Browsing by Author "Top, C. B."
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Item Open Access A denoiser scaling technique for plug-and-play MPI reconstruction(Infinite Science Publishing, 2023-03-19) Güngör, Alper; Aşkın, Barış; Alptekin Soydan, D.; Sarıtaş, Emine Ülkü; Top, C. B.; Çukur, TolgaImage reconstruction based on the system matrix in magnetic particle imaging (MPI) involves an ill-posed inverse problem, which is often solved using iterative optimization procedures that use regularization. Reconstruction performance is highly dependent on the quality of information captured by the regularization prior. Learning-based methods have been recently introduced that significantly improve prior information in MPI reconstruction. Yet, these methods can perform suboptimally under drifts in the image scale between the training and test sets. In this study, we assess the influence of scale drifts on the performance a recent plug-ang-play method (PP-MPI) that uses a pre-trained denoiser. We introduce a new denoiser scaling technique that improves reliability of PP-MPI against deviations in image scale. The proposed technique enables high quality reconstructions that are robust against scale drifts between training and testing sets.Item Open Access A simulation study for an open-sided hybrid MPI-MRI scanner(Infinite Science Publishing, 2023-03-19) Karaca, Sefa; Alptekin Soydan, D.; Top, C. B.; Sarıtaş, Emine ÜlküMagnetic particle imaging (MPI) provides images of magnetic nanoparticle distribution without any signal from the surrounding tissue. MPI would benefit from an additional imaging technique that reveals the anatomical background information, required in many applications. Here, we present a simulation study based on our in-house open-sided prototype MPI system, in which the coils can be utilized interchangeably for MPI and MRI data acquisitions. The system can provide a selection field gradient of 0.5 T m−1 for MPI in field free line topology, and a B0 field of up to 50 mT for MRI. We analyze the system-induced deviations on MRI images for different B0 valuesand pulse sequence parameters.Item Open Access Coded scenes for fast system calibration in magnetic particle imaging(IEEE, 2018) Ilbey, S.; Top, C. B.; Güngör, A.; Sarıtaş, Emine Ülkü; Güven, E.Magnetic nanoparticle (MNP) agents have a wide range of clinical application areas for both imaging and therapy. MNP distribution inside the body can be imaged using Magnetic Particle Imaging (MPI). For MPI image reconstruction with the system function matrix (SFM) approach, a calibration scan is necessary, in which a single MNP sample is placed and scanned inside the full field of view (FOV), which is a very time consuming task. In this study, we propose the use of coded scenes that include MNP samples at multiple positions inside the FOV, and reconstruct the SFM using compressed sensing techniques. We used simulations to analyze the effect of number of coded scenes on the image quality, and compare the results with standard sparse reconstruction using single MNP sample scan. The results show that with the proposed method, the required number of measurements is decreased substantially, enabling a fast system calibration procedure.Item Open Access Comparison of system-matrix-based and projection-based reconstructions for field free line magnetic particle imaging(Infinite Science Publishing, 2017) Ilbey, S.; Top, C. B.; Güngör, A.; Çukur, Tolga; Sarıtaş, Emine Ülkü; Güven, H. E.In magnetic particle imaging (MPI), system sensitivity can be enhanced by scanning the sample along a field free line (FFL) instead of a field free point (FFP). FFL MPI data can then be processed via system-matrix or projection-based reconstructions. Here, we compare the relative performance of these two approaches. We assume an ideal FFL (straight and homogeneous), which is translated and rotated in a two-dimensional field-of-view. We simulate the acquired data from a numerical vessel phantom for a broad range of noise levels. For the system-matrix reconstruction, we propose Alternating Direction Method of Multipliers (ADMM) to solve a constrained convex optimization problem. We also analyze the results of the nonnegative fused lasso (NFL) model to compare the performance of ADMM with one of the state-of-the-art system-matrix-based methods. For the projection-based reconstruction, we use the inverse Radon transform formulation with x-space reconstruction. System-matrix-based methods resulted in a higher structural similarity index and contrast compared to the x-space reconstruction method at the expense of longer reconstruction time. Artifacts occurred due to gridding errors for the x-space reconstruction. As expected, ADMM and NFL reconstructions yielded similar image quality.Item Open Access