Conference Proceedings

2024

54) Y. U. Alcalar and M. Akçakaya, “Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problems,” European Conference on Computer Vision (ECCV), Milano, Italy, October 2024.

53) M. Saberi, P. Jenkins, M. Garwood and M. Akçakaya, “Physics-Driven Deep Learning Reconstruction of Frequency-Modulated Rabi-Encoded Echoes for Faster Accessible MRI,” Proc. 46th IEEE Engineering in Medicine and Biology Conference (EMBC), Orlando, FL, July 2024.

52) M. Gulle and M. Akçakaya, “Robust Outer Volume Subtraction with Deep Learning Ghosting Detection for Highly-Accelerated Real-Time Dynamic MRI,” IEEE International Symposium on Biomedical Imaging (ISBI), May 2024.

51) Y. U. Alcalar, M. Gulle and M. Akçakaya, “A Convex Compressibility-Inspired Unsupervised Loss Function for Physics-Driven Deep Learning Reconstruction,” IEEE International Symposium on Biomedical Imaging (ISBI), May 2024.

50) C. Zhang, O. B. Demirel and M. Akçakaya, “Cycle-consistent self-supervised learning for improved highly-accelerated MRI reconstruction,” IEEE International Symposium on Biomedical Imaging (ISBI), May 2024.

49) T. Kilic, J. Herrler, P. Liebig, O. B. Demirel, A. Nagel, M. Hong, G. B. Giannakis, K. Ugurbil and M. Akçakaya, “Towards Fast Hard-Constrained Parallel Transmit Design in Ultrahigh field MRI with Physics-Driven Neural Networks”, IEEE International Symposium on Biomedical Imaging (ISBI), May 2024.

48) H. Gu, C. Zhang, Z. Yu, C. Rettenmeier, V. A. Stenger and M. Akçakaya, “Non-Cartesian Self-Supervised Physics-Driven Deep Learning Reconstruction for Highly-Accelerated Multi-Echo Spiral fMRI,” IEEE International Symposium on Biomedical Imaging (ISBI), May 2024.

47) C. Zhang and M. Akçakaya, “Uncertainty-Guided Physics-Driven Deep Learning Reconstruction via Cyclic Measurement Consistency,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), April 2024.

2023

46) M. Gulle, O. B. Demirel, L. Dowdle, S. Moeller, E. Yacoub, K. Ugurbil and M. Akçakaya, “Highly-Accelerated High-Resolution Multi-Echo fMRI Using Self-Supervised Physics-Driven Deep Learning Reconstruction,” IEEE Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Dec. 2023.                  
Best Paper Finalist

45) O. B. Demirel, C. Zhang, B. Yaman, M. Gulle, C. Shenoy, T. Leiner, P. Kellman and M. Akçakaya, “High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI,” Proc. 45th IEEE Engineering in Medicine and Biology Conference, Sydney, Australia, July 2023.

44) O. B. Demirel, S. Moeller, L. Vizioli, B. Yaman, L. Dowdle, E. Yacoub, K. Uğurbil and M. Akçakaya, “High-Quality 0.5mm Isotropic fMRI: Random Matrix Theory Meets Physics-Driven Deep Learning,”  Proc. 11th International IEEE EMBS Conference on Neural Engineering, April 2023.

2022

43) J. Jia, M. Hong, Y. Zhang, M. Akçakaya and S. Liu, “On the Robustness of deep learning-based MRI Reconstruction to image transformations,” NeurIPS Workshop on Trustworthy and Socially Responsible Machine Learning, Dec. 2022.

42) H. Gu, B. Yaman, S. Moeller, I. Y. Chun and M. Akçakaya, “Accelerated MRI with Deep Linear Convolutional Transform Learning,”  IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), November 2022.

