2014 Summer Project Week:Atlas Selection - Revision history

Kanglin: /* Key Investigators */

2014-06-27T14:22:13Z

Key Investigators

Kanglin: /* Project Results */

2014-06-26T20:27:00Z

Project Results

Kanglin: /* Project Description */

2014-06-26T20:25:53Z

Project Description

Kanglin: /* Project Results */

2014-06-26T20:16:44Z

Project Results

Kanglin: /* Project Description */

2014-06-26T20:15:45Z

Project Description

Kanglin: /* Project Description */

2014-06-26T19:57:10Z

Project Description

Kanglin: /* Project Results */

2014-06-26T19:54:37Z

Project Results

Kanglin: /* Project Results */

2014-06-26T19:51:39Z

Project Results

Kanglin: /* Project Results */

2014-06-26T19:48:05Z

Project Results

Kanglin: /* Project Description */

2014-06-26T19:18:06Z

Project Description

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 ==Key Investigators==
 * Kanglin Chen (Fraunhofer MEVIS Germany)
-* Gregory Sharp (Harvard Medical School)
+* Gregory Sharp (MGH)
 ==Project Description==

@@ Line 42: / Line 42: @@
 ==Project Results==
-* We have 20 datasets for H&N including lung and chest. For example
+* We have 20 datasets for H&N including lungs and chests. For example
 [[File:Axial_orig_image.png|||400px|||]] [[File:Coronal_orig_image.png|||400px|||]] [[File:Sagittal_orig_image.png|||400px|||]]
-* We select the ROI of every data excluding lung and chest. For each data there exist the segmentations of brain stem, left and right parotids. For example
+* We selected the ROI of every data excluding lung and chest. For each data there exist the segmentations of brain stem, left and right parotids. For example
 [[File:Axial_roi_image.png|||400px|||]] [[File:Coronal_roi_image.png|||400px|||]] [[File:Sagittal_roi_image.png|||400px|||]]
 * We constructed the average atlas of 20 datasets of ROI, and merged the segmentations into the average atlas. These segmentations are the probability maps of

@@ Line 15: / Line 15: @@
 Atlas selection is used for image segmentation. Normally, a single image is chosen as an atlas and the structures are segmented manually.
 The segmentation is transferred to patient data using non-linear image registration. However, image segmentation based on single image atlas is
-not stable. To improve the segmentation, we can select multiple images, which are suitable for image segmentation and after registration we
+not stable. To improve the segmentation, we can select multiple images, which are suitable for image segmentation. After registration we
-can merge the segmentations to a final one. An idea to improve the atlas selection process is that we take advantage of using an average atlas.
+can merge the segmentations to a final one. An idea to improve atlas selection process lies on that we take advantage of using an average atlas.
-The procedure of atlas selection used for image segmentation is defined as follows:
+The procedure of atlas selection using an average atlas for image segmentation is defined as follows:
-* Construct an atlas based on a database
+* Construct an average atlas based on a database
-* Every image of the database is aligned to the atlas after the average atlas construction.
+* Every image of the database is aligned to the average atlas after the atlas construction.
 * Register the average atlas to a new image and transfer the database and their segmentations to the new image.
 * Compare the transformed database with the new image in the ROI and select some well-matched images with respected to some distance measure, e.g. MI, CC, NGF.
 * Merge the segmentations of these well-matched images to a final one based on e.g. weighted voting or STAPLE algorithm.
-The crucial step of atlas selection is the average atlas construction. The focus of this project lies on  the construction of  an average atlas using 3D datasets and validate the average atlas with the inspection of segmentations.
+The crucial step of atlas selection is the average atlas construction. The focus of this project lies on the construction of  an average atlas using 3D datasets and validate the average atlas with the inspection of segmentations.
 </div>
 <div style="width: 27%; float: left; padding-right: 3%;">
 <h3>Approach, Plan</h3>
-The average atlas construction modeling and algorithm are based on non-linear image registration and reconstruction.
+The modeling and algorithm of the average atlas construction are based on non-linear image registration and reconstruction.
 The algorithm does not depend on selecting a particular image as the template and the solution is optimal with respect to a minimization problem.
-In this project we want to construct an atlas using a database with segmentations and validate the average atlas by the visual inspection of merged segmentations.
+In this project we want to construct the average atlas using a database with segmentations and validate the average atlas by the visual inspection of merged segmentations.
 </div>
 <div style="width: 27%; float: left; padding-right: 3%;">
 <h3>Progress</h3>
-* We developed algorithms for the average atlas construction, finished programming in Matlab. and visualization in Slicer.
+* We developed algorithms for the average atlas construction, finished programming in Matlab.
 * We constructed the average atlas of 20 datasets for H&N and merged segmentations into the average atlas.
-* We visualized the average atlas and its probability maps of segmentations in the Slicer.
+* We visualized the average atlas and its probability maps of segmentations in Slicer.
 </div>
 </div>

