.89 mPa • s-15.33 mPa • s. Our results demonstrate the viscosity mapping ability of MPI in the biologically relevant viscosity range.