[Seminar] "An automated high-throughput image processing pipeline for the extraction of structural connectivity from marmoset brain images", Dr. Skibbe
Neural Computation Unit (Doya Unit) would like to invite you to a seminar as follows.
Date: Wednesday, January 23
Venue: Meeting Room D015 - L1 Bldg
Speaker: Dr. Henrik Skibbe, Kyoto University
Title: An automated high-throughput image processing pipeline for the extraction of structural connectivity from marmoset brain images
Abstract: In my talk, I will give an overview over our automated marmoset brain image processing pipeline and will address the problem of detecting and tracking axons in densely labeled samples of neurons in large image datasets acquired from entire marmoset brains.
The pipeline is part of the Japan Brain/MINDS projects. In the Brain/MINDS projects, a connectivity study on marmoset brains uses two-photon microscopy fluorescence images of axonal projections to collect the neuron connectivity from defined brain regions at the mesoscopic scale. The processing of the images requires the detection, segmentation, and registration of the axonal tracer signal. This is difficult because there is a trade-off between the detection of as much tracer signal as possible while not misclassifying other background structures as the signal. Imaging noise, a cluttered image background, insufficient spatial resolution, distortions or varying image contrast make problems.
We have developed a pipeline that processes and maps tracer, Nissl, and backlit image data to a common brain image space. The pipeline incorporates state-of-the-art machine learning and image processing techniques to extract and map all relevant information in a robust manner.
We hope to see many of you.
Neural Computation Unit