Geometric multiscale representions and neuroscience imagingMS69

Advances in imaging acquisition and labeling techniques in recent years have increased the availability of high resolution images in the field of neuroscience. To process such data there is a need for improved algorithms that are capable of capturing complex morphological structures in multidimensional data in a highly sensitive and comprehensive manner. I will present methods from multiscale analysis targeted to neuroscience imaging for the automated extraction of morphological features from fluorescent images of neuronas.

This presentation is part of Minisymposium “MS69 - Anisotropic multi scale methods and biomedical imaging
organized by: Davide Barbieri (Universidad Autonoma de Madrid) , Demetrio Labate (University of Houston) .

Demetrio Labate (University of Houston)
image reconstruction, image representation, image segmentation, machine learning, neuronal tracing