ITK Release 4/Microscopy: Difference between revisions
From KitwarePublic
Jump to navigationJump to search
(→Topics) |
|||
| Line 55: | Line 55: | ||
=== Topics === | === Topics === | ||
==== Challenges ==== | |||
* Large Images: Larger than local RAM | * Large Images: Larger than local RAM | ||
| Line 61: | Line 63: | ||
* Time | * Time | ||
* Many channels | * Many channels | ||
* Cropping M-Dimensional image into N-Dimensional image (e.g. 4D --> 3D) | |||
==== ==== | |||
Revision as of 17:10, 12 August 2010
Microscopy
Overview
Microscopy applications bring new challenges to ITK at many different levels
- Very Large datasets (TeraBytes)
- Examples:
- Brainbow dataset = 11000x15000x1000 x (RGB) = 500 Gigabytes for one 3D image.
- In-toto imaging dataset = 1000x1000x200x1000x5 ~ 500 GB for one imaging session (one organ)
- Data acquisition
- Today 100Gb / day
- Tomorrow 1 Tb / day
- 3D Stacks of 250Mb (8 seconds to acquire, 900 to deconvolve)
- J.J. Field Optics Express 2010.
- Examples:
- Temporal data (2D+t, 3D+t)
- Multiple Components
- Very large number of objects of interest per image
Technical Details
The toolkit needs
- More explicit representation of time and channels
- Management of multi-resolution datasets
- Management of multi-gigabyte datasets (TeraBytes being the standard to look for in 5 years)
- Richer set of classes for object representations
Reference Applications
Related Events
Tcons
August 12th 2010
Attendees
- Alex Gouaillard - Cosmo
- Sean Megason - Harvard
- Marc Niethammer -UNC
- Cory Quanmenn -UNC
- Russ Taylor - UNC
- Marcus Hanwell - Kitware
- Brad Lowekamp - NLM
- Luis Ibanez - Kitware
- Dominik Spinczyk - Silesian University
- Dhanannjay Deo - Kitware
Topics
Challenges
- Large Images: Larger than local RAM
- Pixel Types:
- Scalar, Vector, Tensor,
- Time
- Many channels
- Cropping M-Dimensional image into N-Dimensional image (e.g. 4D --> 3D)
