National Magnetic Resonance Research Center (UMRAM)

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Open Access
2D RF pulse design for optimized reduced field-of-view imaging at 1.5T and 3T
(Elsevier Inc., 2021-10-22) Eren, Orhun Caner; Barlas, Bahadır Alp; Sarıtaş, Emine Ülkü
Two-dimensional spatially selective radiofrequency (2DRF) excitation pulses are widely used for reduced field-of-view (FOV) targeted high-resolution diffusion weighted imaging (DWI), especially for anatomically small regions such as the spinal cord and prostate. The reduction in FOV achieved by 2DRF pulses significantly improve the in-plane off-resonance artifacts in single-shot echo planar imaging (ss-EPI). However, long durations of 2DRF pulses create a sensitivity to through-plane off-resonance effects, especially at 3 T where the off-resonance field doubles with respect to 1.5 T. This work proposes a parameter-based optimization approach to design 2DRF pulses with blips along the slice-select axis, with the goal of maximizing slab sharpness while minimizing off-resonance effects on 1.5 T and 3 T MRI scanners, separately. Extensive Bloch simulations are performed to evaluate the off-resonance robustness of 2DRF pulses. Three different metrics are proposed to quantify the similarity between the actual and ideal 2D excitation profiles, based on the signals within and outside the targeted reduced-FOV region. In addition, simulations on a digital brain phantom are performed for visual comparison purposes. The results show that maintaining a sharp profile is the primary design requirement at 1.5 T, necessitating the usage of relatively high slab sharpness with a time-bandwidth product (TBW) around 8–10. In contrast, off-resonance robustness is the primary design requirement at 3 T, requiring the usage of a moderate slap sharpness with TBW around 5–7.
Open Access
3 boyutlu kartezyen olmayan paralel görüntülemede değişken görüntü alanına dayalı geriçatım
(IEEE, 2018) Şenel, Celal Furkan; Çukur, Tolga
MRG’de yaygın olarak kullanılan geriçatım yöntemleri değişken yoğunluklu Kartezyen olmayan taramalara da uygulanabilmektedir; fakat bu durumda bu yöntemlerin genellikle yüksek hesaplama karmaşıklığı içeren çok sayıda yinelemeye ihtiyaç duyması özellikle 3 boyutlu geriçatımlara uygulanabilirliklerini sınırlamaktadır. 2 boyutlu Kartezyen olmayan veri için daha hızlı geriçatım almak amacıyla, PILS’e dayalı, değişken görüntü alanlarını kullanan bir teknik yakın zamanda teklif edilmiştir. Bu çalışmada bu teknik 3 boyutlu değişken yoğunluklu veriye uygulanmış, ek olarak elde edilen görüntüler dalgacık regülarizasyonu kullanılarak kalan artifaktlardan temizlenmiştir. Önce regülarizasyon için farklı parametrelerin başarımları karşılaştırılmış, sonra regülarizasyon da dâhil olmak üzere değişken görüntü alanı yönteminin, karelerin toplanması, PILS ve ESPIRiT geriçatımları ile başarımları karşılaştırılmıştır. Elde edilen sonuçlar teklif edilen yöntemin başarısının karşılaştırılan diğer geriçatımlardan üstün olduğunu göstermektedir.
Open Access
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.
Open Access
A 60 GHz beam-steering reconfigurable antenna
(IEEE, 2016) Khalat, A.; Towfiq, Md. A.; Cetiner, B. A.; Ceylan, Ö.; Bıyıklı, Necmi
We present the design, microfabrication, and characterization of a multifunctional reconfigurable antenna (MRA) with beam steering capability operating at 60 GHz band (59-66 GHz). The MRA provides 3 different beam directions pertaining to: θ {-30°,0°,30°}; φ = 90° based on reconfigurable parasitic layer approach. The structure consists of three layers namely, feed, driven antenna and reconfigurable parasitic layers. The first two layers use RF and microfabrication process compatible quartz (ϵr = 3.9, tanδ = 0.0002) substrate while parasitic layer is formed on a low-cost pyrex (ϵr = 4.9, tanδ = 0.01) material with air cavities formed underneath. The upper surface of pyrex has 3×3 rectangular shaped metallic pixels, four of which are interconnected by means of switching. By judiciously controlling the switch status the beam-steering is accomplished. The simulated impedance and gain characteristics show ∼ 15% bandwidth over which the maximum realized gain remains relatively flat around ∼ 7.2 dB for all modes of operation. © 2016 IEEE.
