20 citations · 36 across the 3 of their papers we have counts for
4 papers
Learning Guided Electron Microscopy with Active Acquisition
Lu Mi, Hao Wang, Yaron Meirovitch +5
Single-beam scanning electron microscopes (SEM) are widely used to acquire massive data sets for biomedical study, material analysis, and fabrication inspection. Datasets are typic…
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics
Yaron Meirovitch, Lu Mi, Hayk Saribekyan +3
Pixel-accurate tracking of objects is a key element in many computer vision applications, often solved by iterated individual object tracking or instance segmentation followed by o…
Morphological Error Detection in 3D Segmentations
David Rolnick, Yaron Meirovitch, Toufiq Parag +5
Deep learning algorithms for connectomics rely upon localized classification, rather than overall morphology. This leads to a high incidence of erroneously merged objects. Humans,…
Toward Streaming Synapse Detection with Compositional ConvNets
Shibani Santurkar, David Budden, Alexander Matveev +4
Connectomics is an emerging field in neuroscience that aims to reconstruct the 3-dimensional morphology of neurons from electron microscopy (EM) images. Recent studies have success…