Research topics

LISA has developed expertise both in image analysis/pattern recognition and computer graphics. In the field of image analysis and pattern recognition, this unit develops new methods for object segmentation, recognition or tracking in 2D and 3D problems, multi-modal image registration, as well as statistical learning methods applied to image and data classification. Developed algorithms are related to biomedical, industrial and HMI (Human Machine Interface) applications. Image synthesis and virtual reality research activities are oriented towards medical and real time applications such as: patient home care, computer-assisted surgery, 3D real-time rendering of complex geometry and object collision, exact visibility computation and gestural interface.

Most of the aforementioned 2D/3D audio-visual signal processing algorithms require heavy number crunching on large data sets and must hence rely on efficient multi-core parallelization to ensure low-latency, real-time processing. Best performances are achieved when thoroughly trading off the intricate relationship between the application requirements, the algorithmic structure and the architecture’s multilevel memory hierarchy. In particular, General Purpose GPU programming and its efficient partitioning into regular processing kernels with minimal data dependency crossovers calls for a complementary expertise over the full application-algorithm-architecture value chain. In particular, the recent Deep Learning development for signal and image processing gain in efficacy thanks to the massively parallel computing power available on modern GPU cards; this research topic has been chosen for three new phd thesis in the lab.

LISA, following a problem-centered approach, tackles all hardware and software aspects of the chain in multidisciplinary teams (MDs, biologists, engineers, computer scientists, archaeologists, artists ...) over multi-institutional collaborations to deliver functional applications. The research is funded both by institutional/public funds and industry collaborations. LISA's achievements include one patent, several highly cited biomedical papers, implementation of acquisition and thermoregulation devices for live cell imaging, multi-media event organization and international cultural heritage projects.

DEEP NEURAL NETWORK APPLICATIONS

Image super-resolution and image fusion

Automatic P&ID recognition

Depth-image analysis

Relevant Similarities In Images through DNN

MEDICAL APPLICATIONS

Whole slide imaging

Patient-Derived Tumor Growth Modeling from Multiparametric Analysis of Combined Dynamic PET/MR Data

Platform for Imaging in Clinical Research in Brussels

Proton Therapy Research in Wallonia

In vitro cell tracking

AUGMENTED/VIRTUAL REALTY

Augmented RealiTy Unilateral RehabilitatiOn

INTERNATIONAL COLLABORATIONS

Open-echography

COllaborative Consortium for the early detection of LIver CANcer

Previous research

Automatic Recognition for Map Update by Remote Sensing

Star Image Recognition and Its Application in Guidance for Spacecrafts

Multi-modal sensor for road traffic analysis

Multi-classifier systems

PLATFORMS

The LISA is closely connected to two ULB's technological platforms