2007 APR NIH Questions and Answers - Revision history

Tkapur at 17:12, 22 August 2007

2007-08-22T17:12:06Z

Tkapur at 17:11, 22 August 2007

2007-08-22T17:11:02Z

Tkapur at 17:10, 22 August 2007

2007-08-22T17:10:47Z

Tkapur: /* The weakest and probably most difficult parts of the NA-MIC effort are validation and comparison across algorithms. The validation that is being performed needs to be more systematic and coordinate

2007-08-21T17:04:01Z

/* The weakest and probably most difficult parts of the NA-MIC effort are validation and comparison across algorithms. The validation that is being performed needs to be more systematic and coordinate

Tkapur: /* References */

2007-08-21T16:54:17Z

References

Tkapur: /* References */

2007-08-21T15:57:55Z

References

Tkapur: /* The weakest and probably most difficult parts of the NA-MIC effort are validation and comparison across algorithms. The validation that is being performed needs to be more systematic and coordinate

2007-08-21T15:53:37Z

Whitaker: /* What is the rational for choosing a particular method (tool) for solving a particular problem (DBP)? Why was a particular method (tool) chosen for development? Is there a listing of which tool might be helpful for which family of problems? Pleas

2007-08-21T15:20:43Z

/* What is the rational for choosing a particular method (tool) for solving a particular problem (DBP)? Why was a particular method (tool) chosen for development? Is there a listing of which tool might be helpful for which family of problems? Pleas

Whitaker: /* To what problems is DTI best applicable? Is it applicable across age ranges?('''Ross Whitaker''') */

2007-08-21T15:20:07Z

To what problems is DTI best applicable? Is it applicable across age ranges?('''Ross Whitaker''')

Whitaker: /* The weakest and probably most difficult parts of the NA-MIC effort are validation and comparison across algorithms. The validation that is being performed needs to be more systematic and coordinated like the tractography validation effort. Perhaps

2007-08-21T14:39:15Z

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	[[Media:2007_NAMIC_APR_NIH_Questions_and_Answers.doc\|2007 NA-MIC APR Q&A (MS Word)]] - this is the final document sent to the NIH.		[[Media:2007_NAMIC_APR_NIH_Questions_and_Answers.doc\|2007 NA-MIC APR Q&A (MS Word)]] - this is the final document sent to the NIH.

← Older revision		Revision as of 17:11, 22 August 2007
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−		+	[[Media:2007_NAMIC_APR_NIH_Questions_and_Answers.doc\|2007 NA-MIC APR Q&A (MS Word)]] - this is the final document sent to the NIH.
−	[[Media:2007_NAMIC_APR_NIH_Questions_and_Answers.doc\|2007 NA-MIC APR Q&A (MS Word)]]

← Older revision		Revision as of 17:10, 22 August 2007
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		+	[[Media:2007_NAMIC_APR_NIH_Questions_and_Answers.doc\|2007 NA-MIC APR Q&A (MS Word)]]
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	In a letter from Grace Peng, dated July 31 2007 the center team asks the following questions:		In a letter from Grace Peng, dated July 31 2007 the center team asks the following questions:

@@ Line 16: / Line 16: @@
 and Hamilton Jacobi formulations [11, 12]. Courage et al. examine
 different methods of finding fiber correspondences [13] in order to be
-able to do statistics between fibers. Indeed, these comparisons are an
+able to do statistics between fibers. Indeed, these comparisons are a
 necessary requirement for publishing new methodologies. Likewise, in
 the shape analysis work, Styner at al. [14] have compared alternative
@@ Line 48: / Line 48: @@
 measures to compare different methods for the analysis of DTI. In a
 recent planning meeting (phone conference) we agreed to invite a
-selection of prominent nonNA-MIC participants, who we think can come
+selection of prominent non NA-MIC participants, who we think can come
 to the table with very useful and competitive DTI analysis methods. We
 believe this workshop, and the philosophy behind it, sets a new
-standard in the comparing and validating algorithms.
+standard in comparing and validating algorithms.
 These efforts are informed by a great deal of experience of NA-MIC
@@ Line 78: / Line 78: @@
 generally enforces new algorithms to comparison against these
 databases, it can be difficult for researchers to move beyond the
-family techniques that have proven effect in this regard. Thus,
+family of techniques that have proven effect in this regard. Thus,
 insistence on specific databases of images and imaging problems can,
 in some cases, stifle creativity and discourage researchers from
@@ Line 89: / Line 89: @@
 participation from our collaborators at Brigham and Women's (DBP) who
 are applying DTI analysis to clinical problems. In general, the DBPs
-and the associated R01s, a long with extensive list of collaborators
+and the associated R01s, along with extensive list of collaborators
 at each site that are not formally part of NA-MIC, will provide a
 richer context for validating and comparing algorithms.

