Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Browse by All Cardiff Authors

[up] Up a level
Number of items: 20.

Smith, Rhodri Lyn, Bartley, Lee, O’Callaghan, Christopher, Haberska, Luiza and Marshall, Chris ORCID: https://orcid.org/0000-0002-2228-883X 2024. NEMA NU 2-2018 evaluation and image quality optimization of a new generation digital 32-cm axial field-of-view Omni Legend PET-CT using a genetic evolutionary algorithm. Biomedical Physics & Engineering Express 10 (2) , 025032. 10.1088/2057-1976/ad286c
file

Alsyed, Emad, Smith, Rhodri, Bartley, Lee, Marshall, Christopher ORCID: https://orcid.org/0000-0002-2228-883X and Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813 2023. A heterogeneous phantom study for investigating the stability of PET images radiomic features with varying reconstruction settings. Frontiers in Nuclear Medicine 3 10.3389/fnume.2023.1078536
file

Alsyed, Emad, Smith, Rhodri, Paisey, Stephen ORCID: https://orcid.org/0000-0002-2274-3708, Marshall, Christopher ORCID: https://orcid.org/0000-0002-2228-883X and Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813 2021. A self organizing map for exploratory analysis of PET radiomic features. Presented at: 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Boston, MA, USA, 31 October -7 November 2020. 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 10.1109/NSS/MIC42677.2020.9507846
file

Smith, Rhodri L., Chandler, Hannah, Alsyed, Emad, Bartley, Lee, Fielding, Patrick and Marshall, Chris ORCID: https://orcid.org/0000-0002-2228-883X 2021. Deep learning PET epilepsy detection with a novel symmetric loss convolutional autoencoder. Presented at: 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Boston, MA, USA, 31 October -7 November 2020. 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, pp. 1-3. 10.1109/NSS/MIC42677.2020.9507980

Alsyed, Emad, Smith, Rhodri, Marshall, Christopher ORCID: https://orcid.org/0000-0002-2228-883X, Paisey, Stephen ORCID: https://orcid.org/0000-0002-2274-3708 and Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813 2019. The statistical influence of imaging time and segmentation volume on PET radiomic features: A preclinical study. Presented at: 2019 IEEE NSS-MIC, 26 October - 2 November 2019. 2019 IEEE NSS-MIC. IEEE,
file

Smith, Rhodri, Dasari, P., Lindsay, C., King, M. and Wells, K. 2019. Dense motion propagation from sparse samples. Physics in Medicine and Biology 64 (20) , 205023. 10.1088/1361-6560/ab41a0

Ackerley, Ian, Smith, Rhodri L., Scuffham, James W., Halling-Brown, Mark D., Lewis, Emma, Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813, Prakash, Vineet and Wells, Kevin 2019. Using deep learning to detect esophageal lesions in PET-CT scans. Presented at: SPIE Medical Imaging 2019, San Diego, California, USA, 16-21 February 2019. Published in: Gimi, B. and Krol, A. eds. Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging. SPIE, 10.1117/12.2511738

Smith, Rhodri L., Ackerley, Ian M., Wells, Kevin, Bartley, Lee, Paisey, Stephen ORCID: https://orcid.org/0000-0002-2274-3708 and Marshall, Chris ORCID: https://orcid.org/0000-0002-2228-883X 2019. Reinforcement learning for object detection in PET imaging. Presented at: 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Manchester, England, 26 October - 02 November 2019. 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, pp. 1-4. 10.1109/NSS/MIC42101.2019.9060031

Ackerley, Ian, Smith, Rhodri, Scuffham, James, Halling-Brown, Mark, Lewis, Emma, Spezi, Emilio, Prakash, Vineet and Wells, Kevin 2019. Can deep learning detect esophageal lesions in PET-CT scans? Presented at: 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Manchester, England, 26 October - 02 November 2019. 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, pp. 1-4. 10.1109/NSS/MIC42101.2019.9059833

