ChangeTracker:Lupus DBP - Revision history

Fedorov: /* Consequences for ChangeTracker */

2009-01-08T00:20:18Z

Consequences for ChangeTracker

Fedorov: /* Consequences for ChangeTracker */

2009-01-08T00:18:39Z

Consequences for ChangeTracker

Fedorov: /* Consequences for ChangeTracker */

2009-01-08T00:17:36Z

Consequences for ChangeTracker

Fedorov: /* Longitudinal lesion analysis for Lupus project */

2009-01-08T00:14:17Z

Longitudinal lesion analysis for Lupus project

Fedorov: /* Consequences for ChangeTracker */

2009-01-08T00:13:22Z

Consequences for ChangeTracker

Fedorov: /* Consequences for ChangeTracker */

2009-01-07T23:59:11Z

Consequences for ChangeTracker

Fedorov: /* Longitudinal lesion analysis for Lupus project */

2009-01-07T23:54:44Z

Longitudinal lesion analysis for Lupus project

Fedorov: New page: This page summarizes requirements for longitudinal lesion analysis for Lupus DBP, and resulting discussion on possible modifications required to [http://www.na-mic.org/Wiki/index.php/Chang...

2009-01-07T23:25:24Z

New page: This page summarizes requirements for longitudinal lesion analysis for Lupus DBP, and resulting discussion on possible modifications required to [http://www.na-mic.org/Wiki/index.php/Chang...

New page

This page summarizes requirements for longitudinal lesion analysis for Lupus DBP, and resulting discussion on possible modifications required to [http://www.na-mic.org/Wiki/index.php/ChangeTracker ChangeTracker] to make it possibly a more generic change analysis tool.

=Longitudinal lesion analysis for Lupus project=

Lupus DBP will face the need of analyzing multi-modal same-subject brain imaging data at 3+ timepoints in order to detect white matter lesions and analyze their progression. At each time point the following data will be available:

* T1
* T2
* FLAIR
* results of lesion classification: (1) labeled connected component filtering of classification/segmentation output + (2) per-label threshold information for each of the connected components

Essentially, pre-thresholded classification output is the per-pixel estimation of likelihood that the pixel belongs to the lesion. Threshold is defined on the per-lesion basis, since its selection depends on the tumor location and other properties.

Requirements to the analysis results are:

* ability to accept multiple lesions, but give control over per-lesion analysis
* ability to go through the available lesion modalities
* CompareView mode for rsults visualization
* naturally, no need for lesion detection functionality
* ability to adjust the classification threshold (per-lesion)
* distance-based coloring of the change results

@@ Line 34: / Line 34: @@
 * Step 2: Choose number of timepoints, and select with checkbox the types of data available at each timepoint
 * Step 3: Select input datasets for each timepoint
-* Step 4: Register timepoints to the same reference: ''should this be inside ChangeTracker, or the data has already been registered''?
+* Step 4 (transparent to the user): Register timepoints to the same reference (''should this be inside ChangeTracker, or the data has already been registered''?), automatically select an ROI for each lesion, so that tumors in all of the timepoints are within the ROI
 * Step 5: Create a CompareView layout with a strip for each timepoint, and provide a distance map for each timepoint ''i'' that is built in relation to the current binary segmentation at step ''(i-1)''. At the same time, in 3d viewer provide color-coded rendering of the growth/shrinking regions in relation to the initial segmentation.

@@ Line 35: / Line 35: @@
 * Step 3: Select input datasets for each timepoint
 * Step 4: Register timepoints to the same reference: ''should this be inside ChangeTracker, or the data has already been registered''?
-* Step 5: Create a CompareView layout with a strip for each timepoint, and provide a distance map for each timepoint ''i'' that is built in relation to the current binary segmentation at step ''(i-1)''.
+* Step 5: Create a CompareView layout with a strip for each timepoint, and provide a distance map for each timepoint ''i'' that is built in relation to the current binary segmentation at step ''(i-1)''. At the same time, in 3d viewer provide color-coded rendering of the growth/shrinking regions in relation to the initial segmentation.
 Application-specific modifications suggested for ChangeTracker: provide user controls to

@@ Line 32: / Line 32: @@
 * Step 1: Choose application: Meningioma/Lupus, from here, this is a description of the Lupus-related analysis
-* Step 2: Choose number of timepoints, and the select with checkbox the types of data available at each timepoint
+* Step 2: Choose number of timepoints, and select with checkbox the types of data available at each timepoint
-* Step 3: Register timepoints to the same reference: ''should this be inside ChangeTracker, or the data has already been registered''?
+* Step 3: Select input datasets for each timepoint
-* Step 4: Create a CompareView layout with a strip for each timepoint, and provide a distance map for each timepoint ''i'' that is built in relation to the current binary segmentation at step ''(i-1)''. The user controls allow to: (1) choose the specific lesion from the labeled set (''at timepoint i?''); (2) expose the threshold slider initialized to the initial setting of the threshold, so that user is able to adjust the threshold and see the compareview updated interactively; (3) give ability to save the scene and possibly per-lesion analysis with the specific parameter settings.
+* Step 4: Register timepoints to the same reference: ''should this be inside ChangeTracker, or the data has already been registered''?
 =Questions=
 * Are we targeting clinicians or researchers familiar with Slicer?

@@ Line 21: / Line 21: @@
 * distance-based coloring of the change results
 * ability to save/load analysis results
 =Consequences for ChangeTracker=

← Older revision		Revision as of 00:13, 8 January 2009
Line 31:		Line 31:

	* Step 1: Choose application: Meningioma/Lupus, from here, this is a description of the Lupus-related analysis		* Step 1: Choose application: Meningioma/Lupus, from here, this is a description of the Lupus-related analysis
−	* Step 2:	+	* Step 2: Choose number of timepoints, and the select with checkbox the types of data available at each timepoint
		+	* Step 3: Register timepoints to the same reference: ''should this be inside ChangeTracker, or the data has already been registered''?
		+	* Step 4: Create a CompareView layout with a strip for each timepoint, and provide a distance map for each timepoint ''i'' that is built in relation to the current binary segmentation at step ''(i-1)''. The user controls allow to: (1) choose the specific lesion from the labeled set (''at timepoint i?''); (2) expose the threshold slider initialized to the initial setting of the threshold, so that user is able to adjust the threshold and see the compareview updated interactively; (3) give ability to save the scene and possibly per-lesion analysis with the specific parameter settings.
		+
		+	=Questions=
		+	* Are we targeting clinicians or researchers familiar with Slicer?

← Older revision		Revision as of 23:59, 7 January 2009
Line 30:		Line 30:
	Mock-up workflow for Lupus analysis:		Mock-up workflow for Lupus analysis:

−	* Step 1	+	* Step 1: Choose application: Meningioma/Lupus, from here, this is a description of the Lupus-related analysis
		+	* Step 2:

@@ Line 18: / Line 18: @@
 * CompareView mode for rsults visualization
 * naturally, no need for lesion detection functionality
-* ability to adjust the classification threshold (per-lesion)
+* ability to adjust the classification threshold (per-lesion): ''should this be done separately for each timepoint?''
 * distance-based coloring of the change results