40 citations · 69 across the 5 of their papers we have counts for
5 papers
PyTorch Connectomics: A Scalable and Flexible Segmentation Framework for EM Connectomics
Zudi Lin, Donglai Wei, Jeff Lichtman +1
We present PyTorch Connectomics (PyTC), an open-source deep-learning framework for the semantic and instance segmentation of volumetric microscopy images, built upon PyTorch. We de…
A Multi-Pass Approach to Large-Scale Connectomics
Yaron Meirovitch, Alexander Matveev, Hayk Saribekyan +8
The field of connectomics faces unprecedented "big data" challenges. To reconstruct neuronal connectivity, automated pixel-level segmentation is required for petabytes of streaming…
Icon: An Interactive Approach to Train Deep Neural Networks for Segmentation of Neuronal Structures
Felix Gonda, Verena Kaynig, Ray Thouis +4
We present an interactive approach to train a deep neural network pixel classifier for the segmentation of neuronal structures. An interactive training scheme reduces the extremely…
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes using High-Resolution Neural EM Data
Ayushi Sinha, William Gray Roncal, Narayanan Kasthuri +3
Accurately estimating the wiring diagram of a brain, known as a connectome, at an ultrastructure level is an open research problem. Specifically, precisely tracking neural processe…
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes
Ayushi Sinha, William Gray Roncal, Narayanan Kasthuri +8
In this paper, we present a new pipeline which automatically identifies and annotates axoplasmic reticula, which are small subcellular structures present only in axons. We run our…