Open Access
A deep equilibrium technique for 3D MPI reconstruction
(Infinite Science Publishing, 2024-03-10) Güngör, Alper; Sarıtaş, Emine Ülkü; Çukur, Tolga
Image reconstruction in MPI involves estimation of the particle concentration given acquired data and system matrix (SM). As this is an ill-posed inverse problem, image quality depends heavily on the prior information used to improve problem conditioning. Recent learning-based priors show great promise for MPI reconstruction, but priors purely driven by image samples in training datasets can show limited reliability and generalization. Here, we propose 3DEQ-MPI, a new deep equilibrium technique for 3D MPI reconstruction. 3DEQ-MPI is based on an infinitely-unrolled network architecture that synergistically leverages a data-driven prior to learn attributes of MPI images and a physics-driven prior to enforce fidelity to acquired data based on the SM. 3DEQ-MPI is trained on a simulated dataset, and unlike common deep equilibrium models, it utilizes a Jacobian-free backpropagation algorithm for fast and stable convergence. Demonstrations on simulated data and experimental OpenMPI data clearly show the superior performance of 3DEQ-MPI against competing methods. © 2024 Güngör et al.; licensee Infinite Science Publishing GmbH.
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, Tolga
Image 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.
Open Access
A dictionary-based algorithm for MNP signal prediction at unmeasured drive field frequencies
(Infinite Science Publishing, 2023-03-19) Alpman, Aslı; Utkur, Mustafa; Sarıtaş, Emine Ülkü
The signal in MPI depends on magnetic nanoparticle (MNP) parameters and environmental conditions, as wellas drive field (DF) settings and measurement system response. In this study, we propose a dictionary-basedalgorithm using a coupled Brown-Néel rotation model to simultaneously estimate the MNP parameters togetherwith system transfer function. We then propose an empirical method that enables signal prediction at unmeasuredDF frequencies, where measurement data is not available.
Open Access
A diffusion-based reconstruction technique for single pixel camera
(IEEE - Institute of Electrical and Electronics Engineers, 2023-08-28) Güven, Baturalp; Güngör, A.; Bahçeci, M. U.; Çukur, Tolga
Single-pixel imaging enables high-resolution imaging through multiple coded measurements based on lowresolution snapshots. To reconstruct a high-resolution image from these coded measurements, an ill-posed inverse problem is solved. Despite the recent popularity of deep learning-based methods for single-pixel imaging reconstruction, they are insufficient in preserving spatial details and achieving a stable reconstruction. Diffusion-based methods, which have gained attention in recent years, provide a solution to this problem. In this study, to the best of our knowledge, the single-pixel image reconstruction is performed for the first time using a denoising diffusion probabilistic model. The proposed method reconstructs the image by conditioning it towards the least squares solution while preserving data consistency after unconditional training of the model. The proposed method is compared against existing singlepixel imaging methods, and ablation studies are conducted to demonstrate the individual model components. The proposed method outperforms competing methods in both quantitative measurements and visual quality.
Open Access
A large video set of natural human actions for visual and cognitive neuroscience studies and its validation with fMRI
(MDPI, 2022-12-29) Ürgen, Burcu Ayşen; Nizamoğlu, Hilal; Eroğlu, Aslı; Orban, G. A.
