News

At UMRAM, our graduate students and faculty members with researchers from Aselsan published a paper titled “Statistically Segregated k-Space Sampling for Accelerating Multiple-Acquisition MRI” in IEEE Transactions on Medical Imaging on 14 January 2019. The article authored by Lütfi Kerem Şenel, Toygan Kılıç, Asst. Prof. Emine Ülkü Sarıtaş, Assoc. Prof. Tolga Çukur from UMRAM and Alper Güngör, Emre Kopanoğlu, H. Emre Güven, Aykut Koç from Aselsan Research Center.

Abstract: A central limitation of multiple-acquisition magnetic resonance imaging (MRI) is the degradation in scan efficiency as the number of distinct datasets grows. Sparse recovery techniques can alleviate this limitation via randomly undersampled acquisitions. A frequent sampling strategy is to prescribe for each acquisition a different random pattern drawn from a common sampling density. However, naive random patterns often contain gaps or clusters across the acquisition dimension that in turn can degrade reconstruction quality or reduce scan efficiency. To address this problem, a statistically-segregated sampling method is proposed for multiple-acquisition MRI. This method generates multiple patterns sequentially, while adaptively modifying the sampling density to minimize k-space overlap across patterns. As a result, it improves incoherence across acquisitions while still maintaining similar sampling density across the radial dimension of k-space. Comprehensive simulations and in vivo results are presented for phase-cycled balanced steady-state free precession and multi-echo T2-weighted imaging. Segregated sampling achieves significantly improved quality in both Fourier and compressedsensing reconstructions of multiple-acquisition datasets.

Our beloved employee Erhan Erköseoğlu has just left from UMRAM. He was working as an system engineer in UMRAM since April, 2018. We have had succesful work together. By the begin of January 2019, he had left UMRAM.
We would like to thank him for his contributions to UMRAM and we wish him all good luck on his chosen path.

Toygan Kılıç from UMRAM, has successfully defended his MSc thesis on January 21st, 2019.

He is currently enrolled in Electrical and Electronics MSc Program with his supervisor Emine Ülkü Sarıtaş and co-advisor Tolga Çukur at Bilkent University.

Thesis Title: Rapid Multi-Contrast Magnetic Resonance Imaging and Time-Of-Flight Angiography

Abstract: Magnetic resonance imaging (MRI) is a frequently used imaging modality for examining soft tissue structures. Long scanning time is the most crucial constraint that limits the use of MRI in the clinics. Partial Fourier (PF), parallel imaging (PI), and compressed sensing (CS) methods have been proposed to accelerate acquisitions by undersampling the data in k-space. However, further increase in acceleration factor as well as image quality are needed in certain applications of MRI, such as T2-weighted imaging and time-of-flight (TOF) angiography. Previous studies have adopted SPIRiT, a popular CS method, to the problem of multi-contrast image reconstruction. However, the mutual information across different contrast images were not utilized in these studies. In this thesis, a new method is proposed to benefit from the correlated structural information among the images by emphasizing high-spatial frequencies during joint reconstruction. The results obtained from in vivo brain scans and numerical phantom show that the proposed method is more robust against parameter selection when compared to conventional methods. For TOF angiography images, the goal of this thesis is to increase the signal-to-noise-ratio and shorten the scanning time, simultaneously. For this purpose, a combination of 2D acceleration in the phase-encode dimensions via CS and 1D PF data acquisition in the frequency-encode dimension to reduce echo time is proposed. Following this data acquisition, a joint reconstruction that iteratively alternates between CS and PF is introduced. In vivo angiography results in the brain show that the proposed time-efficient TOF method improves the vessel-background contrast, while decreasing the scanning time.

The new year 2019 has been celebrated in UMRAM at the party which is held with a large number of participants. We would like to extend our warmest new year wishes once more to everybody especially to the ones who has honored us by coming to UMRAM to celebrate new year with us. At the same party, we also had opportunity of toasting our glasses for the well deserved succes of Niyazi Koray Ertan who had defended his Phd thesis.

Koray Ertan from UMRAM has successfully defended his Phd thesis.
He is currently enrolled in Electrical and Electronics PhD Program with his supervisor Ergin Atalar at Bilkent University.

He will continue his post-doc studies at Stanford University in following years.

Thesis Title: Design and Applications of A Z-Gradient Array in Magnetic Resonance Imaging.

Abstract: Array of gradient coils driven by independent power amplifiers can generate gradient fields with dynamically changing gradient field profiles. Nine channel prototype z-gradient coil array with a diameter of 25 cm is designed and manufactured. Previously designed gradient power amplifiers with maximum voltage of 50 V and maximum current of 20 A are used to independently drive the coils. Mutual coupling between gradient coils are investigated to maintain high time fidelity in the gradient waveform. A first-order circuit model including the mutual couplings is provided to analytically calculate the input voltages and minimum achievable rise times for a given set of gradient array currents and amplifier limitations. Mutual impedance of the system is measured which is in a good agreement with the first order circuit model inside the operating bandwidth of the amplifiers (<10kHz). An example z-gradient profile is optimized and used in Magnetic Resonance Imaging

(MRI) phantom experiment as a readout gradient. After validating the proper functioning of the hardware with current measurements and MRI experiments, advantages of dynamically arrangeable field profiles generated by z-gradient array are investigated.

