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Université Libre de Bruxelles

Fluorescence microscopy image segmentation and colocalization quantification


LISA - Image is involved in research and development in two main topics of applied sciences : image analysis and computer graphics.

In the field of image analysis and pattern recognition, LISA - Image develops new methods for object segmentation in digital images, based on classification and decision theory, as well as for tracking mobile objects in image sequences. Developed algorithms and applications cover 2D and 3D problems and are most of the time related to medical problems such as: automatic in vitro 2D & 3D cell tracking for characterization of cell migration and proliferation, characterization of pigmented skin lesions, tissue-based biomarkers, pulmonary emphysema and articulation cartilage. We are currently offering a number of intership and master thesis projects. 


In the context of Human kidney disease, the understanding of protein/protein interaction could be crucial to the development of new treatments. Using normal or mutated Human kidney cell lines we need to develop tools to analyze colocalization percentage between 2 or 3 protein partners.

Spatial overlap between two or more emission signals of multiply labelled fluorescent specimens can be observed and quantitated in fluorescence microscopy. This problem, called spatial colocalization, typically occurs between proteins and is a common question in optical microscopy. However, existing colocalization techniques are generally visual-based and therefore highly prone to random error and bias.

The objective of this project is to develop an automated method for colocalization quantification that includes automated segmentation of regions of interest and objective spatial colocalization quantification.

The applicant should satisfy the following requirements: choice of image processing subjects, experience in programing languages (preferably MATLAB or C++ or  ImageJ or Python).  



  • Experience and interest in computer vision (image processing & machine learning)

  • Programing skills: preferably experience or eagerness to learn Matlab or C++ or Python or ImageJ.

  • Good knowledge of English

  • Creative

  • Well-organized

We bieden aan

We offer an oportunity to work in a stimulating enviroment in one of the best Belgian universities in a highly popular field of computer vision. Additionally, a multidisciplinary topic of the internship is motivativating, interesting, and offers a good experiance for vast oportunities in the job market for both academia and industry. You will be guided and helped by experienced universtiy researchers, and you will have oportunity to work with highest quality images made using the lastest technology biomedical scanners. 

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