Semi-automated

Description

3DeeCellTracker is a deep-learning based pipeline for tracking cells in 3D time-lapse images of deforming/moving organs.

The installation comprises a set of Jupyter notebooks and a library they depend on. The workflow steps include separate training and segmentation/tracking.

Examples of cell tracking from the reference publication are: ~100 cells in a freely moving nematode brain, ~100 cells in a beating zebrafish heart, and ~1000 cells in a 3D tumor spheroid.

Overall procedures of our method (Wen et al. eLife, 2021–Figure 1)
Description

napari-lattice is a napari plugin designed for the analysis and visualization of Lattice Lightsheet Microscopy (LLSM) and Oblique Plane Microscopy (OPM) data, particularly focusing on data acquired from Zeiss Lattice Lightsheet systems. Also available as lls-core - a command line version of the same tool which does not require napari.

napari-lattice allows users to deskew and deconlolve lattice light sheet, or any oblique plane microscopy, data. To speed processing, users can provide ROIs to be cropped and processed separately.  This significantly speeds up processing time and allows many options for parallelisation. 

Description

AnyLabeling is Effortless AI-assisted data labeling tool with AI support from Segment Anything and YOLO models!

AnyLabeling = LabelImg + Labelme + Improved UI + Auto-labeling

Installation

Standalone (executable)

The executable file links are provided in Assets section here

Install from source

git clone https://github.com/vietanhdev/anylabeling
cd anylabeling
pip install .

Install from PyPI

pip install anylabeling

With GPU support:

pip install anylabeling-gpu
Description

A generalist framework for multi-dimensional automatic spot detection and quantification.

SpotMAX is designed to accomplish two tasks:

  1. Detecting and quantifying globular-like structures (a.k.a. "spots")
  2. Segmenting and quantifying fluorescently labelled structures

It supports 2D, 3D, 4D, and 5D data, i.e., z-stacks, timelapse, and multiple fluorescence channels (and combinations thereof).

has function
SpotMAX Logo
Description

Description from Github page:

A GUI-based Python framework for segmentation, tracking, cell cycle annotations and quantification of microscopy data.
Provides a GUI for neural network models including Segment Anything Model (SAM), YeaZ, cellpose, StarDist, YeastMate, omnipose, delta, DeepSea.

Schematic overview of pipeline and GUI