Automated neuron tracing using probability hypothesis density filtering | Zendy

Miroslav Radojević | Zendy; Erik Meijering | Zendy

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Automated neuron tracing using probability hypothesis density filtering

Author(s) -

Miroslav Radojević,

Erik Meijering

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btw751

Subject(s) - tracing , computer science , software , java , plug in , source code , code (set theory) , artificial intelligence , image (mathematics) , bayesian probability , computer vision , pattern recognition (psychology) , data mining , programming language , set (abstract data type)

The functionality of neurons and their role in neuronal networks is tightly connected to the cell morphology. A fundamental problem in many neurobiological studies aiming to unravel this connection is the digital reconstruction of neuronal cell morphology from microscopic image data. Many methods have been developed for this, but they are far from perfect, and better methods are needed.

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