Info - Prostate Cancer
Information about the prostate cancer projects and summary of published results.
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 cancer detection, focused on early-stage cancer diagnosis, anatomical segmentation, region of interest identification, machine learning and characterising biomarkers.
- Sophie Shermer, Physics, Swansea University
- Rhodri Evans, Institute of Life Science, Swansea University
- Asmail Muftah, School of Computer Science and Informatics, Cardiff University
- Frank C Langbein, School of Computer Science and Informatics, Cardiff University; langbein.org
- Jing Wu, School of Computer Science and Informatics, Cardiff University
- Kirill Sidorov, School of Computer Science and Informatics, Cardiff University
- Alexia Zoumpoulaki, School of Computer Science and Informatics, Cardiff University
- Andrew Nightingale, School of Computer Science and Informatics, Cardiff University
- Daniel Morgan, School of Computer Science and Informatics, Cardiff University
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]
- 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]
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]
QDicom Utilities - Utilities to deal with dicom files and data repositories.
MRI Delineator - A tool for delineating polygons upon stacks of MRI slices.
- Swansea University PCa data set.
PCa Workshop, Swansea University, 15th November 2018.
VLunch Seminar, Cardiff University, August 2018: Rhodri Evans, Prostate Cancer Diagnosis.
For any general enquiries relating to this project group, send an e-mail.
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