Fast system calibration with coded calibration scenes for magnetic particle imaging(IEEE, 2019) İlbey, Serhat; Top, C. B.; Güngör, Alper; Çukur, Tolga; Sarıtaş, Emine Ülkü; Güven, H. EmreMagnetic particle imaging (MPI) is a relatively new medical imaging modality, which detects the nonlinear response of magnetic nanoparticles (MNPs) that are exposed to external magnetic fields. The system matrix (SM) method for MPI image reconstruction requires a time consuming system calibration scan prior to image acquisition, where a single MNP sample is measured at each voxel position in the field-of-view (FOV). The scanned sample has the maximum size of a voxel so that the calibration measurements have relatively poor signal-to-noise ratio (SNR). In this paper, we present the coded calibration scene (CCS) framework, where we place multiple MNP samples inside the FOV in a random or pseudo-random fashion. Taking advantage of the sparsity of the SM, we reconstruct the SM by solving a convex optimization problem with alternating direction method of multipliers using CCS measurements. We analyze the effects of filling rate, number of measurements, and SNR on the SM reconstruction using simulations and demonstrate different implementations of CCS for practical realization. We also compare the imaging performance of the proposed framework with that of a standard compressed sensing SM reconstruction that utilizes a subset of calibration measurements from a single MNP sample. The results show that CCS significantly reduces calibration time while increasing both the SM reconstruction and image reconstruction performances.Item Open Access Magnetic particle fingerprinting using arbitrary waveform relaxometer(Infinite Science Publishing, 2020) Yağız, Ecrin; Utkur, Mustafa; Top, C. B.; Sarıtaş, Emine ÜlküIn magnetic particle imaging (MPI), the information about the local environment, such as its viscosity and temperature, can be inferred via the relaxation behavior of the nanoparticles. As the nanoparticle signal also changes with drive field (DF) parameters, one potential problem for quantitative mapping applications is the optimization of these parameters. In this work, an accelerated framework is proposed for characterizing the unique response of a nanoparticle under different environmental settings. The proposed technique, called magnetic particle fingerprinting (MPF), rapidly sweeps a wide range of DF parameters, mapping the unique tau-fingerprint of a sample. This technique can enable simultaneous mapping of several parameters (e.g., viscosity, temperature, nanoparticle type, etc.) with reduced scan time.Item Open Access PP-MPI: A deep plug-and-play prior for magnetic particle imaging reconstruction(Springer Cham, 2022-09) Aşkın, Barış; Güngör, Alper; Alptekin Soydan, D.; Sarıtaş, Emine Ülkü; Top, C. B.; Çukur, Tolga; Haq, Nandinee; Maier, Andreas; Qin, Chen; Johnson, Patricia; Würfl, Tobias; Yoo, JaejunMagnetic particle imaging (MPI) is a recent modality that enables high contrast and frame-rate imaging of the magnetic nanoparticle (MNP) distribution. Based on a measured system matrix, MPI reconstruction can be cast as an inverse problem that is commonly solved via regularized iterative optimization. Yet, hand-crafted regularization terms can elicit suboptimal performance. Here, we propose a novel MPI reconstruction “PP-MPI” based on a deep plug-and-play (PP) prior embedded in a model-based iterative optimization. We propose to pre-train the PP prior based on a residual dense convolutional neural network (CNN) on an MPI-friendly dataset derived from magnetic resonance angiograms. The PP prior is then embedded into an alternating direction method of multiplier (ADMM) optimizer for reconstruction. A fast implementation is devised for 3D image reconstruction by fusing the predictions from 2D priors in separate rectilinear orientations. Our demonstrations show that PP-MPI outperforms state-of-the-art iterative techniques with hand-crafted regularizers on both simulated and experimental data. In particular, PP-MPI achieves on average 3.10 dB higher peak signal-to-noise ratio than the top-performing baseline under variable noise levels, and can process 12 frames/sec to permit real-time 3D imaging.Item Open Access Real-time three-dimensional image reconstruction using alternating direction method of multipliers for magnetic particle imaging(IEEE, 2018) İlbey, Serhat; Güngör, A.; Top, C. B.; Sarıtaş, Emine Ülkü; Güven, H. E.Manyetik Parçacık Görüntüleme (MPG), süperparamanyetik demiroksit nanoparçacıklarının uzamsal dağılımını tespit etmekte kullanılan görece yeni bir medikal görüntüleme yöntemidir. MPG’de görüntü geriçatımı için kullanılan yöntemlerden biri sistem matrisi yaklaşımıdır. Bu yöntemde öncelikle kalibrasyon ölçümleri yapılarak sistem