A quiet revolution is under way in technologies used for nanoscale cellular imaging.
Focused ion beams, previously restricted to the materials sciences and semiconductor …

Electron microscopy (EM) enables high-resolution imaging of tissues and cells based on 2D
and 3D imaging techniques. Due to the laborious and time-consuming nature of manual …

In this paper, we study the influence of both long and short skip connections on Fully
Convolutional Networks (FCN) for biomedical image segmentation. In standard FCNs, only …

In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation
that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual …

Abstract Convolutional Neural Networks (CNNs) can be shifted across 2D images or 3D
videos to segment them. They have a fixed input size and typically perceive only small local …

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image
analysis framework for automated three-dimensional cell segmentation in large-scale …

The goal of connectomics is to manifest the interconnections of neural system with the
Electron Microscopy (EM) images. However, the formidable size of EM image data renders …

Electron microscopy (EM) image segmentation plays an important role in computer‐aided
diagnosis of specific pathogens or disease. However, EM image segmentation is a laborious …

Progress in electron microscopy-based high-resolution connectomics is limited by data
analysis throughput. Here, we present SegEM, a toolset for efficient semi-automated …

Motivation Progress in 3D electron microscopy (EM) imaging has greatly facilitated
neuroscience research in high-throughput data acquisition. Correspondingly, high …