The investigation of the perception of others’ actions and underlying neural mechanisms has been hampered by the lack of a comprehensive stimulus set covering the human behavioral repertoire. To fill this void, we present a video set showing 100 human actions recorded in natural settings, covering the human repertoire except for emotion-driven (e.g., sexual) actions and those involving implements (e.g., tools). We validated the set using fMRI and showed that observation of the 100 actions activated the well-established action observation network. We also quantified the videos’ low-level visual features (luminance, optic flow, and edges). Thus, this comprehensive video set is a valuable resource for perceptual and neuronal studies.
Open Access
A naturalistic laboratory setup for real-world HRI studies
(Association for Computing Machinery, 2024-03-11) Pekçetin, T.N.; Evsen, Şeyda; Pekçetin, S.; Karaduman, Tuvana Dilan; Acarturk, C.; Ürgen, Burcu Ayşen
We present our novel naturalistic laboratory setup that facilitates the presentation of real-world live-action stimuli by physically present actors in a controlled manner. Participants observe liveaction stimuli through a screen, which is surrounded by curtains, akin to a theatre experience, and promptly evaluate them when the screen turns to its opaque mode. Additionally, we introduce key components of the setup, including curtains, an actor PC, a security camera, and a bell, and the insights we gained during the task development. This innovative setup holds promise for advancing real-world investigations in Human-Robot Interaction.
Open Access
A plug-in graph neural network to boost temporal sensitivity in fMRI analysis
(IEEE, 2024-09) Şıvgın, Irmak; Bedel, Hasan Atakan; Ozturk, Saban; Çukur, Tolga
Learning-based methods offer performance leaps over traditional methods in classification analysis of high-dimensional functional MRI (fMRI) data. In this domain, deep-learning models that analyze functional connectivity (FC) features among brain regions have been particularly promising. However, many existing models receive as input temporally static FC features that summarize inter-regional interactions across an entire scan, reducing the temporal sensitivity of classifiers by limiting their ability to leverage information on dynamic FC features of brain activity. To improve the performance of baseline classification models without compromising efficiency, here we propose a novel plug-in based on a graph neural network, GraphCorr, to provide enhanced input features to baseline models. The proposed plug-in computes a set of latent FC features with enhanced temporal information while maintaining comparable dimensionality to static features. Taking brain regions as nodes and blood-oxygen-level-dependent (BOLD) signals as node inputs, GraphCorr leverages a node embedder module based on a transformer encoder to capture dynamic latent representations of BOLD signals. GraphCorr also leverages a lag filter module to account for delayed interactions across nodes by learning correlational features of windowed BOLD signals across time delays. These two feature groups are then fused via a message passing algorithm executed on the formulated graph. Comprehensive demonstrations on three public datasets indicate improved classification performance for several state-of-the-art graph and convolutional baseline models when they are augmented with GraphCorr.
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 Ülkü
Magnetic 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.
Open Access
A transformer-based prior legal case retrieval method
(IEEE - Institute of Electrical and Electronics Engineers, 2023-08-28) Öztürk, Ceyhun Emre; Özçelik, Şemsi Barış; Koç, Aykut
In this work, BERTurk-Legal, a transformer-based language model, is introduced to retrieve prior legal cases. BERTurk-Legal is pre-trained on a dataset from the Turkish legal domain. This dataset does not contain any labels related to the prior court case retrieval task. Masked language modeling is used to train BERTurk-Legal in a self-supervised manner. With zero-shot classification, BERTurk-Legal provides state-of-the-art results on the dataset consisting of legal cases of the Court of Cassation of Turkey. The results of the experiments show the necessity of developing language models specific to the Turkish law domain.
