Identification of optimal surgical intervention for Chiari I malformation

The herniation of cerebellum through the foramen magnum may block the normal flow of the cerebrospinal fluid, determining a severe disorder called Chiari I Malformation (CM-I).

Different surgical options are available to help patients, but there is no standard to select the optimal treatment. This research activity is aimed at developing a fully automated method to select the optimal intervention. It is based on morphological parameters of the brain, posterior fossa and cerebellum, estimated by processing sagittal magnetic resonance images (MRI).

Deep learning algorithms represent a further interesting alternative to suggest the optimal treatment by processing directly the MRIs. The study is in collaboration with the Neurosurgery Department of Meyer Children’s Hospital (Florence), with whom an institutional agreement for scientific collaboration has been established, and the Italian CM-I patient association AISMAC.

Erc Sector:

  • PE7_7 Signal processing, Image processing

Keywords:

  • Magnetic resonance imaging
  • Artificial intelligence

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