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Section: New Results

Multi-modal and multi-structure image registration

Participants : Pierre Fillard [Correspondant] , Viviana Siless.

In this project, we aim at adding neural fibers information to registration in order to lead a more plausible an accurate alignment of two anatomies.

In medical imaging studies, being able to compare images of hundreds of patients with images of hundreds of normal controls helps to detect abnormalities caused by pathologies. An abnormality can be seen as a deviation from the normal distribution of a structure.

Registration consists in finding a geometrical mapping from one subject's anatomy onto another one in order to align their structures and be able to compare them. Current registration algorithms align structures using solely information obtained from images.

In medical images, the information is mainly carried by the images contours, which is the interface between white and gray matter. Using only the information coming from the contours of the image, could lead to a misalignment of the internal structures, such as neural fibers, as they appear uniformly white in images.

Allowing registration algorithms to collect also information from the neural fibers and use it to constrain the registration will lead to a more plausible registration of anatomies as it will also force a proper fiber alignment.

This project is being developed in C++, using libraries such as ITK and VTK.

The project name is KaraMetria (see also https://sites.google.com/site/karametria/ ) and it is available at INRIAGForge https://gforge.inria.fr/projects/kmtk .

Figure 1. Above we show an example using two subjects. We called moving subject the subject we are registering, which the deformation transformation is applied to. We called fixed subject the one we are trying to align with.
Original fibers of fixed and moving sujects     Original fibers of fixed and registered moving subjects (without fiber constraint)Original fibers of fixed and registered moving subjects (with fiber constraint)
IMG/fib1IMG/fib2IMG/fib3
IMG/fib4IMG/fib5IMG/fib6

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