MorphoNet Python API

Description

The Morphonet Python API provide an easy interface to interact directly with the MorphoNet server. Very useful to upload, download your dataset and superimpose on it any quantitative and quantitative informations.

MorphoNet

Description

MorphoNet is a novel concept of web-based morphodynamic browser to visualise and interact with complex datasets, with applications in research and teaching. 

MorphoNet offers a comprehensive palette of interactions to explore the structure, dynamics and variability of biological shapes and its connection to genetic expressions. 

By handling a broad range of natural or simulated morphological data, it fills a gap which has until now limited the quantitative understanding of morphodynamics and its genetic underpinnings by contributing to the creation of ever-growing morphological atlases.

Neuroglancer

Description

Web based viewer developped for google for very big data: 

Neuroglancer is a WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non axis-aligned) cross-sectional views of volumetric data, as well as 3-D meshes and line-segment based models (skeletons). The segmentation has to be done before loading the dataset, it is not done Inside the viewer.

This is not an official Google product.

It has among other the nice feature of beeing able to generate url for sharing a specific view.

Note that the only supported browser for now are 

  • Chrome >= 51
  • Firefox >= 46

 

Neuroglancer

Ikosa

Description

online image data management system which supports authenticated image upload, cloud-based storage, project-based management and viewing of standard and whole slide images. One can use different annotation tools to highlight important objects or areas within images. It is the first basic version and new features such as sharing for easy collaboration with your colleagues or first automated analysis applications based on artificial intelligence will be added soon.

Ikosa Portal: multi user image data management

Ikosa Prisma: Automated Image Analysis based on deep learning (available in summer 2019)

Free if limited to 2 users and 1 gigabyte, otherwise montly fees.

 

ikosa

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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bisque screenshot

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

ScientiFig

Description

ScientiFig is a free tool to help you create, format or reformat scientific figures. It comes either as a stand alonesoftware, either as a Fiji/IJ plugin.

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scientifig

Shiny - R package

Description

Shiny is an R package that makes it easy to build interactive web apps straight from R.

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FigureJ

Description

This plugin achieves easy creation of image figures for publications, reports, projects.

  • Easy-to-design interactive figure layout.

  • Visually assign image content to panels.

  • High-quality image scaling and rotation.

  • Easy and consistent panel labels and scale bars.

  • Each panel has it's original datasource's properties and tracks achieved image processing.

  • Save and re-open editable figures.

  • Export as standard image formats with textual description of each panel history.

Compared to Make montage, the plugin adds more flexibility to montage creation: Easy-to-design interactive figure layout. Visually assign image content to panels. High-quality image scaling and rotation. Easy and consistent panel labels and scale bars. Each panel has it's original data source's properties and tracks achieved image processing. Save and re-open editable figures. Export as standard image formats with textual description of each panel history. 

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FigureJ

MyTardis

Description

MyTardis is free and open-source data management software. It facilitates annotation, sharing and archiving of data and metadata collected from different modalities. It focuses on integration with scientific instruments, instrument facilities and research storage and computing infrastructure; to address the challenges of data storage, data access, collaboration and data publication. It is currently being used to capture data from areas such as optical microscopy, electron microscopy, medical imaging, protein crystallography, neutron and X-ray scattering, flow cytometry, genomics and proteomics. ## Key features * Easy instrument integration. * Discipline specific: MX, Imaging, Microscopy, Genomics ... * Wide range of data formats & supported instruments. * Secure cloud data storage & access. * Simple data sharing. * Researcher controlled data publishing. * APIs for programmatic access to data and metadata.

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