Past Projects in Medical Image Analysis Past Projects in Medical Image Analysis

Wireless Capsule Endoscopy (WCE)

This research project uses computational colour vision to improve analysis of WCE video (a tedious and time consuming task currently undertaken by clinical experts). In collaboration with gastroenterologists at Norfolk and Norwich University Hospital the group developed a tool which cuts the time taken to analyse WCE by more than 50%. Further details and publications.

wireless capsule endoscopy

Image Guided Radiation Therapy Treatment

image guided radiation therapy treatment imageThe high levels of ionising radiation used in radiotherapy treatment are harmful to both malignant and healthy tissue so it must be accurately targeted. Modern treatment planning systems use 3D CT data to prescribe highly conformal dose distributions but these plans can be compromised by intra-fraction patient motion (due to breathing). UEA's work within EU FP6 collaborative project MAESTRO addresses this problem through the development of a range of online motion compensation strategies. Further details and publications.


Retinal Vessel Segmentation

The condition of tissues and vessels in images of the retina (routinely captured as part of an eye test) can give early diagnosis of a number of serious conditions such as glaucoma and diabetes. But the images require expert examination and their interpretation can be time consuming. The segmentation of vessels in retinal images has been the focus of researchers for more than two decades. We use a machine learning framework paradigm, generate filters and our evaluations show the technique outperforms traditional approaches using matched filters. Further details and publications.

Original image, (left image), Ground truth (middle image) and Automatic (texton) segmentation (right image)


  1. Berens, J., Mackiewicz, M. and Bell, G. D., Stomach, Intestine and Colon tissue discriminators for Wireless Capsule Endoscopy images. In Proceedings of SPIE, vol. 5747, p. 283-290, 2005
  2. Berens,J., Mackiewicz,M., Fisher, M. and Bell,G.D., Using colour distributions to discriminate tissues in wireless capsule endoscopy, In Proc. MIUA 2005, pp. 107-110, Bristol, UK, 2005.
  3. Coimbra, M., Mackiewicz, M.,Fisher,M.,Jamieson,C.,Soares,J., and Silva Cunha, J.P., Computer vision tools for capsule endoscopy exam analysis, Eurasip News Letter (invited paper), March 2007.
  4. Finlayson, G., Mackiewicz, M., and Hurlbert, A., Making calculation of Logvinenko's coordinates easy. Proceedings of 20th CIC conference, Los Angeles, USA, Nov, 2012,
  5. Crichton, S., Pichat, J., Mackiewicz, M., and Hurlbert, A., Skin chromaticity gamuts for illumination recovery, Proceedings of 6th CGIV conference, Amsterdam, Netherlands, May, 2012 (Best Paper Award)
  6. Fisher, M.,Mackiewicz,M. Colour image analysis of wireless capsule endoscopy video: A review, In M. Emre Celebi and Gerald Schafer (Eds.), Color Medical Image Analysis, Springer, 2012
  7. Mackiewicz, M., Berens, J., and Fisher, M., Wireless capsule endoscopy colour video segmentation, IEEE Trans. Medical Imaging, 27(12):1769-81, December 2008.
  8. Mackiewicz,M. Computer-assisted wireless capsule endoscopy video analysis, PhD thesis, School of Computing Sciences, UEA, Norwich, UK, 2007.
  9. Mackiewicz,M., Berens,J., Fisher, M., Bell,G.D. and Jamieson, C. Computational colour techniques can speed up the viewing of Wireless Capsule Endoscopy(WCE) images as well as determine gastric and intestinal transit times(GTT and ITT). Endoscopy, 54 (Suppl II):A10, 2005.
  10. Mackiewicz, M. Capsule, Endoscopy - State of the Technology and Computer Vision Tools After the First Decade, New Techniques in Gastrointestinal Endoscopy, Oliviu Pascu (Ed.), ISBN 978-953-307-777-2, InTech., 2011
  11. Mackiewicz, M., Berens, J., Fisher, M. and Bell, G.D., Colour and texture based gastrointestinal tissue discrimination. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, vol. II, p.597-600, Toulouse, France, May, 2006
  12. Mackiewicz, M., Crichton, S., Newsome, S., Gazerro, R., Finlayson, G., and Hurlbert, A., Spectrally tunable LED illuminator for vision research, Proceedings of 6th CGIV conference, Amsterdam, Netherlands, May, 2012

Research Team

Lei Zhang, Dr. Mark Fisher, Dr. Michal Mackiwicz