pystackreg

Description

Python/C++ port of the ImageJ extension TurboReg/StackReg written by Philippe Thevenaz/EPFL.

A python extension for the automatic alignment of a source image or a stack (movie) to a target image/reference frame.

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Detection of Molecules - DoM

Description

A collection of components for super resolution image data:

  • Detect Molecules
  • Reconstruct Image
  • Results table
  • Drift correction
  • Chromatic correction

Temporal Medial Filter

Description

This component can be used to find moving foreground features, which can be a powerful way to suppress false background detections in subsequent tracking steps.

set time window, and standard deviations above background for foreground time window should be more than 2x larger than time taken for a feature to traverse a pixel (NB. total window is 2x half-width +1) moving foreground identified by intensity increase relative to background average (i.e. median) for a pixel over a given time window "soft" segmentation, yielding foreground probability related to excess intensity (in standard deviations) over background level crude Anscombe transform applied to data to stabilize the variance

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Chainer

Description

Chainer is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using CuPy for high performance training and inference. For more details of Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter.

QCAnet

Description

Quantitative Criterion Acquisition Network (QCA Net) performs instance segmentation of 3D fluorescence microscopic images. QCA Net consists of Nuclear Segmentation Network (NSN) that learned nuclear segmentation task and Nuclear Detection Network (NDN) that learned nuclear identification task. QCA Net performs instance segmentation of the time-series 3D fluorescence microscopic images at each time point, and the quantitative criteria for mouse development are extracted from the acquired time-series segmentation image. The detailed information on this program is described in our manuscript posted on bioRxiv.

has function

Manual tracking with TrackMate

Description

Manual tracking using Trackmate plugin (comes with FIji, so no installation required if you are using Fiji). 

has function

GIMP

Description

This is the official website of the GNU Image Manipulation Program (GIMP).

GIMP is a cross-platform image editor available for GNU/Linux, OS X, Windows and more operating systems. It is free software, you can change its source code and distribute your changes.

Whether you are a graphic designer, photographer, illustrator, or scientist, GIMP provides you with sophisticated tools to get your job done. You can further enhance your productivity with GIMP thanks to many customization options and 3rd party plugins.

CLI

example

gimp -i -b '(simple-unsharp-mask "foo.png" 5.0 0.5 0)' -b '(gimp-quit 0)'

More details, see here: GIMP Batch Mode

Log3D

Description

The freely available software module below is a 3D LoG filter. It applies a LoG (Laplacian of Gaussian or Mexican Hat) filter to a 2D image or to 3D volume. Here, we have a fast implementation. It is a perfect tool to enhance spots, like spherical particles, in noisy images. This module is easy to tune, only by selecting the standard deviations in X, Y and Z directions.

IJ Macro command example

run("LoG 3D", "sigmax=1 sigmay=1 sigmaz=13 displaykernel=0 volume=1");

ImagePy

Description

This note presents the design of a scalable software package named ImagePy for analysing biological images. Our contribution is concentrated on facilitating extensibility and interoperability of the software through decoupling the data model from the user interface. Especially with assistance from the Python ecosystem, this software framework makes modern computer algorithms easier to be applied in bioimage analysis.

Jama

Description

JAMA is a basic linear algebra package for Java. It provides user-level classes for constructing and manipulating real, dense matrices. It is meant to provide sufficient functionality for routine problems, packaged in a way that is natural and understandable to non-experts. It is intended to serve as the standard matrix class for Java, and will be proposed as such to the Java Grande Forum and then to Sun. A straightforward public-domain reference implementation has been developed by the MathWorks and NIST as a strawman for such a class. We are releasing this version in order to obtain public comment. There is no guarantee that future versions of JAMA will be compatible with this one.

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