matrisi elde edilir. Daha sonra, sistem matrisi ve görüntülenen objeden alınan veri ile bir doğrusal denklem sistemi oluşturulur ve görüntülenen alandaki manyetik parçacık dağılımı yinelemeli düzenlileştirme veya eniyileme algoritmaları ile çözülür. Bu çalışmada, grafik işlemciler kullanılarak yön degiştiren çarpanlar yöntemi ile üç boyutlu bir görüntüleme uzayında gerçek zamanlı görüntü geriçatımı yapılabileceği gösterilmiştir.Item Open Access Tomographic field free line magnetic particle imaging with an open-sided scanner configuration(IEEE, 2020) Top, C. B.; Güngör, AlperSuperparamagnetic iron oxide nanoparticles (SPIONs) have a high potential for use in clinical diagnostic and therapeutic applications. In vivo distribution of SPIONs can be imaged with the Magnetic Particle Imaging (MPI) method, which uses an inhomogeneous magnetic field with a field free region (FFR). The spatial distribution of the SPIONs are obtained by scanning the FFR inside the field of view (FOV) and sensing SPION related magnetic field disturbance. MPI magnets can be configured to generate a field free point (FFP), or a field free line (FFL) to scan the FOV. FFL scanners provide more sensitivity, and are also more suitable for scanning large regions compared to FFP scanners. Interventional procedures will benefit greatlyfrom FFL based open magnet configurations. Here, we present the first open-sided MPI system that can electronically scan the FOV with an FFL to generate tomographic MPI images. Magnetic field measurements show that FFL can be rotated electronically in the horizontal plane and translated in three dimensions to generate 3D MPI images. Using the developed scanner, we obtained 2D images of dot and cylinder phantoms with varying iron concentrations between 11 μg/ml and 770 μg/ml. We used a measurement based system matrix image reconstruction method that minimizes 11-norm and total variation in the images. Furthermore, we present 2D imaging results of two 4 mm-diameter vessel phantoms with 0% and 75% stenosis. The experiments show high quality imaging results with a resolution down to 2.5 mm for a relatively low gradient field of 0.6 T/m.Item Open Access TranSMS: transformers for super-resolution calibration in magnetic particle imaging(Institute of Electrical and Electronics Engineers Inc., 2022-07-11) Gungor, Alper; Askin, Baris; Soydan, D.A.; Saritas, Emine Ulku; Top, C. B.; Çukur, TolgaMagnetic particle imaging (MPI) offers exceptional contrast for magnetic nanoparticles (MNP) at high spatio-temporal resolution. A common procedure in MPI starts with a calibration scan to measure the system matrix (SM), which is then used to set up an inverse problem to reconstruct images of the MNP distribution during subsequent scans. This calibration enables the reconstruction to sensitively account for various system imperfections. Yet time-consuming SM measurements have to be repeated under notable changes in system properties. Here, we introduce a novel deep learning approach for accelerated MPI calibration based on Transformers for SM super-resolution (TranSMS). Low-resolution SM measurements are performed using large MNP samples for improved signal-to-noise ratio efficiency, and the high-resolution SM is super-resolved via model-based deep learning. TranSMS leverages a vision transformer module to capture contextual relationships in low-resolution input images, a dense convolutional module for localizing high-resolution image features, and a data-consistency module to ensure measurement fidelity. Demonstrations on simulated and experimental data indicate that TranSMS significantly improves SM recovery and MPI reconstruction for up to 64-fold acceleration in two-dimensional imagingItem Open Access Vector modulator based active compensation of direct feedthrough(Infinite Science Publishing, 2020) Taşdelen, Bilal; Yağız, Ecrin; Utkur, Mustafa; Çağıl, Ahmet R.; Top, C. B.; Atalar, Ergin; Sarıtaş, Emine ÜlküIn magnetic particle imaging (MPI), simultaneous excitation and signal acquisition leads to direct feedthrough problems. While this direct-feedthrough can be mitigated up to some extent with passive compensation, this may not be sufficient given the time-variant nature of the system. Active compensation methods are proposed to overcome this challenge. In magnetic resonance imaging (MRI), we have recently proposed a promising active compensation technique that uses a vector modulator-like structure to modify a copy of the transmitted signal and use it for subtracting the direct-feedthrough in analog domain. In this work, this technique is adapted to MPI for active compensation of the direct-feedthrough. We demonstrate a significant increase in detection sensitivity at the fundamental harmonic on an in-house arbitrary waveform relaxometer.