A collection is a software that encapsulate a set of bioimage components and/or workflows.

Blender

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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.

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scikit-learn (sklearn)

Description

Scikit-learn (sklearn) is a python library used for machine learning. sklearn contains simple and efficient tools for data mining and data analysis. Modules and functions include those for classification, regression, clustering, dimensionality reduction, model selection and data preprocessing. Many people have contributed to sklearn (list of authors)

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Microscope autopilot

Description

AutoPilot is the open source project that hosts the general algorithm for fast and robust assessment of local image quality, an automated computational method for image-based mapping of the three-dimensional light-sheet geometry inside a fluorescently labeled biological specimen, and a general algorithm for data-driven optimization of the system state of light-sheet microscopes capable of multi-color imaging with multiple illumination and detection arms.

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FoCuS-point

Description

FoCuS-point is stand-alone software for TCSPC correlation and analysis. FoCuS-point utilizes advanced time-correlated single-photon counting (TCSPC) correlation algorithms along with time-gated filtering and innovative data visualization. The software has been designed to be highly user-friendly and is tailored to handle batches of data with tools designed to process files in bulk. FoCuS-point also includes advanced diffusion curve fitting algorithms which allow the parameters of the correlation functions and thus the kinetics of diffusion to be established quickly and efficiently.

FoCuS-scan

Description

FoCuS-scan is software for processing and analysis of large-scale scanning fluorescence correlation spectroscopy (FCS) data. FoCuS-scan can correlate data acquired on conventional turn-key confocal systems and in the form of xt image carpets.

BioCat

Description

Biocat is a java based software that allows to perform image classification or segmentation using machine learning. Several algorithm for the classification are available.

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acquiarium

Description

Acquiarium is open source software (GPL) for carrying out the common pipeline of many spatial cell studies using fluorescence microscopy. It addresses image capture, raw image correction, image segmentation, quantification of segmented objects and their spatial arrangement, volume rendering, and statistical evaluation.

It is focused on quantification of spatial properties of many objects and their mutual spatial relations in a collection of many 3D images. It can be used for analysis of a collection of 2D images or time lapse series of 2D or 3D images as well. It has a modular design and is extensible via plug-ins. It is a stand-alone, easy to install application written in C++ language. The GUI is written using cross-platform wxWidgets library.

Acquiarium functionalities diagram

BisQue

Description

Bisque (Bio-Image Semantic Query User Environment) : Store, visualize, organize and analyze images in the cloud. It also allow to run workflows using a set of deployed tools, such as CellProfiler, RootTipMultin Nuclear Tracker, Microtubule tracker etc...

Bisque was developed for the exchange and exploration of biological images.

The Bisque system supports several areas useful for imaging researchers from image capture to image analsysis and querying. The bisque system is centered around a database of images and metadata. Search and comparison of datasets by image data and content is supported. Novel semantic analyses are integrated into the system allowing high level semantic queries and comparison of image content.

  • Bisque is free and open-source
  • Flexible textual and graphical annotations
  • Cloud scalability: PBs of images, millions of annotations
  • Distributed storage: local, iRODS, S3
  • Integrated image analysis, high-throughput with Condor
  • Analysis in MATLAB, Python, Java+ImageJ
  • 100+ biological image formats
  • Very large 5D images (100+ GB)
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