Fraudulent Version.pdf

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🔗 Source: people.csail.mit.edu
📊 Size: 272 KB
📄 Pages: 10 pages
⬇️ Downloads: 122

Summary

A nonparametric, probabilistic model for automatic segmentation of medical images is proposed, using a training set of images and corresponding label maps. The model relies on pairwise registrations between the test image and individual training images, transferring training labels to the test image and fusing them to compute the final segmentation. The framework allows for comparison of different label fusion algorithms and yields more accurate segmentation than existing methods, including Free Surfer. Experiments on brain MRI scans demonstrate the model's ability to detect hippocampus volume changes in studies of aging and Alzheimer's Disease.

Description

A nonparametric, probabilistic model for automatic segmentation of medical images is proposed, using a training set of images and corresponding label maps.

Technical Information

  • File Format: PDF
  • File Size: 272 KB
  • Pages: 10
  • Language: EN
  • Total Downloads: 122
  • Last Updated: 2 hours ago

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