41) O. B. Demirel, B. Yaman, S. Moeller, S. Weingärtner and M. Akçakaya, “Signal-Intensity Informed Multi-Coil MRI Encoding Operator for Improved Physics-Guided Deep Learning Reconstruction of Dynamic Contrast-Enhanced MRI,” Proc. 44th IEEE Engineering in Medicine and Biology Conference, Glasgow, Scotland, UK, July 2022.

40) J Tourais, O. B. Demirel, Q. Tao, I. Pierce, G. D. Thornton, T. A. Treibel, M. Akçakaya and S. Weingärtner, “Myocardial Approximate Spin-lock Dispersion Mapping using a Simultaneous  T2 and TRAFF2  Mapping at 3T MRI, ” Proc. 44th IEEE Engineering in Medicine and Biology Conference, Glasgow, Scotland, UK, July 2022.

39) C. Coletti, J. Tourais, T. Ploem, C. van de Steeg-Henzen, M. Akçakaya and S. Weingärtner, “Adiabatic spin-lock preparations enable robust in vivo cardiac T1rho-mapping at 3T,” Proc. 44th IEEE Engineering in Medicine and Biology Conference, Glasgow, Scotland, UK, July 2022. 

38) B. Yaman, S. A. H. Hosseini and M. Akçakaya, “Zero-Shot Self-Supervised Learning for MRI Reconstruction,” International Conference on Learning Representations (ICLR), Apr. 2022.

37) C. Zhang, D. Piccini, O. B. Demirel, G. Bonanno, B. Yaman, M. Stuber, S. Moeller and M. Akçakaya, "Distributed Memory-Efficient Physics-Guided Deep Learning Reconstruction for Large-Scaled 3D Non-Cartesian MRI," Proc. 18th IEEE International Symposium on Biomedical Imaging (ISBI), Kolkata, West Bengal, India, March 2022.
 

2021

36) C. Zhang, J. Jia, B. Yaman, S. Moeller, S. Liu, M. Hong and M. Akçakaya, "Instabilities of Conventional Multi-Coil MRI Reconstruction To Small Adversarial Perturbations," Proc. 55th IEEE Asilomar, Pacific Grove, CA, USA, November 2021. 

35) O. B. Demirel, B. Yaman, L. Dowdle, S. Moeller, L. Vizioli, E. Yacoub, J. Strupp, C. Olman, K. Uğurbil and M. Akçakaya, “Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning,” Proc. 55th IEEE Asilomar, Pacific Grove, California, USA, November 2021.

34) Z. Deng, B. Yaman, C. Zhang, S. Moeller and M. Akçakaya, “Efficient training of 3D unrolled neural networks for MRI reconstruction using small databases,” Proc. 55th IEEE Asilomar, Pacific Grove, California, USA, November 2021.

33) O. B. Demirel, B. Yaman, L. Dowdle, S. Moeller, L. Vizioli, E. Yacoub, J. Strupp, C. Olman, K. Uğurbil and M. Akçakaya, “20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction,” Proc. 43rd IEEE Engineering in Medicine and Biology Conference (EMBC), November 2021.

32) H. Gu, B. Yaman, K. Ugurbil, S. Moeller and M. Akçakaya, "Compressed Sensing MRI with ℓ1-Wavelet Reconstruction Revisited Using Modern Data Science Tools," Proc. 43rd IEEE Engineering in Medicine and Biology Conference (EMBC), November 2021.

31) J. Boon, T. Ploem, C. S. Simpson, I. Hermann, M. Akçakaya, E. H. Oei, A. A. Zadpoor, N. Tumer, T. M. Piscaer, J. Tourais and S. Weingartner,  “Magnetic Resonance Imaging compatible Elastic Loading Mechanism (MELM): A minimal footprint device for MR imaging under load,” Proc. 43rd IEEE Engineering in Medicine and Biology Conference (EMBC), November 2021.

30) B. Yaman, S.A.H. Hosseini, S. Moeller, and M. Akçakaya, “Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, June 2021.

