Projects
Automated Analysis of Histological Images Using Machine Learning and Image Processing Techniques KU Leuven
SUMMARY
Histology studies microscopic tissue appearance and properties.
Histology analysis is used to study disease at the cellular level. This analysis happens through microscopic examination of tissue sections,
thin slices of tissue that were obtained from biopsies, mounted on a microscope slide, and made visible using a specific dye. Digital imaging allows individual microscopic structures, ...
Contemporary image constructions: a rhetorical analysis of architectural images and their institutional performances, through the practices of Caruso St John, OFFICE Kersten Geers David Van Severen and architecten de vylder vinck taillieu. Ghent University
Hierarchical statistical image modeling with applications in analysis, restoration and coding of images and video Ghent University
Semi-automated image segmentation and registration, facilitating multi-modal image analysis for selective internal radiation therapy (SIRT) KU Leuven
The aim of this project is to develop dedicated image alignment (registration) and AI-based segmentation techniques in order to extract more information from these images. This will lead to more accurate dose calculations and treatment verification, which in turn will improve the efficacy of the therapy.
Next-generation pathology by MILAN: multiplex immunohistochemistry and advanced trainable image analysis KU Leuven
OrBITS Platform: A Cloud-Based Image Analysis and Drug Screening Service. University of Antwerp
Design of limited reference perceptual metrics for the analysis of quality of image and videa material Vrije Universiteit Brussel
- Compression of the necessary image properties using dimension reduction and sensitivity analysis;
- Combining the different part metrics to a single limited-reference (BR) quality metrics for automatic quality monitoring.
Artificial Intelligence for medical image analysis : application to functional ultrasound imaging KU Leuven
functional UltraSound imaging (fUSi) is a technology developed in our laboratory (Urban et al., 2015; Macé et al., 2018) allowing real-time visualization of brain activity with a high spatiotemporal resolution (100µm3 voxel size, 100ms). It has been widely validated in preclinical research but fUSi is currently limited to imaging of a small part of rodent’s brain. To extend fUSi capabilities, we recently developed 3D-fUSi for volumetric ...
Phenotyping perennial ryegrass using image analysis Research Institute for Agriculture, Fisheries and Food
The aim of the Fenogras project is to develop semi-automatic analysis procedures for images of individual perennial ryegrass plants grown in field trials. Growth and architectural features will be assessed using this phenotyping tool. The system will allow capture of many images of individual plants and efficient analysis of those images. The final aim is to use image analysis as a supporting ...