@@ Line 46: / Line 46: @@
 * We select the ROI of every data excluding lung and chest. For each data there exist the segmentations of brain stem, left and right parotids. For example
 [[File:Axial_roi_image.png|||400px|||]] [[File:Coronal_roi_image.png|||400px|||]] [[File:Sagittal_roi_image.png|||400px|||]]
-* We constructed an atlas from 20 datasets of ROI, and merged the segmentations. These segmentations are probability maps of
+* We constructed the average atlas of 20 datasets of ROI, and merged the segmentations into the average atlas. These segmentations are the probability maps of
 brain stem, left and right parotids.
 [[File:Axial_atlas_image.png|||400px|||]] [[File:Coronal_atlas_image.png|||400px|||]] [[File:Sagittal_atlas_image.png|||400px|||]]

@@ Line 14: / Line 14: @@
 <h3>Objective</h3>
 Atlas selection is used for image segmentation. Normally, a single image is chosen as an atlas and the structures are segmented manually.
-The segmentation is transferred to patient data using non-linear image registration. However, image segmentation based on single atlas is
+The segmentation is transferred to patient data using non-linear image registration. However, image segmentation based on single image atlas is
-not stable. To improve the segmentation we can select multiple images, which are suitable for image segmentation and after registration we
+not stable. To improve the segmentation, we can select multiple images, which are suitable for image segmentation and after registration we
-can merge the segmentations to a final one. The selection of these images can be based on an atlas. The procedure defines in the following steps:
+can merge the segmentations to a final one. An idea to improve the atlas selection process is that we take advantage of using an average atlas.
 * Construct an atlas based on a database
-* Every image of the database is aligned to the atlas after atlas construction
+* Every image of the database is aligned to the atlas after the average atlas construction.
-* Register the atlas to a new image and transfer the database to the new image
+* Register the average atlas to a new image and transfer the database and their segmentations to the new image.
-* Compare the transformed database to the new image and select some well-matched images
+* Compare the transformed database with the new image in the ROI and select some well-matched images with respected to some distance measure, e.g. MI, CC, NGF.
-* Merge the segmentations of these images to a final one based on e.g. "weighted voting" or STAPLE algorithms
+* Merge the segmentations of these well-matched images to a final one based on e.g. weighted voting or STAPLE algorithm.
-The crucial step of atlas selection is atlas construction and the focus of this project is to construct an atlas and validate the atlas using segmentation.
+The crucial step of atlas selection is the average atlas construction. The focus of this project lies on  the construction of  an average atlas using 3D datasets and validate the average atlas with the inspection of segmentations.
 </div>
 <div style="width: 27%; float: left; padding-right: 3%;">
 <h3>Approach, Plan</h3>
-An average atlas construction is based on image registration and reconstruction. We plan to construct the average atlas with merged segmentation
+The average atlas construction modeling and algorithm are based on non-linear image registration and reconstruction.
-using real 3D datasets and validate them.
+The algorithm does not depend on selecting a particular image as the template and the solution is optimal with respect to a minimization problem.
 </div>
 <div style="width: 27%; float: left; padding-right: 3%;">
 <h3>Progress</h3>
-* We developed algorithms for atlas construction, programming in Matlab and visualization in Slicer.
+* We developed algorithms for the average atlas construction, finished programming in Matlab. and visualization in Slicer.
-* We constructed an atlas of 40 datasets for H&N and merged segmentations into the atlas.
+* We constructed the average atlas of 20 datasets for H&N and merged segmentations into the average atlas.
 </div>
 </div>

@@ Line 36: / Line 36: @@
 ==Project Results==
-* Datasets
+* We have 20 datasets for H&N including lung and chest. Example:
 [[File:Axial_orig_image.png|||400px|||]] [[File:Coronal_orig_image.png|||400px|||]] [[File:Sagittal_orig_image.png|||400px|||]]
-* ROI of datasets
+* We select the ROI of every data excluding lung and chest. Example
 [[File:Axial_roi_image.png|||400px|||]] [[File:Coronal_roi_image.png|||400px|||]] [[File:Sagittal_roi_image.png|||400px|||]]
 * Constructed atlas
 [[File:Axial_atlas_image.png|||400px|||]] [[File:Coronal_atlas_image.png|||400px|||]] [[File:Sagittal_atlas_image.png|||400px|||]]