Schweiger, M., & Arridge, S. (2016). Basis mapping methods for forward and inverse problems. International Journal for Numerical Methods in Engineering. doi:10.1002/nme.5271

Ehrhardt, M., Thielemans, K., Pizarro, L., Atkinson, D., Ourselin, S., Hutton, B., & Arridge, S. (2015). Joint reconstruction of PET-MRI by exploiting structural similarity. Inverse Problems, 31, 015001. doi:10.1088/0266-5611/31/1/015001

Smigaj, W., Arridge, S., Betcke, T., Phillips, J., & Schweiger, M. (2015). Solving Boundary Integral Problems with BEM++. ACM Transactions on Mathematical Software. doi:10.1145/2590830

Bassi, A., D'Andrea, C., Valentini, G., Cubeddu, R., & Arridge, S. (2008). Temporal propagation of spatial information in turbid media. OPTICS LETTERS, 33 (23), 2836-2838. doi:10.1364/OL.33.002836

Hänninen, N., Pulkkinen, A., Arridge, S., & Tarvainen, T. (2022). Adaptive stochastic Gauss-Newton method with optical Monte Carlo for quantitative photoacoustic tomography. Journal of Biomedical Optics, 27 (8), 083013. doi:10.1117/1.JBO.27.8.083013

Di Sciacca, G., Maffeis, G., Farina, A., Dalla Mora, A., Pifferi, A., Taroni, P., & Arridge, S. (2022). Evaluation of a pipeline for simulation, reconstruction, and classification in ultrasound-aided diffuse optical tomography of breast tumors. JOURNAL OF BIOMEDICAL OPTICS, 27 (3), ARTN 036003. doi:10.1117/1.JBO.27.3.036003

Arjas, A., Alles, E. J., Maneas, E., Arridge, S., Desjardins, A., Sillanpaa, M. J., & Hauptmann, A. (2022). Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. doi:10.1109/tuffc.2022.3162097

Jin, B., Barbano, R., Arridge, S., & Tanno, R. (2022). Uncertainty quantification in medical image synthesis. Biomedical Image Synthesis Simulation: Methods and Applications. Lavoisier.

Arridge, S. R., Ehrhardt, M. J., & Thielemans, K. (2021). (An overview of) Synergistic reconstruction for multimodality/multichannel imaging methods. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 379 (2200), 20200205. doi:10.1098/rsta.2020.0205

Stanziola, A., Arridge, S. R., Cox, B. T., & Treeby, B. E. (2021). A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound. Journal of Computational Physics, 441. doi:10.1016/j.jcp.2021.110430