@@ Line 104: / Line 104: @@
 =====References=====
-[1] Gilmore John H., Lin Weili, Corouge Isabelle, Vetsa Y. Sampath K.,
+[1] J.H. Gilmore, W. Lin, I. Corouge, Y. Vetsa, K. Sampath, J.K. Smith, C. Kang, H. Gu, R. Hamer, J. Lieberman, G. Gerig. Early Postnatal Development of Corpus
 Callosum and Corticospinal White Matter Assessed with Quantitative
 Tractography, accepted AJNR- (American Journal of Neuroradiology), in
 print.
-[2] Melonakos J., Pichon E., Angenent S., Tannenbaum A. Finsler Active
+[2] J. Melonakos, E. Pichon, S. Angenent, A. Tannenbaum. Finsler Active
 Contours. IEEE PAMI. 2007. In Press.
-[3] Fletcher PT, Joshi S. Riemannian Geometry for the Statistical Analysis
+[3] P.T. Fletcher, S. Joshi. Riemannian Geometry for the Statistical Analysis
 of Diffusion Tensor Data. Signal Processing, 2006.

@@ Line 123: / Line 123: @@
 Nonlinear Registration of Diffusion MR Images. MICCAI 2007. In Press.
-[6] Goodlett, Casey , Fletcher, P. Thomas , Lin, Weili , and Gerig, Guido,
+[6] C. Goodlett, P. T. Fletcher, W. Lin, and G. Gerig,
 "Quantification of measurement error in DTI: Theoretical predictions
 and validation", in print MICCAI 2007, to appear Nov. 2007
@@ Line 131: / Line 131: @@
 of White Matter Fiber Tracts, IPMI 2007, Netherlands.
-[8] Goodlett C, Fletcher PT, Lin W, and Gerig G. Noise-induced bias in
+[8] C. Goodlett, P.T. Fletcher, W. Lin, and G. Gerig. Noise-induced bias in
 low-direction diffusion tensor MRI: Replication of Monte-Carlo
 simulation with in-vivo scans. Accepted ISMRM 2007.
@@ Line 141: / Line 141: @@
 Manifold. CVPR'07. In Press.
-[11] Fletcher, P.T., Tao, R., Jeong, W.-K., Whitaker, R.T., "A Volumetric
+[11] P.T. Fletcher, R. Tao, W. -K. Jeong, R.T. Whitaker, "A Volumetric
 Approach to Quantifying Region-to-Region White Matter Connectivity in
 Diffusion Tensor MRI," to appear Information Processing in Medical
 Imaging (IPMI) 2007.
-[12] Jeong, W.-K., Fletcher, P.T., Tao, R., Whitaker, R.T., "Interactive
+[12] W.-K. Jeong,  P.T. Fletcher, R. Tao, R.T. Whitaker, "Interactive
 Visualization of Volumetric White Matter Connectivity in Diffusion
 Tensor MRI Using a Parallel-Hardware Hamilton-Jacobi Solver," to
@@ Line 158: / Line 158: @@
 http://www.na-mic.org/Wiki/index.php/Algorithm:MIT:DTI_StochasticTractography
-[14]  Styner M, Xu SC, El-Sayed M, Gerig G, Correspondence Evaluation
+[14]  M. Styner, SC Xu , M. El-Sayed, G. Gerig, Correspondence Evaluation
 in Local Shape Analysis and Structural Subdivision, IEEE Symposium on
 Biomedical Imaging ISBI 2007, in print
@@ Line 165: / Line 165: @@
 Modeling and Analysis with Entropy-Based Particle Systems. IPMI 2007.
-[16] Nain D, Haker S, Bobick A, Tannenbaum A. Multiscale 3D Shape
+[16] D. Nain, S. Haker, A. Bobick, A. Tannenbaum. Multiscale 3D Shape
 Analysis using Spherical Wavelets. Proc MICCAI, Oct 26-29 2005; p
 -467

