Publications

Listed newest first. See also my Google Scholar profile.

2026

• Synthetic Data in MR Spectroscopy: Current Practices, Applications, and Considerations

  J. T. LaMaster, A. T. Gudmundson, A. Abaei, S. Alcicek, A. Alvarado, O. Andronesi, T. K. Bell, W. Bogner, H. Bugler, A. R. Craven, C. Cudalbu, A. Davidson, C. W. Davies-Jenkins, D. Deelchand, R. A. E. Edden, M. Esmaeili, C. C. Fleischer, A. Gad, G. Genovese, S. Gurbani, A. D. Harris, P. Henry, K. C. Igwe, A. Joy, M. Julià-Sapé, H. Kim, R. Kreis, F. Lam, K. Landheer, B. Lanz, C. Lee, C. Ligneul, J. P. Merkofer, J. J. Miller, J. Mosso, S. Motyka, E. Mougel, P. G. Mullins, S. Murali-Manohar, C. Najac, S. Nakajima, G. Oeltzschner, E. Ozturk-Isik, M. Palombo, U. Pilatus, J. Platek, E. Van Praagh, X. Qu, R. Rizzo, C. T. Rodgers, E. P. Rodriguez, Y. Rodriguez, M. K. Sammi, D. M. J. van de Sande, M. K. Sarma, F. Saviola, A. Schrantee, A. Shamaei, D. Simicic, B. J. Soher, N. Sollmann, Y. Song, J. A. Stanley, B. Strasser, A. Susnjar, K. M. Swanberg, M. A. Thomas, I. Tkáč, Z. Tu, P. J. Weiser, M. Widmaier, M. Wilson, C. J. Wu, L. Xin, H. J. Zöllner, İ. Özdemir, M. S. D. W. Group, and A. Kaiser

  arXiv preprint, arXiv:2602.23463, 2026.

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• A Digital Phantom for MR Spectroscopy Data Simulation

  D. M. J. van de Sande, A. T. Gudmundson, S. Murali-Manohar, C. W. Davies-Jenkins, D. Simicic, G. Simegn, İ. Özdemir, S. Amirrajab, J. P. Merkofer, H. J. Zöllner, G. Oeltzschner, and R. A. E. Edden

  Magnetic Resonance in Medicine, vol. 95, no. 3, pp. 1345–1359, 2026.

• Data-Driven Synthesis of Magnetic Resonance Spectroscopy Data Using a Variational Autoencoder

  D. M. J. van de Sande, J. P. Merkofer, S. Amirrajab, M. Veta, G. S. Drenthen, J. F. A. Jansen, and M. Breeuwer

  arXiv preprint, arXiv:2603.00736, 2026.

  link

2025

• Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance Spectroscopy

  J. P. Merkofer, D. M. J. van de Sande, A. A. Bhogal, and R. J. G. van Sloun

  arXiv preprint, arXiv:2505.03590, 2025.

  link

• Strategies to Minimize Out-of-Distribution Effects in Data-Driven MRS Quantification

  J. P. Merkofer, A. Kaiser, A. Schrantee, O. J. Gurney-Champion, and R. J. G. van Sloun

  arXiv preprint, arXiv:2511.23135, 2025.

  link

• WAND: Wavelet Analysis-Based Neural Decomposition of MRS Signals for Artifact Removal

  J. P. Merkofer, D. M. J. van de Sande, S. Amirrajab, K. M. Nam, R. J. G. van Sloun, and A. A. Bhogal

  NMR in Biomedicine, vol. 38, no. 6, pp. e70038, 2025.

2024

• Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time

  R. P. Berto, H. Bugler, G. Dias, M. Oliveira, L. Ueda, S. Dertkigil, P. D. P. Costa, L. Rittner, J. P. Merkofer, D. M. J. van de Sande, S. Amirrajab, G. S. Drenthen, M. Veta, J. F. A. Jansen, M. Breeuwer, R. J. G. van Sloun, A. Qayyum, C. Rodero, S. Niederer, R. Souza, and A. D. Harris

  Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 37, no. 3, pp. 449–463, 2024.

• Anomalous Change Point Detection Using Probabilistic Predictive Coding

  R. G. Hup, J. P. Merkofer, A. A. Bhogal, R. J. G. van Sloun, R. Haakma, and R. Vullings

  arXiv preprint, arXiv:2405.15727, 2024.

  link

• SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation

  D. H. Shmuel, J. P. Merkofer, G. Revach, R. J. G. van Sloun, and N. Shlezinger

  IEEE Transactions on Vehicular Technology, vol. 74, no. 3, pp. 4962–4976, 2024.

2023

• A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge

  J. P. Merkofer, D. M. J. van de Sande, S. Amirrajab, G. S. Drenthen, M. Veta, J. F. A. Jansen, M. Breeuwer, and R. J. G. van Sloun

  arXiv preprint, arXiv:2306.02984, 2023.

  link

• DA-MUSIC: Data-Driven DoA Estimation via Deep Augmented MUSIC Algorithm

  J. P. Merkofer, G. Revach, N. Shlezinger, T. Routtenberg, and R. J. G. van Sloun

  IEEE Transactions on Vehicular Technology, vol. 73, no. 2, pp. 2771–2785, 2023.

• Deep Root MUSIC Algorithm for Data-Driven DoA Estimation

  D. H. Shmuel, J. P. Merkofer, G. Revach, R. J. G. van Sloun, and N. Shlezinger

  ICASSP 2023 – 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1–5, 2023.

• A Review of Machine Learning Applications for the Proton MR Spectroscopy Workflow

  D. M. J. van de Sande, J. P. Merkofer, S. Amirrajab, M. Veta, R. J. G. van Sloun, M. J. Versluis, J. F. A. Jansen, J. S. van den Brink, and M. Breeuwer

  Magnetic Resonance in Medicine, vol. 90, no. 4, pp. 1253–1270, 2023.

2022

• Deep Augmented MUSIC Algorithm for Data-Driven DoA Estimation

  J. P. Merkofer, G. Revach, N. Shlezinger, and R. J. G. van Sloun

  ICASSP 2022 – 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3598–3602, 2022.