Machine Vision and Pattern Recognition Laboratory (MVPR)

Funding for MVPR from Academy of Finland

The Academy of Finland decided to fund the project Automatic segmentation of overlapping objects for cell image analysis (CellVision)

The CellVision project serves needs of the healthcare and the industry. In industrial and biomedical machine vision applications it is very important to deal with digital images which contain a very large amount of overlapping objects. This lead to very useful applications such as cell imaging in the healthcare for diagnosis of cancer and nanoparticle imaging in the industry for quality control and material research. Our goal is to study automatic segmentation of overlapping objects. Manual segmentation is laborious, slow, and sensitive to interpretations. Images may contain tens of thousands of objects and it is time-consuming to detect attached and overlapping objects accurately. Recent developments in machine learning, especially with deep neural networks have enabled massive computations with large datasets. We have developed the state-of-the-art methods for nanoparticle segmentation mainly for industrial purposes, and now our plan is to extend our approach to cell imaging for the modern digital healthcare using machine vision and machine learning.

This is a collaborative project between MVPR and Professor Alan Bovik from LIVE at University of Texas at Austin (UTA).

The two-year project was started in January 1, 2018. The principal investigator is Prof. Heikki Kälviäinen and the project manager is Adjunct Professor, Dr. Tuomas Eerola. See the COMPHI project page for more information.