CS295J/Project Schedule:Steve - Revision history

Steven Gomez: /* How do analysts assess scan quality in MRI imaging? How does that inform workflow or tool design? */

2011-12-06T18:38:14Z

How do analysts assess scan quality in MRI imaging? How does that inform workflow or tool design?

← Older revision		Revision as of 18:38, 6 December 2011
Line 4:		Line 4:

	== How do analysts assess scan quality in MRI imaging? How does that inform workflow or tool design? ==		== How do analysts assess scan quality in MRI imaging? How does that inform workflow or tool design? ==
	~~Some directions~~:		Contributions (for proposal):
			* Demonstrated task analysis for brain science workflow.
			* Evaluation principle: demonstrated that Mechanical Turk works for these kinds of scientific graphical perception tasks.

			Future Direction:
	* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.		* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.

	* ''Crowdsourcing'': If we can separate QA into two process -- one of which requires little or no anatomical knowledge -- can we outsource the image-level assessment task to naive Turkers? How does their scoring compare to that of research assistants on a dataset of scans?

	== Project Schedule ==		== Project Schedule ==

Steven Gomez: /* Boards */

2011-12-06T17:38:55Z

Boards

← Older revision		Revision as of 17:38, 6 December 2011
Line 89:		Line 89:

	<center>		<center>
	<gallery widths="~~300px~~" heights="~~300px~~" caption="MTurk HIT Gallery">		<gallery widths="250px" heights="250px" caption="MTurk HIT Gallery">
	Image:Sample MRI Turk HIT.png \| Can we use Turkers to evaluate image quality in MRI scans? Nov 14, 2011		Image:Sample MRI Turk HIT.png \| Can we use Turkers to evaluate image quality in MRI scans? Nov 14, 2011
	Image:Sample_MRI_HIT_2.png \| The pilot HIT we tried on Mechanical Turk. Nov 28, 2011		Image:Sample_MRI_HIT_2.png \| The pilot HIT we tried on Mechanical Turk. Nov 28, 2011
			Image:Steveg_cs295j_pilot_results.png \| Pilot results from MTurk. Dec 5, 2011
	</gallery>		</gallery>
	</center>		</center>

Steven Gomez: /* Boards */

2011-11-29T17:53:05Z

Boards

← Older revision		Revision as of 17:53, 29 November 2011
Line 91:		Line 91:
	<gallery widths="300px" heights="300px" caption="MTurk HIT Gallery">		<gallery widths="300px" heights="300px" caption="MTurk HIT Gallery">
	Image:Sample MRI Turk HIT.png \| Can we use Turkers to evaluate image quality in MRI scans? Nov 14, 2011		Image:Sample MRI Turk HIT.png \| Can we use Turkers to evaluate image quality in MRI scans? Nov 14, 2011
			Image:Sample_MRI_HIT_2.png \| The pilot HIT we tried on Mechanical Turk. Nov 28, 2011
	</gallery>		</gallery>
	</center>		</center>

Steven Gomez: /* Report Drafts */

2011-11-29T17:45:44Z

Report Drafts

← Older revision		Revision as of 17:45, 29 November 2011
Line 29:		Line 29:
	* [[media:6nov2011-cs295j-report-steveg.pdf]], 19:13, 6 November 2011 (EST)		* [[media:6nov2011-cs295j-report-steveg.pdf]], 19:13, 6 November 2011 (EST)
	* [[media:22nov2011-cs295j-report-steveg.pdf]], 12:56, 22 November 2011 (EST)		* [[media:22nov2011-cs295j-report-steveg.pdf]], 12:56, 22 November 2011 (EST)
			* [[media:29nov2011-cs295j-report-steveg.pdf]], 12:45, 29 November 2011 (EST)

	== Data and Resource Links ==		== Data and Resource Links ==

Steven Gomez: /* Boards */

2011-11-25T07:17:10Z

Boards

← Older revision		Revision as of 07:17, 25 November 2011
Line 76:		Line 76:

	<center>		<center>
	<gallery widths="~~300px~~" heights="~~250px~~" caption="Poster sketches and in-class critiques ">		<gallery widths="200px" heights="150px" caption="Poster sketches and in-class critiques ">
			Image:Steve_Poster_22_Nov_2011.jpg \| Nov 22, 2011
	Image:Steve_Poster_20_Oct_2011.JPG \| Oct 20, 2011		Image:Steve_Poster_20_Oct_2011.JPG \| Oct 20, 2011
	Image:Steve_Poster_18_Oct_2011.JPG \| Oct 18, 2011		Image:Steve_Poster_18_Oct_2011.JPG \| Oct 18, 2011
Line 87:		Line 88:

	<center>		<center>
	<gallery widths="~~400px~~" heights="~~400px~~" caption="MTurk HIT Gallery">		<gallery widths="300px" heights="300px" caption="MTurk HIT Gallery">
	Image:Sample MRI Turk HIT.png \| Can we use Turkers to evaluate image quality in MRI scans? Nov 14, 2011		Image:Sample MRI Turk HIT.png \| Can we use Turkers to evaluate image quality in MRI scans? Nov 14, 2011
	</gallery>		</gallery>
	</center>		</center>

Steven Gomez: /* How do analysts assess scan quality in MRI imaging? How does that inform tool design? */

2011-11-22T20:02:44Z

How do analysts assess scan quality in MRI imaging? How does that inform tool design?