Open Access
Abnormal subcortical activity in congenital mirror movement disorder with RAD51 mutation
(Turkish Society of Radiology, 2018) Demirayak, Pınar; Onat, Onur Emre; Gevrekci, A. Ö.; Gülsüner, S.; Uysal, H.; Bilgen, R.; Doerschner, Katja; Özçelik, Tayfun; Boyacı, Hüseyin
PURPOSE Congenital mirror movement disorder (CMMD) is characterized by unintended, nonsuppressible, homologous mirroring activity contralateral to the movement on the intended side of the body. In healthy controls, unilateral movements are accompanied with predominantly contralateral cortical activity, whereas in CMMD, in line with the abnormal behavior, bilateral cortical activity is observed for unilateral motor tasks. However, task-related activities in subcortical structures, which are known to play critical roles in motor actions, have not been investigated in CMMD previously. METHODS We investigated the functional activation patterns of the motor components in CMMD patients. By using linkage analysis and exome sequencing, common mutations were revealed in seven affected individuals from the same family. Next, using functional magnetic resonance imaging (fMRI) we investigated cortical and subcortical activity during manual motor actions in two right-handed affected brothers and sex, age, education, and socioeconomically matched healthy individuals. RESULTS Genetic analyses revealed heterozygous RAD51 c.401C>T mutation which cosegregated with the phenotype in two affected members of the family. Consistent with previous literature, our fMRI results on these two affected individuals showed that mirror movements were closely related to abnormal cortical activity in M1 and SMA during unimanual movements. Furthermore, we have found previously unknown abnormal task-related activity in subcortical structures. Specifically, we have found increased and bilateral activity during unimanual movements in thalamus, striatum, and globus pallidus in CMMD patients. CONCLUSION These findings reveal further neural correlates of CMMD, and may guide our understanding of the critical roles of subcortical structures for unimanual movements in healthy individuals.
Open Access
Accelerating the co-simulation method for the design of transmit array coils for MRI
(Springer, 2020) Sadeghi‑Tarakameh, Alireza; Kazemivalipour, Ehsan; Gündoğdu, Umut; Erdoğan, Serhat; Atalar, Ergin
Objective: Accelerating the co-simulation method for the design of transmit array (TxArray) coils is studied using equivalent circuit models. Materials and methods: Although the co-simulation method dramatically reduces the complexity of the design of TxArray coils, finding the optimum solution is not trivial since there exist many local minima in the optimization problem. We propose to utilize an equivalent circuit model of the TxArray coil to obtain a proper initial guess for the optimization process of the co-simulation method. To prove the concept, six different TxArray coils (i.e., three degenerate birdcage coils (DBC), two dual-row head coils, and one elliptical body TxArray coil) with two different loading strategies (cylindrical phantom and human head/body model) at 3 T field strength are investigated theoretically; as an example study, an eight-channel head-DBC is constructed using the obtained values. Results: This approach accelerates the design process more than 20-fold for the coils that are investigated in this manuscript. Conclusion: A fast and accurate method for tuning and decoupling of a TxArray coil can be achieved using its equivalent circuit model combined with the co-simulation method.
Open Access
Adaptive diffusion priors for accelerated MRI reconstruction
(Elsevier B.V., 2023-07-20) Güngör, Alper; Dar, Salman Ul Hassan; Öztürk, Şaban; Korkmaz, Yılmaz; Bedel, Hasan Atakan; Elmas, Gökberk; Özbey, Muzaffer; Çukur, Tolga
Deep MRI reconstruction is commonly performed with conditional models that de-alias undersampled acquisitions to recover images consistent with fully-sampled data. Since conditional models are trained with knowledge of the imaging operator, they can show poor generalization across variable operators. Unconditional models instead learn generative image priors decoupled from the operator to improve reliability against domain shifts related to the imaging operator. Recent diffusion models are particularly promising given their high sample fidelity. Nevertheless, inference with a static image prior can perform suboptimally. Here we propose the first adaptive diffusion prior for MRI reconstruction, AdaDiff, to improve performance and reliability against domain shifts. AdaDiff leverages an efficient diffusion prior trained via adversarial mapping over large reverse diffusion steps. A two-phase reconstruction is executed following training: a rapid-diffusion phase that produces an initial reconstruction with the trained prior, and an adaptation phase that further refines the result by updating the prior to minimize data-consistency loss. Demonstrations on multi-contrast brain MRI clearly indicate that AdaDiff outperforms competing conditional and unconditional methods under domain shifts, and achieves superior or on par within-domain performance. © 2023 Elsevier B.V.
