Generative models and abstractions for large-scale neuroanatomy datasets.

Generative models and abstractions for large-scale neuroanatomy datasets. Curr Opin Neurobiol. 2019 Mar 14;55:112-120 Authors: Rolnick D, Dyer EL Abstract Neural datasets are increasing rapidly in both resolution and volume. In neuroanatomy, this trend has been accelerated by innovations in imaging technology. As full datasets are impractical and unnecessary for many applications, it is important to identify abstractions that distill useful features of neural structure, organization, and anatomy. In this review article, we discuss several such abstractions and highlight recent algorithmic advances in working with these models. In particular, we discuss the use of generative models in neuroanatomy; such models may be considered 'meta-abstractions' that capture distributions over other abstractions. PMID: 30878806 [PubMed - as supplied by publisher]
Source: Current Opinion in Neurobiology - Category: Neurology Authors: Tags: Curr Opin Neurobiol Source Type: research