← Older revision		Revision as of 20:02, 22 November 2011
Line 3:		Line 3:
	This project explores the types of QA involved in accepting or rejecting a scan used for brain research. We can think of '''multiple scales''' of QA that usually happen. What we are finding is that there is often an '''image-based QA''', which does not require interpreting the underlying brain data, and a '''semantics-based QA''' process that may happen later in the research process.		This project explores the types of QA involved in accepting or rejecting a scan used for brain research. We can think of '''multiple scales''' of QA that usually happen. What we are finding is that there is often an '''image-based QA''', which does not require interpreting the underlying brain data, and a '''semantics-based QA''' process that may happen later in the research process.

	== How do analysts assess scan quality in MRI imaging? How does that inform tool design? ==		== How do analysts assess scan quality in MRI imaging? How does that inform workflow or tool design? ==
	Some directions:		Some directions:
	* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.		* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.

Steven Gomez: /* Report Drafts */

2011-11-22T17:56:27Z

Report Drafts

← Older revision		Revision as of 17:56, 22 November 2011
Line 28:		Line 28:

	* [[media:6nov2011-cs295j-report-steveg.pdf]], 19:13, 6 November 2011 (EST)		* [[media:6nov2011-cs295j-report-steveg.pdf]], 19:13, 6 November 2011 (EST)
			* [[media:22nov2011-cs295j-report-steveg.pdf]], 12:56, 22 November 2011 (EST)

	== Data and Resource Links ==		== Data and Resource Links ==

Steven Gomez: /* How do analysts assess scan quality in MRI imaging? How does that inform tool design? */

2011-11-15T20:46:38Z

How do analysts assess scan quality in MRI imaging? How does that inform tool design?

← Older revision		Revision as of 20:46, 15 November 2011
Line 3:		Line 3:
	This project explores the types of QA involved in accepting or rejecting a scan used for brain research. We can think of '''multiple scales''' of QA that usually happen. What we are finding is that there is often an '''image-based QA''', which does not require interpreting the underlying brain data, and a '''semantics-based QA''' process that may happen later in the research process.		This project explores the types of QA involved in accepting or rejecting a scan used for brain research. We can think of '''multiple scales''' of QA that usually happen. What we are finding is that there is often an '''image-based QA''', which does not require interpreting the underlying brain data, and a '''semantics-based QA''' process that may happen later in the research process.

	= How do analysts assess scan quality in MRI imaging? How does that inform tool design? =		== How do analysts assess scan quality in MRI imaging? How does that inform tool design? ==
	Some directions:		Some directions:
	* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.		* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.

Steven Gomez at 20:45, 15 November 2011

2011-11-15T20:45:52Z

← Older revision		Revision as of 20:45, 15 November 2011
Line 1:		Line 1:
			Quality assessment (QA) is an important part of the quality control (QC) process. MRI and other imaging methods sometimes have issues like motion artifacts (i.e., if a subject moves during a scan), low signal-to-noise ratio (SNR), or contrast problems that complicate the process of drawing insights from these images. In a perfect world, a given pixel or voxel has an intensity created only by the underlying brain data, but this is not always the case.

			This project explores the types of QA involved in accepting or rejecting a scan used for brain research. We can think of '''multiple scales''' of QA that usually happen. What we are finding is that there is often an '''image-based QA''', which does not require interpreting the underlying brain data, and a '''semantics-based QA''' process that may happen later in the research process.

	= How do analysts assess scan quality in MRI imaging? How does that inform tool design? =		= How do analysts assess scan quality in MRI imaging? How does that inform tool design? =
	Some directions:		Some directions:

Steven Gomez: /* How do analysts assess scan quality in MRI imaging? How does that inform tool design? */

2011-11-15T20:45:31Z

How do analysts assess scan quality in MRI imaging? How does that inform tool design?

← Older revision		Revision as of 20:45, 15 November 2011
Line 1:		Line 1:
	= How do analysts assess scan quality in MRI imaging? How does that inform tool design? =		= How do analysts assess scan quality in MRI imaging? How does that inform tool design? =

	Quality assessment (QA) is an important part of the quality control (QC) process. MRI and other imaging methods sometimes have issues like motion artifacts (i.e., if a subject moves during a scan), low signal-to-noise ratio (SNR), or contrast problems that complicate the process of drawing insights from these images. In a perfect world, a given pixel or voxel has an intensity created only by the underlying brain data, but this is not always the case.

	This project explores the types of QA involved in accepting or rejecting a scan used for brain research. We can think of '''multiple scales''' of QA that usually happen. What we are finding is that there is often an '''image-based QA''', which does not require interpreting the underlying brain data, and a '''semantics-based QA''' process that may happen later in the research process.

	Some directions:		Some directions:
	* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.		* ''Trust'': Brain imaging inherently presents uncertain data to the researcher/analyst. Part of that uncertainty comes from the imaging method (see the artifacts discussion above). Another part comes from the fact that there is usually no reference data to verify what analysts see (unless the brain is dissected). In cases where the brain structure may be changed due to a clinical case, analysts may not even know a priori what they're looking for. The 'trust' question comes because at some point in the analysis process, the analyst must trust that the tool is providing a correct visual mapping of the underlying data. Suppose a tool interface has an 'ugly' and 'pretty' condition; we hypothesize that the analyst is more likely to trust the pretty interface than the ugly one, and that this might result is spending less time checking for artifacts or otherwise verifying what s/he is seeing.