rOMERO-gateway

Description

R wrapper around the OMERO Java Gateway, to enable access to OMERO via R using rJava

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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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Openimadis

Description

OpenImadis stands for Open Image Discovery: A platform for Image Life Cycle Management. It was previously called CID iManage (for Curie Image Database).

No image data conversions, no duplication.

- Uploads data to a secure server in the original format

- Unique id for data

Supports sharing and collaboration with access control

- Allows users to upload, view, update or download data based on their access privileges

Supports multiple ways of attaching meta-information

- Annotations, comments and file attachments

-Analysis results as query-able visual objects

Supports Archiving (data moving to another long-term storage but still searchable)

Facilitates custom visualization and analysis

- Access data from preferred analysis and visualization tools

- Access relevant bits of data to build efficient web and mobile application

Facilitate easy access to analysis and visualization applications hosted on other servers

- Run analysis on dedicated compute clusters

- Access applications hosted and published by other users

Highly Scalable

- Supports on-the-fly addition of server nodes to scale concurrent usage

 

 

openImadis

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.

Drishti

Description

Drishti (from Sanskrit  word for "vision" or "insight") is a multi-platform, open-source volume-exploration and presentation tool. Written for visualizing tomography data, electron-microscopy data and the like.

Drishti

Luigi

Description

Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else.

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BigStitcher

Description

The BigStitcher is a software package that allows simple and efficient alignment of multi-tile and multi-angle image datasets, for example acquired by lightsheet, widefield or confocal microscopes. The software supports images of almost arbitrary size ranging from very small images up to volumes in the range of many terabytes, which are for example produced when acquiring cleared tissue samples with lightsheet microscopy.

Cytomine

Description

Cytomine is a rich internet application using modern web and distributed technologies (Grails, HTML/CSS/Javascript, Docker), databases (spatial SQL and NoSQL), and machine learning (tree-based approaches with random subwindows) to foster active and distributed collaboration and ease large-scale image exploitation.

It provides remote and collaborative principles, rely on data models that allow to easily organize and semantically annotate imaging datasets in a standardized way (using user-defined ontologies associated to regions of interest), efficiently support high-resolution multi-gigapixel images (incl. major digital scanner image formats), and provide mechanisms to readily proofread and share image quantifications produced by any image recognition algorithms.

By emphasizing collaborative principles, the aim of Cytomine is to accelerate scientific progress and to significantly promote image data accessibility and reusability. Cytomine allows to break common practices in this domain where imaging datasets, quantification results, and associated knowledge are still often stored and analyzed within the restricted circle of a specific laboratory.

This software is e.g. being used by life scientists in to help them better evaluate drug treatments or understand biological processes directly from whole-slide tissue images (digital histology), by pathologists to share and ease their diagnosis, and by teachers and students for pathology training purposes. It is also used in various microscopy applications.

Cytomine can be used as a stand-alone application (e.g. on a laptop) or on larger servers for collaborative works.

Cytomine implements object classification, image segmentation, content-based image retrieval, object counting, and interest point detection algorithms using machine learning.

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Phenoripper

Description

An easy to use, image analysis software package that enables rapid exploration and interpretation of microscopy data.

PhenoBrowser

OMERO

Description

OMERO is a free, open source image management software. It is client-server based system which supports 5D images, including big images and high-content screening data. Data are stored on a server using relational database. They are accessed using 3 main clients, a desktop client, a web client and a command line tool. There are bindings from OMERO to other image analysis packages, like FLIMfit, OMERO.searcher. The data in OMERO are organized in groups. A user can be a member of one or more groups. This groups can be collaborative or private, there are 4 levels of permissions to access/edit/annotate/delete the data of other users.

The package is supported not only by community forums, but also by a dedicated team which helps users to solve their problems and deals with the bugs submitted via error submission system.

Strengths

Open source, scalable software, Supports diverse sets of imaging applications and domains (EM,LM, HCS, DigPath) Cross-platform, Java-based application, API support for Java, Python, C++, Django, On-line Forums, Automatic QA and upload of software errors Multi-dimensional images, Web access, Free Demo-server accounts

Limitations

Enterprise-scale software, so complex install, requires expertise, Actively developing API, Python scripts and functions still developing

Omero