Difference between revisions of "2014 Summer Project Week:mipiX"

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This is a new approach for fast and effective visualization of large image collections in population studies. The key insight is to collapse inherently high-dimensional imaging data onto an interactive two-dimensional canvas native to a computer screen in a way that enables intuitive browsing of the image data. Increasingly, medical image computing research involves exploring large image sets with high intrinsic dimensionality. This includes three dimensions for each medical volume, and many meta-dimensions such as subject index, modality type in multimodal studies, time in longitudinal studies, or parameter choice in parameter sweep experiments. Current visualization tools generally display one or few 2D slices or 3D renderings at a time, and do not provide a natural way to explore the meta-dimensions.
 
This is a new approach for fast and effective visualization of large image collections in population studies. The key insight is to collapse inherently high-dimensional imaging data onto an interactive two-dimensional canvas native to a computer screen in a way that enables intuitive browsing of the image data. Increasingly, medical image computing research involves exploring large image sets with high intrinsic dimensionality. This includes three dimensions for each medical volume, and many meta-dimensions such as subject index, modality type in multimodal studies, time in longitudinal studies, or parameter choice in parameter sweep experiments. Current visualization tools generally display one or few 2D slices or 3D renderings at a time, and do not provide a natural way to explore the meta-dimensions.
  
[http://goo.gl/EQ9iLt Lupus Dataset Demo]
+
[http://www.mit.edu/~adalca/tipiXnightly/?path=http://www.mit.edu/~adalca/tipiX/imageSets/lupus/lupus_$_$.jpg&nDims=2&xBins=5&yBins=56&debug=true Lupus Dataset Demo]
  
 
[http://mipix.fotozygous.com/demo/?path=http://mipix.fotozygous.com/exdata/adnisel/crop_ds_$.nii.gz&nDims=1&xBins=20&crossOrigin=1&debug=1# ADNI Demo]
 
[http://mipix.fotozygous.com/demo/?path=http://mipix.fotozygous.com/exdata/adnisel/crop_ds_$.nii.gz&nDims=1&xBins=20&crossOrigin=1&debug=1# ADNI Demo]

Revision as of 16:08, 23 June 2014

Home < 2014 Summer Project Week:mipiX

Key Investigators

- Adrian Dalca, Ramesh Sridharan, Erjona Topalli, Polina Golland, MIT

Project Description

This is a new approach for fast and effective visualization of large image collections in population studies. The key insight is to collapse inherently high-dimensional imaging data onto an interactive two-dimensional canvas native to a computer screen in a way that enables intuitive browsing of the image data. Increasingly, medical image computing research involves exploring large image sets with high intrinsic dimensionality. This includes three dimensions for each medical volume, and many meta-dimensions such as subject index, modality type in multimodal studies, time in longitudinal studies, or parameter choice in parameter sweep experiments. Current visualization tools generally display one or few 2D slices or 3D renderings at a time, and do not provide a natural way to explore the meta-dimensions.

Lupus Dataset Demo

ADNI Demo

Objective

  • We intend to incorporate several new features into the tool, including the display of appropriate information about the volume and support for individual masks for each volume.

Approach, Plan

Progress