SyMBac
Synthetic bacteria images
Generates high-quality synthetic images of bacterial cells to aid machine learning-based image segmentation algorithms.
Accurate segmentation of bacterial microscope images using deep learning synthetically generated image data.
19 stars
4 watching
9 forks
Language: Jupyter Notebook
last commit: 6 months ago
Linked from 1 awesome list
biologydeep-learningimage-processingmachine-learningmicroscopysegmentationsynthetic-biologysynthetic-datasynthetic-dataset-generation
Related projects:
Repository | Description | Stars |
---|---|---|
pycroscopy/atomai | A PyTorch-based package for analyzing microscopy data with machine learning algorithms | 197 |
turagalab/decode | An implementation of a deep learning-based tool for single-molecule localization microscopy with high accuracy and speed. | 96 |
computational-cell-analytics/micro-sam | Tools for interactive microscopy image segmentation and tracking | 372 |
fish-quant/big-fish | A toolbox for analyzing microscopy images of cells labeled with single-molecule fluorescent in situ hybridization (smFISH) tags. | 58 |
jhsmit/colicoords | A platform for analyzing fluorescence microscopy data from rodlike cells. | 26 |
reedscot/icml2016 | Generates synthetic images from text descriptions using a Generative Adversarial Network (GAN) | 912 |
abe404/root_painter | An open-source tool for training deep learning models for image analysis | 59 |
jungmannlab/picasso | Tools for enhancing image resolution using machine learning algorithms | 110 |
csbdeep/csbdeep | Toolbox for improving digital images taken with fluorescence microscopy using deep learning algorithms | 287 |
oist/usiigaci | Automated cell tracking in phase contrast microscopy images using machine learning and computer vision techniques | 193 |
kreshuklab/plant-seg | A tool for cell instance aware segmentation in densely packed 3D volumetric images | 101 |
bmirds/deepslide | Classifies high-resolution microscopy images of lung adenocarcinoma using deep neural networks with a sliding window framework. | 494 |
ternaus/iglovikov_segmentation | A deep learning-based semantic segmentation pipeline using the Catalyst framework. | 20 |
ethanhe42/u-net | A convolutional neural network architecture for biomedical image segmentation | 430 |
bebop/poly | A comprehensive Go package for computational synthetic biology and gene engineering | 676 |