Synonyms
Semantic object classification
Isolated object classification

Icy Label Extractor

has function
need a thumbnail

ImJoy

Description

ImJoy is a plugin powered hybrid computing platform for deploying deep learning applications such as advanced image analysis tools.

ImJoy runs on mobile and desktop environment cross different operating systems, plugins can run in the browser, localhost, remote and cloud servers.

With ImJoy, delivering Deep Learning tools to the end users is simple and easy thanks to its flexible plugin system and sharable plugin URL. Developer can easily add rich and interactive web interfaces to existing Python code.

NeuroMorph

Description

NeuroMorph is a toolset designed to import, analyze, and visualize mesh models in Blender. It has been developed specifically for the morphological analysis of 3D objects derived from serial electron microscopy images of brain tissue, but much of its functionality can be applied to any 3D mesh. These mesh objects can be generated by any 3D image segmentation software, such as ilastik or Fiji

FishInspector

Description

The software FishInspector provides automatic feature detections in images of zebrafish embryos (body size, eye size, pigmentation). It is Matlab-based and provided as a Windows executable (no matlab installation needed).

The recent version requires images of a lateral position. It is important that the position is precise since deviation may confound with feature annotations. Images from any source can be used. However, depending on the image properties parameters may have to be adjusted. Furthermore, images obtained with normal microscope and not using an automated position system with embryos in glass capillaries require conversion using a KNIME workflow (the workflow is available as well). As a result of the analysis the software provides JSON files that contain the coordinates of the features. Coordinates are provided for eye, fish contour, notochord , otoliths, yolk sac, pericard and swimbladder. Furthermore, pigment cells in the notochord area are detected. Additional features can be manually annotated. It is the aim of the software to provide the coordinates, which may then be analysed subsequently to identify and quantify changes in the morphology of zebrafish embryos.

FishInspector Logo

Cell or particle counting and scoring the percentage of stained objects

Description

This one example workflow from the Cell Profiler(CP)  Examples . CP is commonly used to count cells or other objects as well as percent-positives, by measuring the per-cell staining intensity. This pipeline shows how to do both of these tasks, and demonstrates how various modules may be used to accomplish the same result. 

In a few words, it used the IdentifyPrimaryObject module of CellProfiler to detect nuclei from a channel (e.g DAPI), then again the same module on another channel to detect another probe (e.g some particular histone)  .

Then objects (nuclei) are related to the second object (Histone), to create a parent child-relation ship: where nuclei can have histone has child. Nuclei are then filtered according to the property of having histone (positive) or not having histone (negtiveobject) related to them.  If needed, nuclei can be expanded in order to include touching object rather than object inside only.

The percentage of positive nuclei vs total number of nuclei can then be computed using the CalculateMath Module.

Positivepercentcell

Cell or particle Counting and scoring stained objects using CellProfiler

Description

This is a Jupyter notebook demonstrating the run of a code from IDR data sets by loading a CellProfiler Pipeline 

The example here is applied on real data set, but does not correspond to a biological question. It aims to demonstrate how to create a jupyter notebook to process online plates hosted in the IDR.

It reads the plate images from the IDR.

It loads the CellProfiler Pipeline and replace the reading modules used to read local files from this defaults pipeline by module allowing to read data remotely accessible.

It creates a CSV file and displays it in the notebook.

It makes some plot with Matplotlib.

 

jupyter

Orbit

Description

Orbit Image Analysis is a free open source software with the focus to quantify big images like whole slide scans.

It can connect to image servers, e.g. Omero.
Analysis can be done on your local computer or via scaleout functionality in a distrubuted computing environment like a Spark cluster.

Sophisticated image analysis algorithms incl. tissue quantification using machine learning, object segmentation and classification are build in. In addition a versatile API allows you to enhance Orbit and to run your own scripts.

Orbit

MAARS

Description

automated open-source image acquisition and on-the-fly analysis pipeline (initially developped for analysis of mitotic defects in fission yeast)

maars workflow from publication

 

maars

McLuigi

Description

Multicut workflow for large connectomics data. Using luigi for pipelining and caching processing steps. Most of the computations are done out-of-core using hdf5 as backend and implementations from nifty