Firstly, linear gradient in variable Volume of Interests (VOIs) with variable linearity errors are optimized with four different performance parameters such as maximization of gradient strength for unit amplifier current limits, maximization of slew rate for unit amplifier voltage limits, minimization of current norm and peak vector B-field for a unit gradient strength. Decreasing the size of the gradient VOI and allowing more linearity error increases all performance parameters more than five times among the sweep ranges. The advantage of dynamic field optimization is demonstrated in Diffusion Weighted Imaging (DWI).

Maximization of gradient fields only inside the slice volume rather than entire coil volume results in 4 times higher gradient strength which decreases the diffusion encoding gradient duration 3 times and halves the echo time. Increased signal to noise ratio (SNR) of the diffusion weighted images results in better estimate for the apparent diffusion coefficient (ADC) values inside the phantom.

Secondly, gradient array is also capable of generating nonlinear gradient field distributions. In addition to many applications of nonlinear gradients in MRI, two novel applications based on nonlinear gradients are proposed. In the first application, nonlinear gradients are used to encode multiple slice locations to the same frequency.

Excitation of multiple slices is achieved with a single band radio frequency (RF) pulse in contrast to multi-band RF pulses with higher specific absorption rate (SAR) and peak power. Two different field design method is presented and both of them are analyzed in terms of slice thickness error, center location variation, gradient strength per unit norm current, power dissipation. Two and three slices are excited with a single band RF pulse in phantom experiments. In the second application, a single channel nonlinear gradient field is simultaneously used with linear gradients during spoke excitation to mitigate the B1+ inhomogeneity. Excitation k-space with increased dimension are introduced for simultaneous use of linear and nonlinear gradients by including independent k-space variables for nonlinear gradient channel.

Simulations are performed for 1D, 2D, RF power limited and RF power unlimited cases to demonstrate the enhanced B1+ homogeneity for simultaneous use of linear and nonlinear gradients compared to using only linear or only nonlinear gradients. Proposed method results in 2.3 times more decrease in the excitation inhomogeneity compared to using only linear gradients in MRI experiments.

Dr. Aaron M.Clarke passed away on November 24, 2018. He was former faculty member of UMRAM and Bilkent University, Department of Psychology, Faculty of Economics, Administration and Social Sciences (2015-2018). We wish to extend our condolences to Clarke family and his friends at Bilkent. Funeral service was held in Canada. If you would like to express your sympathies, and commit your thoughts and feelings to paper, we have opened a book of condolences at Aaron’s office in UMRAM building. The book will be kept open until 15th February 2019.

UMRAM/Aysel Sabuncu Brain Reserch Center hosted a training course in EEG data collection and analysis on December 1. More than 50 researchers from various disciplines (e.g., psychology, philosophy, engineering, medicine, education) and from different parts of Turkey attended the course. Six different lectures were delivered by UMRAM researchers Hulusi Kafalıgönül, Utku Kaya, Burcu A. Ürgen, Esra Nur Çatak, and Alaz Aydın. The event was supported by British Academy-Newton Funding.

UMRAM and Electrical and Electronics Engineering faculty member, Dr. Tolga Cukur has been promoted to Associate Professor. Dr. Tolga Çukur received his bachelor’s degree (2003) from Bilkent University Electrical and Electronics Engineering Department with rank 1. He completed his master’s (2005) and doctoral (2009) studies at Stanford University with his “Stanford Graduate Fellowship” scholarship. He carried out postdoc studies in University of California at Berkeley  (2010-2013) at the Helen Wills Neuroscience Institute. He has been working as a faculty member in the Electrical and Electronics Engineering Department of Bilkent University since 2013 and is also affiliated with  the National Magnetic Resonance Research Center (UMRAM) and Aysel Sabuncu Brain Research Center. Dr. Cukur also received  2017 IEEE Turkey Research Incentive Award, 2017 Academy of Sciences BAGEP award,  2017 Young Scientist Award from Science Heroes Association,  2015 TUBA-GEBIP award, 2015 EMBO Installation Grant, and  2013 Marie Curie Reintegration Grant. Dr. Çukur’s research focuses on innovative biomedical imaging, machine and deep learning techniques in biology and medicine.

One day course will be held in 1 December 2018 at UMRAM with collobration of Hulusi Kafalıgönül, Bilkent University and Andrea Pavan, University of Lincoln and it will be supported by British Academy via Newton Fund. Postdocs, graduates, and senior under graduate students can apply. Other requirements are listed on the visual.

At October 6, 2018, as UMRAM, we organized a Sports Day and had an enjoyable day! During all day, with the participation of UMRAM people, volleyball tournament was held, and the team which came the first in the tournament got their awards. Moreover, the entartainment continued with other games and film screenings. We had chance to have conversation and fun.

On January 3, 2018, fire extinguishing training and drill were held at UMRAM. In the training given by Bilkent University Civil Defence and Security Office, UMRAM employees and students were told what to do in case of emergency. A fire drill was then carried out in order to show how to respond to fire.   Bilkent Emergency phone: +90 312 290 66 66