29) B. Yaman, C. Shenoy, Z. Deng, H. El-Rewaidy, R. Nezafat and M. Akçakaya,  "Self-Supervised Physics-Guided Deep Learning Reconstruction For High-Resolution 3D LGE CMR," IEEE International Symposium on Biomedical Imaging (ISBI), Nice, April 2021.

28) B. Yaman, S.A.H. Hosseini, S. Moeller, J. Ellermann, K. Uğurbil and M. Akçakaya, "Ground-Truth Free Multi-Mask Self-Supervised Physics-Guided Deep Learning in Highly Accelerated MRI," IEEE International Symposium on Biomedical Imaging (ISBI), Nice, April 2021.

2020

27) S. A. Hosseini, B. Yaman, S. Moeller and M. Akçakaya, “High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks,” IEEE Engineering in Medicine and Biology Conference (EMBC), Montreal, Canada, July 2020.

26) P. J. Bolan, F. Branzoli, A. L. Di Stefano, L. Nichelli, R. Valabregue, S. Saunders, M. Akçakaya, M. Sanson, S. Lehéricy, and M. Marjańska, “Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer,” International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lima, Peru, Oct. 2020.

25) B. Yaman, S. A. Hosseini, S. Moeller, J. Ellermann, K. Uğurbil and M. Akçakaya, “Self-Supervised Physics-Based Deep Learning MRI Reconstruction without Fully-Sampled Data,” IEEE International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, April 2020.                  
Best Paper Award

24) O. B. Demirel, S. Weingärtner, S. Moeller and M. Akçakaya, “Improved Simultaneous Multi-slice Imaging for Perfusion Cardiac MRI Using Outer Volume Suppression and Regularized Reconstruction,” IEEE International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, April 2020.

23) S. A. Hosseini, B. Yaman, C. Zhang, K. Uğurbil, S. Moeller and M. Akçakaya, “Scan-Specific Accelerated MRI Reconstruction in a Regularized Self-Consistent Framework Using Recurrent Neural Networks,” IEEE International Symposium on Biomedical Imaging (ISBI) Workshop on Deep Learning for Biomedical Image Reconstruction, Iowa City, IA, April 2020.

2019

22) C. Zhang, S. A. H. Hosseini, S. Moeller, S. Weingärtner, K. Uğurbil and M. Akçakaya. “Scan-Specific Residual Convolutional Neural Networks for Fast MRI Using Residual RAKI,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2019.

21) B. Yaman, S. A. H. Hosseini, S. Moeller and M. Akçakaya. “Comparison of Neural Network Architectures for Physics-Driven Deep Learning MRI Reconstruction,” IEEE Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, Canada, October 2019.  

20) O. B. Demirel, S. Weingärtner, S. Moeller and M. Akçakaya, “Improved Regularized Reconstruction for Simultaneous Multi-Slice Cardiac MRI T1 Mapping,” European Signal Processing Conference (EUSIPCO), A Coruña, Spain, September 2019.

19) S. A. Hosseini, C. Zhang, K. Uğurbil, S. Moeller and M. Akçakaya, “sRAKI-RNN: Accelerated MRI with Scan-Specific Recurrent Neural Networks using Densely Connected Blocks,” SPIE Wavelets and Sparsity XVIII, San Diego, CA, August 2019.

18) S. Weingärtner, O. B. Demirel, C. Shenoy, F. Wenson, L. R. Schad, J. Schulz-Menger and M. Akçakaya, “Functional LGE Imaging: Cardiac Phase-Resolved Assessment of Focal Fibrosis,” IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, July 2019.

17) S. Weingärtner, X. Chen, M. Akçakaya and T. Moore, “Robust Online Spike Recovery for High-Density Electrode Recordings using Convolutional Compressed Sensing,” IEEE Conference on Neural Engineering (NER), San Francisco, CA, May 2019.  
Best Paper Finalist

16) C. I. Kanatsoulis, N. D. Sidiropoulos, M. Akçakaya and X. Fu, “Regular sampling of tensor signals: Theory and application to fMRI,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019.

