Search Results for author: Narayanan Kasthuri

Found 9 papers, 3 papers with code

Internal Feedback in Biological Control: Architectures and Examples

no code implementations11 Oct 2021 Anish A. Sarma, Jing Shuang Li, Josefin Stenberg, Gwyneth Card, Elizabeth S. Heckscher, Narayanan Kasthuri, Terrence Sejnowski, John C. Doyle

In biology, in addition to typical feedback between plant and controller, we observe feedback pathways within control systems, which we call internal feedback pathways (IFPs), that are often very complex.

Distributed optimization for nonrigid nano-tomography

1 code implementation11 Jul 2020 Viktor Nikitin, Vincent De Andrade, Azat Slyamov, Benjamin J. Gould, Yuepeng Zhang, Vandana Sampathkumar, Narayanan Kasthuri, Doga Gursoy, Francesco De Carlo

Resolution level and reconstruction quality in nano-computed tomography (nano-CT) are in part limited by the stability of microscopes, because the magnitude of mechanical vibrations during scanning becomes comparable to the imaging resolution, and the ability of the samples to resist beam damage during data acquisition.

Distributed Optimization Optical Flow Estimation

RhoanaNet Pipeline: Dense Automatic Neural Annotation

no code implementations21 Nov 2016 Seymour Knowles-Barley, Verena Kaynig, Thouis Ray Jones, Alyssa Wilson, Joshua Morgan, Dongil Lee, Daniel Berger, Narayanan Kasthuri, Jeff W. Lichtman, Hanspeter Pfister

The best segmentation results obtained gave $V^\text{Info}_\text{F-score}$ scores of 0. 9054 and 09182 for the cortex datasets, 0. 9438 for LGN, and 0. 9150 for Cerebellum.

Segmentation

Quantifying mesoscale neuroanatomy using X-ray microtomography

no code implementations13 Apr 2016 Eva L. Dyer, William Gray Roncal, Hugo L. Fernandes, Doga Gürsoy, Vincent De Andrade, Rafael Vescovi, Kamel Fezzaa, Xianghui Xiao, Joshua T. Vogelstein, Chris Jacobsen, Konrad P. Körding, Narayanan Kasthuri

Methods for resolving the 3D microstructure of the brain typically start by thinly slicing and staining the brain, and then imaging each individual section with visible light photons or electrons.

Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes

no code implementations16 Apr 2014 Ayushi Sinha, William Gray Roncal, Narayanan Kasthuri, Ming Chuang, Priya Manavalan, Dean M. Kleissas, Joshua T. Vogelstein, R. Jacob Vogelstein, Randal Burns, Jeff W. Lichtman, Michael Kazhdan

The contribution of this work is the introduction of a straightforward and robust pipeline which annotates axoplasmic reticula with high precision, contributing towards advancements in automatic feature annotations in neural EM data.

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