3DBrainMiner is a analysis framework developped in collaboration between the LIFAT laboratory and the NECOS team of INRAE Nouzilly.

This research aims at developing models and algorithms to describe, analyze and compare objectively the brains of different animal species or humans.
  • These current works aim at:
    • i/ making images, segmentations, and graph representations of brain available to the Neuroscience, Animal Sciences and Machine Learning research communities =>3DBrainModels
    • ii/ providing open access to the source codes of the tools developped to generate graph models of brain => 3DBrainMiner platform.
      The produced graphs can combine a wide variety of information such as morphometric (volume, distance, ...), structural (signal intensity) and functional (symmetry, connection strength, ...) variables.
    • iiI/ designing new algorithms dedicated to the analysis and comparison of graphs (using Graph Neural Networks)
  • In the context of Antoine Bourlier's PhD thesis (co-direction LIFAT-NECOS, co-funding INRAE-Région CVL), Graph-based machine learning algorithms (GNN) are developed to analyze and compare the models produced with their various parameters to, for example, assess the impact of the rearing environment (type of suckling, ...) on the anatomical organization of the brain of young lambs.
  • This dynamic will allow a better understanding of the anatomy of the ovine brain, its development and the impact of the rearing conditions. In the longer term, this platform could be extended to other animal species to facilitate comparative anatomy and to human brains for clinical purposes.
The SILA3D platform was first developed in the framework of Gaétan Galisot's thesis (regional projects NeuroGeo and Neuro2Co). SILA3D proposes a new method of interactive and incremental segmentation of 3D medical images.


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Computer Science Laboratory of Tours (LIFAT).
Université de Tours.
64 av. Jean Portalis 37200 Tours city, France.
Email: sila3D at univ-tours dot fr