Structural aging of human neurons is the opposite of the changes in schizophrenia

no code implementations • 13 Nov 2022 • Ryuta Mizutani, Rino Saiga, Yoshiro Yamamoto, Masayuki Uesugi, Akihisa Takeuchi, Kentaro Uesugi, Yasuko Terada, Yoshio Suzuki, Vincent De Andrade, Francesco De Carlo, Susumu Takekoshi, Chie Inomoto, Naoya Nakamura, Youta Torii, Itaru Kushima, Shuji Iritani, Norio Ozaki, Kenichi Oshima, Masanari Itokawa, Makoto Arai

The neurite curvature also showed a correlation with a hallucination score (Pearson's r = 0. 80, p = 1. 8 x 10^(-4)), indicating that neurite structure is relevant to brain function.

Hallucination

Distributed optimization for nonrigid nano-tomography

1 code implementation • 11 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

Structural diverseness of neurons between brain areas and between cases

1 code implementation • 1 Jul 2020 • Ryuta Mizutani, Rino Saiga, Yoshiro Yamamoto, Masayuki Uesugi, Akihisa Takeuchi, Kentaro Uesugi, Yasuko Terada, Yoshio Suzuki, Vincent De Andrade, Francesco De Carlo, Susumu Takekoshi, Chie Inomoto, Naoya Nakamura, Youta Torii, Itaru Kushima, Shuji Iritani, Norio Ozaki, Kenichi Oshima, Masanari Itokawa, Makoto Arai

The analysis also revealed the geometric differences between the neurons of the schizophrenia and control cases, suggesting that neuron structure is associated with brain function.

TomoGAN: Low-Dose Synchrotron X-Ray Tomography with Generative Adversarial Networks

3 code implementations • 20 Feb 2019 • Zhengchun Liu, Tekin Bicer, Rajkumar Kettimuthu, Doga Gursoy, Francesco De Carlo, Ian Foster

We present \TOMOGAN{}, a denoising technique based on generative adversarial networks, for improving the quality of reconstructed images for low-dose imaging conditions.

Denoising