Open Access
Adaptive reconstruction for vessel preservation in unenhanced MR angiography
(IEEE, 2016) Ilıcak, Efe; Çetin, S.; Sarıtaş, Emine Ülkü; Ünal, G.; Çukur, Tolga
The image quality of unenhanced magnetic resonance angiography, which images blood vessels without contrast agents, is limited by constraints related to scan time. To address this problem, techniques that undersample angiographic data and then apply regularized reconstructions are used. Conventional reconstructions employ regularization terms with uniform spatial weighting. Thus, they can yield improper suppression of aliasing artifacts and poor blood/background contrast. In this study, a reconstruction strategy is evaluated that applies spatially-adaptive regularization based on vessel maps obtained via a tractographic segmentation. This strategy is compared with conventional methods in terms of peak signal to noise ratio, structural similarity and contrast.
Open Access
Analysis and mitigation of noise in simultaneous transmission and reception in MRI
(John Wiley & Sons, Inc., 2021-03-05) Taşdelen, Bilal; Sadeghi-Tarakameh, Alireza; Yılmaz, Uğur; Atalar, Ergin
Purpose In simultaneous transmission and reception (STAR) MRI, along with the coupling of the excitation pulse to the received signal, noise, and undesired distortions (spurs) coming from the transmit chain also leak into the acquired signal and degrade image quality. Here, properties of this coupled noise and its relationship with the transmit amplifier gain, transmit chain noise density, isolation performance, and imaging bandwidth are analyzed. It is demonstrated that by utilizing a recently proposed STAR technique, the transmit noise can be reduced. The importance of achieving high isolation and careful selection of the corresponding parameters are demonstrated. Theory and Methods A cancellation algorithm, together with a vector modulator, is used for transmit-receive isolation. The scanner is modeled as a pipeline of blocks to demonstrate the noise contribution from each block. With higher isolation, coupled transmit noise can be reduced to the point that the dominant noise source becomes acquisition noise, as in the case for pulsed MRI. Amplifiers with different gain and noise properties are used in the experiments to verify the derived noise-transmit parameter relation. Results With the proposed technique, more than 80 dB isolation in the analog domain is achieved. The leakage noise and the spurs coupled from the transmit chain, are reduced. It is shown that the transmit gain plays the most critical role in determining sufficient isolation, whereas the amplifier noise figure does not contribute as much. Conclusion The transmit noise and the spurs in STAR imaging are analyzed and mitigated by using a vector modulator.
Open Access
Analysis of B1 mapping by Bloch Siegert shift
(ISMRM, 2012-05) Abacı-Türk, Esra; İder, Yusuf Ziya; Atalar, Ergin
The Bloch-Siegert shift is a new phase-based B1 mapping method [1]. This method utilizes the fact that for a large off-resonance frequency, square of the B1 field magnitude is proportional to the phase. In this study, relation between the off-resonance frequency, the RF pulse shape, and the duration of the RF pulse is investigated. Moreover, importance of the crusher usage in the sequence is examined for the Fermi and hard pulse shapes. Understanding of these parameters can be helpful for the general use of this method and may give an intuition for appropriate RF pulse design.
Open Access
Analysis of B1 mapping by Bloch Siegert Shift
(ISMRM, 2012) Türk, Esra Abacı; İder, Yusuf Ziya; Atalar, Ergin
In this study, B1 mapping by the Bloch-Siegert shift is analyzed with simulations and experiments. The importance of the pulse duration and the crusher gradients are investigated. It is shown that the off-resonance pulse duration is necessary for an accurate B1 mapping and also crusher gradients have to be used in order to remove the echo originating from tilting off-slice spins by the off-resonance pulse.