15) S. A. Hosseini, S. Moeller, S. Weingärtner, K. Uğurbil and M. Akçakaya, “Accelerated Coronary MRI Using 3D SPIRiT-RAKI with Sparsity Regularization,” IEEE International Symposium on Biomedical Imaging (ISBI), Venice, Italy, April 2019.

2018

14) C. Zhang, S. Moeller, S. Weingärtner, K. Uğurbil and M. Akçakaya, “Accelerated Simultaneous Multi-Slice MRI using Subject-Specific Convolutional Neural Networks,” Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, October 2018.

13) M. Akçakaya, S. Moeller, S. Weingärtner and K. Uğurbil, “Subject-Specific Convolutional Neural Networks for Accelerated Magnetic Resonance Imaging,” IEEE International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, July, 2018.

12) C. Zhang, S. Weingärtner, S. Moeller, K. Uğurbil and M. Akçakaya, “Fast GPU Implementation of a Scan-Specific Deep Learning Reconstruction for Accelerated Magnetic Resonance Imaging,” IEEE International Conference on Electro Information Technology, May 2018.

11) L. Zhang, G. V. Karanikolas, M. Akçakaya, and G. B. Giannakis, “Fully Automatic Segmentation of the Right Ventricle Via Multi-Task Deep Neural Networks,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018.

2017

10) B. Yaman, S. Weingärtner, N. Kargas, N. Sidiropoulos and M. Akçakaya, “Locally Low-Rank Tensor Regularization for High-Resolution Quantitative Dynamic MRI,” IEEE Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Dec. 2017.

9) S. Moeller, S. Weingärtner and M. Akçakaya, “Multi-Scale Locally Low-Rank Noise Reduction for High-Resolution Dynamic Quantitative Cardiac MRI,” IEEE Engineering in Medicine and Biology Conference (EMBC), Jeju Island, Korea, July 2017.

8) G. Wang, L. Zhang, G. B. Giannakis, J. Chen and M. Akçakaya, “SPARTA: Sparse Phase Retrieval via Truncated Amplitude Flow,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), New Orleans, LA, March 2017.

2015 and earlier

7) M. Akçakaya, T. A. Basha, S. Weingärtner and R. Nezafat, “Joint Image Reconstruction and Motion Parameter Estimation for Free-Breathing Navigator-Gated Cardiac MRI,” SPIE International Symposium on Optical Science and Technology, Wavelets and Sparsity XV, August 2013 (invited).

6) M. Akçakaya and V. Tarokh, “Distortion-Based Achievability Conditions for Joint Estimation of Sparse Signals and Measurement Parameters from Undersampled Acquisitions,” IEEE International Symposium on Information Theory (ISIT), Istanbul, Turkey, July 2013.

5) M. Akçakaya, J. Park and V. Tarokh, “Low Density Frames for Compressive Sensing,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Dallas, TX, March 2010.

4) M. Akçakaya and V. Tarokh, “Limits on Noisy Compressive Sampling in Linear and Sublinear Regimes,” Conference on Information Sciences and Systems (CISS), Princeton, NJ, March 2008 (invited).

3) M. Akçakaya and V. Tarokh, “On Sparsity, Redundancy and Quality of Frame Representations,” IEEE International Symposium on Information Theory (ISIT), Nice, France, June 2007.

2) M. Akçakaya and V. Tarokh, "Performance Study of Various Sparse Representation Methods Using Redundant Frames,” Conference on Information Sciences and Systems (CISS), Baltimore, MD, March 2007.

1) N. Mysore, M. Akçakaya, J. Bajcsy and H. Kobayashi, “A New Performance Evaluation Technique for Iteratively Decoded Magnetic Recording Systems,” IEEE International Magnetics Conference, Nagoya, Japan, April 2005.