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Frank C Langbein (via github actions) edited this page Nov 15, 2022 · 5 revisions

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.

People

Publications

  • 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]

Presentations

  • 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]

PhDs

  • 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.

Reports

  • 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]

Code

  • QDicom Utilities - Utilities to deal with dicom files and data repositories.

  • MRI Delineator - A tool for delineating polygons upon stacks of MRI slices.

Data

  • Swansea University PCa data set.

Workshops

  • PCa Workshop, Swansea University, 15th November 2018.

  • VLunch Seminar, Cardiff University, August 2018: Rhodri Evans, Prostate Cancer Diagnosis.

Locations

The wiki is written and maintained on Qyber\black at https://qyber.black/ca/info-cancer/

Contact

For any general enquiries relating to this project group, send an e-mail.

License

CC BY-NC-SA 4.0 This wiki is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The publications, code, data, etc. may be under a different license. Check the relevant information provided with these products.

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