Smith, Rhodri, Rahni, A., Jones, J. and Wells, K. 2018. A Kalman-based approach with EM optimization for respiratory motion modelling in medical imaging. IEEE Transactions on Radiation and Plasma Medical Sciences 3 (4) , pp. 410-420. 10.1109/TRPMS.2018.2879441

Martins, C, Da Pieve, C, Burley, T, Smith, Rhodri, Ciobota, D, Allott, L, Harrington, K, Oyen, W, Smith, G and Kramer-Marek, G 2018. HER3-mediated resistance to Hsp90 inhibition detected in breast cancer xenografts by affibody-based PET imaging. Clinical Cancer Research 24 (8) , 1853--1865. 10.1158/1078-0432.CCR-17-2754

Smith, Rhodri L., Paisey, Stephen J., Evans, N., Florence, V., Fittock, E., Siebzehnrubl, F. and Marshall, Christopher ORCID: https://orcid.org/0000-0002-2228-883X 2018. Deep learning pre-clinical medical image segmentation for automated organ-wise delineation of PET. Presented at: Annual Congress of the European Association of Nuclear Medicine, Barcelona, Spain, 12-16 October 2019. , vol.45

Smith, Rhodri 2017. Motion correction in medical imaging. PhD Thesis, University of Surrey.

Smith, Rhodri L., Dasari, Paul, Lindsay, Cliff, King, Michael and Wells, Kevin 2016. Dense motion propogation from sparse samples for free breathing respiratory motion modelling. Presented at: 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), Seattle, WA, USA, 8-15 November 2014. 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 1--5. 10.1109/NSSMIC.2014.7430843

Burley, T. A., Martins, C. D., Da Pieve, C., Allott, L., Smith, R., Ciobita, D. M., Smith, G., Harrington, K. and Kramer-Marek, G. 2016. Imaging EGFR in head and neck cancer: useful prognostic and treatment monitoring tool? [Conference Abstract]. European Journal of Nuclear Medicine and Molecular Imaging 43 , S231--S231.

Smith, Rhodri, Rahni, A.A.A., Jones, John, Tahavori, Fatemeh and Wells, Kevin 2014. Motion estimation for nuclear medicine: a probabilistic approach. Presented at: SPIE Medical Imaging, San Diego, CA, USA, 15-20 February 2014. Published in: Ourselin, S. and Styner, M. A. eds. Proceedings Volume 9034, Medical Imaging 2014: Image Processing. SPIE, 10.1117/12.2044141

Rahni, Ashrani A. A., Smith, Rhodri, Lewis, Emma and Wells, Kevin 2013. Extracting respiratory motion from 4D MRI using organ-wise registration. Presented at: SPIE Medical Imaging, Lake Buena Vista, FL, USA, 9-14 February 2013. Published in: Ourselin, Sebastien and Haynor, David R. eds. Proceedings Volume 8669, Medical Imaging 2013: Image Processing. SPIE, p. 866930. 10.1117/12.2006861

Smith, Rhodri L., Rahni, Ashrani Abd, Jones, John and Wells, Kevin 2013. Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine. Presented at: 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC), Seoul, South Korea, 27 October-2 November 2013. 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC). IEEE, 1--4. 10.1109/NSSMIC.2013.6829066

Smith, Rhodri L., Wells, Kevin, Jones, John, Dasari, Paul, Lindsay, Cliff and King, Michael 2013. Toward a framework for high resolution parametric respiratory motion modelling. Presented at: 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC), Seoul, South Korea, 27 October-2 November 2013. 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC). IEEE, 1--4. 10.1109/NSSMIC.2013.6829294

Smith, Rhodri, Rahni, Ashrani Abd, Jones, John and Wells, Kevin 2013. Recursive Bayesian estimation for respiratory motion correction in nuclear medicine imaging. Presented at: 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference, Anaheim, CA, USA, 27 Oct - 3 Nov 2012. 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC). IEEE, 10.1109/NSSMIC.2012.6551672

This list was generated on Thu Apr 18 08:35:28 2024 BST.


Maintained by Cardiff University Information Services