← Older revision		Revision as of 15:53, 21 August 2007
Line 102:		Line 102:
	clinical or scientific results.		clinical or scientific results.

		+	=====References=====

	[1] Gilmore John H., Lin Weili, Corouge Isabelle, Vetsa Y. Sampath K.,		[1] Gilmore John H., Lin Weili, Corouge Isabelle, Vetsa Y. Sampath K.,

@@ Line 304: / Line 304: @@
 NA-MIC is, perhaps, somewhat different from other projects in image analysis,
-because it is an {\em alliance}.  Our choice of approaches and tools does
+because it is an alliance.  Our choice of approaches and tools does
 not reflect the interests or experiences of a single investigator or
 research group, but instead it relies on the experiences and talents of

@@ Line 187: / Line 187: @@
 algorithms and software for medical image analysis.  Our work is
 driven by medical and biological problems defined by our collaborators
-(e.g. DBPs) both within and outside of the project, and it is {\em their}
+(e.g. DBPs) both within and outside of the project, and it is their
 interests and hypotheses regarding DTI that drive the software
 development.  Thus, the question of the appropriateness of clinical
 problems,  in the short term and long term, is not central to the
-charter of the center.  {\em We are providing our clinical collaborators
+charter of the center.  We are providing our clinical collaborators
 and the field as a whole a set of software tools that will
-help determine the how and where DTI is most useful. }
+help determine the how and where DTI is most useful.
 That said, the project is informed about the role of DTI in scientific

@@ Line 43: / Line 43: @@
 attention is also evident in the upcoming "Tractography Measures
 Conference" [17].
 At this workshop we will have our biological collaborators, with
 data already preprocessed and available on Wiki, a set of Core 1
@@ Line 60: / Line 59: @@
 have been compared on a standard set of photographs, and the
 literature shows a progression of wavelet-shrinkage strategies that
-produce progressively better RMS errors [????]. While this progress
+produce progressively better RMS errors [18]. While this progress
 has been impressive, it has produced a series of algorithms and
 parameter settings that are particularly well suited to those data
 sets, and which do not necessarily generalize to images that are not
-well represented in that data [awate2005]. Thus, close attention to
+well represented in that data [19]. Thus, close attention to
 comparison and validation against particular metrics and data sets
 tends to skew algorithms toward those measures. Another example is in
@@ Line 71: / Line 70: @@
 automobiles, etc., of different types, in somewhat natural
 surroundings and various degrees of occlusion and lighting are
-available [???] for training and testing algorithms for object
+available [20] for training and testing algorithms for object
 recognition. As with image denoising, the field has benefited
 significantly, but there are those who argued that these databases and
@@ Line 84: / Line 83: @@
 looking at problems from different points of view.
-Thus, we believe comparisons of different algorithms cannot rely
+We believe comparisons of different algorithms cannot rely
 solely on databases of standard images, but must also be evaluated in
-their direct impact on clinical problems. Thus, for example, the
+their direct impact on clinical problems. For example, the
 upcoming "Tractography Measures Conference" will include extensive
 participation from our collaborators at Brigham and Women's (DBP) who
@@ Line 169: / Line 168: @@
 -467
-[17] http://www.na-mic.org/Wiki/index.php/SanteFe.Tractography.Conference
+[17]
 ==== To what problems is DTI best applicable? Is it applicable across age ranges?('''Ross Whitaker''')====