Info - Cancer

Info - Cancer

Information about the prostate and brain cancer projects and summary of published results.

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The projects and published results in this group deal with prostate cancer.

We investigate the use of multi-parametric magnetic resonance imaging and spectroscopy for prostate and brain cancer detection, focused on early-stage cancer diagnosis, anatomical segmentation, region of interest identification, machine learning and characterising biomarkers.



  • E Alwadee, X Sun, Y Qin, FC Langbein. LATUP-Net: A Lightweight 3D Attention U-Net with Parallel Convolutions for Brain Tumor Segmentation. Preprint, 2024. [arxiv:2404.05911] [PDF]
  • I Papadopoulos, J Phillips, R Evans, N Fenn, S Shermer. Evaluation of Diffusion Weighted Imaging in the Context of Multi-Parametric MRI of the Prostate in the assessment of suspected low volume prostatic carcinoma. Magnetic Resonance Imaging, 47, 131-136, 2018. [arxiv:1711.09703] [DOI:10.1016/j.mri.2017.11.014]
  • ZG Portakal, S Shermer, E Spezi, T Perrett, J Phillips. Effect of Noise Floor Suppression on Diffusion Kurtosis for Prostate Brachytherapy. In: Radiotherapy and Oncology, 123, S938-S938, 2017. [PDF:poster]
  • S Shermer, I Papadopoulos, G Portakal, J Phillips, R Evans. Multimodal magnetic resonance imaging and spectroscopy for prostate cancer screening and staging. Physica Medica, 32, Suppl. 3, 324, 2016. [DOI:10.1016/j.ejmp.2016.07.217]
  • ZG Portakal, JW Phillips, CE Richards, E Spezi, T Perrett, DG Lewis, Z Yegingil. EP-1878: Feasibility of gel phantoms in MRI for the assessment of kurtosis for prostate brachytherapy. J Radiotherapy and Oncology, 119, S887-S888, 2016. [PDF:paper]


  • S Shermer. Quantitative MRI and Spectroscopy: from quantification of chemicals in the brain to diagnostic tools for prostate cancer. Healthcare Technologies Research Group seminar at the School of Computer Science and Informatics, Cardiff University, 16/2/2022. [YouTube:video]


  • I Papadopoulos. Multi-parametric MRI of Prostate Cancer: Assessmnet of Spectroscopy, Diffusion, Dynamic Contrast and Relaxometry for Active Surveillance and Staging. PhD thesis, Swansea University, 2018. [DOI:10.23889/Suthesis.51146]
  • AAS Muftah. Machine Learning and Image Analysis for Prostate Cancer Detection. School of Computer Science and Informatics, Cardiff University.
  • EJ Alwadee. Novel Adaptive Down-sample Neural Network Classification for Detecting Brain Tumour from MRI Brain Images. School of Computer Science and Informatics, Cardiff University.
  • O Ukwandu. Developing A Robust Artificial Intelligence System for Precision Diagnosis of Prostate Cancer Using Magnetic Resonance Imaging. School of Computer Science and Informatics, Cardiff University.


  • A Nightingale. Delineating regions of interest in MRI/S prostate scans for cancer diagnosis. MSc Computing dissertation, Cardiff University. 2020.
  • D Morgan. Delineating regions of interest in MRI prostate scans. BSc Computer Science project, Cardiff University, 2019. [Archive]




  • PCa Workshop, Swansea University, 15th November 2018.
  • VLunch Seminar, Cardiff University, August 2018: Rhodri Evans, Prostate Cancer Diagnosis.


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