Difference between revisions of "2017 Winter Project Week/Diffusely abnormal white matter segmentation with 3d U-net"
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− | * | + | * Diffusely abnormal white matter (“DAWM”) are fuzzy-bordered areas of subtly increased signal |
− | Diffusely abnormal white matter (“DAWM”) are fuzzy-bordered areas of subtly increased signal | ||
intensity on proton density or T2-weighted images. These abnormalities have been referred to as dirty white matter or dirty-appearing white matter. The goal is to develop an automated system that accurately segments diffusely abnormal white matter. | intensity on proton density or T2-weighted images. These abnormalities have been referred to as dirty white matter or dirty-appearing white matter. The goal is to develop an automated system that accurately segments diffusely abnormal white matter. | ||
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− | * | + | * The 3D-Unet architecture is implemented in Lasagne and it is currently being trained. |
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Latest revision as of 15:29, 6 June 2017
Home < 2017 Winter Project Week < Diffusely abnormal white matter segmentation with 3d U-netKey Investigators
- Mohsen Ghafoorian (BWH, Radboud University)
- Bram Platel (Radboud University)
- Sandy Wells (BWH)
- Tina Kapur (BWH)
- Charles Guttmann (BWH)
- Hans Meine (Univ. Bremen, Fh MEVIS)
Project Description
Objective | Approach and Plan | Progress and Next Steps |
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intensity on proton density or T2-weighted images. These abnormalities have been referred to as dirty white matter or dirty-appearing white matter. The goal is to develop an automated system that accurately segments diffusely abnormal white matter. |
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