2017 Winter Project Week/ProstateSectorSegmentation - Revision history

Ameyer: /* Project Description */

2017-01-13T15:52:14Z

Project Description

2017-01-13T15:51:25Z

Project Description

2017-01-13T15:49:31Z

Project Description

2017-01-13T15:45:33Z

2017-01-13T14:33:48Z

Project Description

2017-01-09T18:20:28Z

2017-01-09T18:00:13Z

Key Investigators

2017-01-08T15:22:31Z

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 <!-- Progress and Next steps bullet points (fill out at the end of project week) -->
 * Creation of 3 zone segmentations of the prostate (different volumes)
-* Prediction of zones for specific locations in ProstateX challenge with Deep Learning is in progress
+* Prediction of zones for specific locations in ProstateX dataset with Deep Learning is in progress
 * Next Steps: Create 3D model with higher resolution. Atlas based segmentation on more publicly available data.
 |}

@@ Line 39: / Line 39: @@
 <!-- Progress and Next steps bullet points (fill out at the end of project week) -->
 * Creation of 3 zone segmentations of the prostate (different volumes)
-* Prediction of zones in ProstateX challenge with Deep Learning is in progress
+* Prediction of zones for specific locations in ProstateX challenge with Deep Learning is in progress
 * Next Steps: Create 3D model with higher resolution. Atlas based segmentation on more publicly available data.
 |}

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 * Test with ProstateX challenge dataset (where zones of findings are given) to predict the zone with Deep Learning
 * if more training data is available: deep learning for an automatic sector segmentation
-* (Try (model-based) segmentation approach (costs for segmentation optimization can be derived for example from supervised classification of the gland tissue). The shape of individual sector models could be used as segmentation prior)
+* Try atlas-based segmentation approach to map zone segmentations on more datasets
@@ Line 40: / Line 40: @@
 * Creation of 3 zone segmentations of the prostate (different volumes)
 * Prediction of zones in ProstateX challenge with Deep Learning is in progress
 |}
 ==Background and References==
 <!-- Use this space for information that may help people better understand your project, like links to papers, source code, or data -->

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 File:Prostate_MRI.PNG|Transversal slice of Prostate MRI.
 File:SectorMap_Prostate.PNG|Sector Map according to PI-RADS v2.
 </gallery>

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 * Generation/ Refinement of ground truth data
 * Creation of a 3D sector model
-* Initialization of segmentation with user interaction or atlas-based segmentation (in order to decrease search space)
+* Test with ProstateX challenge dataset (where zones of findings are given) to predict the zone with Deep Learning
-* Try (model-based) segmentation approach (costs for segmentation optimization can be derived for example from supervised classification of the gland tissue). The shape of individual sector models could be used as segmentation prior
+* if more training data is available: deep learning for an automatic sector segmentation
-* if more training data is available: deep learning for a better cost generation or for an automatic sector segmentation
+* (Try (model-based) segmentation approach (costs for segmentation optimization can be derived for example from supervised classification of the gland tissue). The shape of individual sector models could be used as segmentation prior)
+|
 <!-- Progress and Next steps bullet points (fill out at the end of project week) -->
+* Creation of 3 zone segmentations of the prostate (different volumes)
 |}
 ==Background and References==
 <!-- Use this space for information that may help people better understand your project, like links to papers, source code, or data -->

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 * Alireza Mehrtash, BWH
 * Christian Hansen, University of Magdeburg (Germany)
 ==Project Description==

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 * Anneke Meyer, University of Magdeburg (Germany)
 * Andrey Fedorov, BWH
 ==Project Description==

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 Image:PW-Winter2017.png|link=2017_Winter_Project_Week#Projects|[[2017_Winter_Project_Week#Projects|Projects List]]
 <!-- Use the "Upload file" link on the left and then add a line to this list like "File:MyAlgorithmScreenshot.png" -->
 </gallery>