Medical Imaging

Contact: Professor Lasse Lensu

Medical imaging is among the most important application areas of computer vision and image analysis. In the recent years, MVPR has conducted research on processing microscopy images and automatic detection of lesions of diabetic retinopathy from fundus images. The laboratory has published the DiaRetDB1 database for benchmarking diabetic retinopathy detection methods and the database has become one of the standard benchmarks in the field.

See: DiaRetDB1 V2.1.

Featured projects

Retinal Blood Vessel Segmentation and Characterisation (2014-2016)

Retinal blood vessel structure is an important indicator of many retinal and systemic diseases, which has motivated the development of various image segmentation and characterisation methods for the blood vessels. In this project, supervised and unsupervised segmentation methods were reviewed and compared as part of further characterisation of the vessel structure. The research was carried out in collaboration with the University of Birmingham, the University of Eastern Finland, and the University of Tampere.

Supplementary information for our paper Performance Comparison of Publicly Available Retinal Blood Vessel Segmentation Methods can be found under this project.

ReVision (2012-2015)

ReVision was a multidisciplinary research project focusing on improving retinal imaging, image processing, and computational analysis of the image data to enable efficient automatic and semi-automatic methods for eye health. The consortium partners were the University of Eastern Finland (responsible institution; photonics) and the University of Tampere (ophthalmology). The project had strong international collaboration with the University of Birmingham and Tokyo Institute of Technology. The project was funded by the Academy of Finland.

ReVision produced image processing and analysis methods for spectral retinal images, an enhanced prototype of a spectral fundus camera and a tunable spectral light source, a few scientific publications and one doctor of science in technology (Lauri Laaksonen, LUT).

ImageRet (2006-2009)

The ultimate goal of the Imageret project was to develop new imaging hardware and novel image processing methods to efficiently and reliably assist in medical decision making in diabetic retinopathy diagnosis.

The goal was achievable by combining the knowledge from medical science, optics, and image processing and via the scientific research provide new results to be used in medics. Furthermore, by educating new young masters and doctors within the field of medical image processing and medical image acquisition the future requirements of the health care can be met.