DeepSCEM

DeepSCEM enables fast and efficient segmentation of cellular electron microscopy images using deep learning with a focus on generation and training of models for organelle segmentation.

Key Features:

• Deep learning-based segmentation: Uses convolutional neural networks for automatic image segmentation of cellular electron micrographs.
• Organelle segmentation model generation: Supports efficient generation and training of models specifically for organelle segmentation.

Scientific Applications:

• Cellular electron microscopy image analysis: Automates segmentation of cellular electron microscopy images for organelle identification and analysis.

Methodology:

Deep learning using convolutional neural networks.