User:Jadrian Miles/Thesis proposal feedback: Difference between revisions

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Feedback on my October 2010 thesis proposal included [[/dhl notes]] from during the talk, [[/jfh email]] after the talk, [[/dhl meeting notes]] after Spike's email, and conversations with other committee and faculty members that were not recorded.  Feedback on the style and organization of my talk was synthesized into the HOWTO page [[Give a talk]].  Feedback on the content of my ideas and their individual presentation is listed on this page.  The committee has asked that I formally respond to these comments.
Feedback on my October 2010 thesis proposal included [[/dhl notes]] from during the talk, [[/jfh email]] after the talk, [[/dhl meeting notes]] after Spike's email, and conversations with other committee and faculty members that were not recorded.  Feedback on the style and organization of my talk was synthesized into the HOWTO page [[Give a talk]].  Feedback on the content of my ideas and their individual presentation is listed on this page.  The committee has asked that I formally respond to these comments.


# The term "unambiguous" in the thesis statement is poorly defined.  The statement that the solution to this system could not be computed using other models may be unprovable.
# Spike pointed out two issues with the thesis statement.  The term "unambiguous" may be meaningless in this context, and the statement that the solution to this system could not be computed using other, single-scale models may be unprovable.
# More direct comparison to a greater variety of related work is needed, including global macrostructure models (such as spin-glass models), signal regularization schemes, and microstructure models.
# Peter expressed a desire for more direct comparison to a greater variety of related work, in particular global macrostructure models such as Gibbs tracking and spin-glass models.  Direct comparison to related work of other sorts, including signal regularization schemes and microstructure models, is also needed.
# The order in which curve clusters are selected for candidate merges is unclear, as are the consequences of different ordering choices.
# Several commenters felt that the distinction between the geometry-based curve-clustering process and the image-based bundle-adjustment process was insufficiently clear.
# The "black-box math" used to describe the curve-clustering algorithm's energy function is insufficiently specific.  What is the principled reason for an algorithm to choose a middle ground between 300,000 singleton clusters and one whole-brain cluster?
# Spike and others were concerned that the "black-box math" used to describe the curve-clustering algorithm's cluster configuration energy function is insufficiently specific.  What is the principled reason for the algorithm to choose a middle ground between 300,000 singleton clusters and one whole-brain cluster?
# The nature of the optimization algorithm for image-based bundle refinement is not specified.  How does it relate to established techniques? What is the relationship between image differences and the space of candidate bundle refinements that they suggest?  How does it avoid overfitting?
# Eugene asked for clarification of the order in which curve clusters are selected for candidate merges, as well as the consequences of different ordering choices.
# How will the model accomodate white matter fascicles that project outside of the brain?
# David and Spike both felt that the anatomical assumptions and prior knowledge that are applied to various steps in the macrostructure-fitting process required stronger justifications from the biological literature.
# How will the macrostructure modeling results be validated?
# Chad and others were concerned that the nature of the optimization algorithm for image-based bundle refinement is not specified.  How does it relate to established techniques?
# Would chained applications of the macrostructure fitting process converge quickly?  If not, why not?  If so, what is the nature of the fixed-point solution?
# Ben asked how image differences would be translated into a space of candidate bundle refinements.
# The stated choice of a Rician distribution for axon diameters seems inappropriate.
# The entire committee asked how the image-based bundle-adjustment optimization algorithm would avoid overfitting.
# A concrete "toy example" is needed for proper evaluation of this proposal.  This could take the form of a computational or physical phantom.
# Peter asked how the model will accomodate white matter fascicles that terminate outside of the brain.
# Spike asked how the modeling system's macrostructure reconstruction will be validated, whether it would be stable across subjects and acquisitions, and whether it would correspond reasonably (perhaps in a subset relationship) with anatomists' conception of the macrostructure.
# Spike asked whether the fitting process would be idempotent, up to variation due to noise.  If not, would chained applications of the process converge quickly?  If not, why not?  If so, what is the nature of the fixed-point solution?
# David mentioned that the stated choice of a Rician distribution for axon diameters seems inappropriate.
# Ben and others expressed concern about the feasibility of the proposed research schedule.

Revision as of 19:13, 3 November 2010

Feedback on my October 2010 thesis proposal included /dhl notes from during the talk, /jfh email after the talk, /dhl meeting notes after Spike's email, and conversations with other committee and faculty members that were not recorded. Feedback on the style and organization of my talk was synthesized into the HOWTO page Give a talk. Feedback on the content of my ideas and their individual presentation is listed on this page. The committee has asked that I formally respond to these comments.

  1. Spike pointed out two issues with the thesis statement. The term "unambiguous" may be meaningless in this context, and the statement that the solution to this system could not be computed using other, single-scale models may be unprovable.
  2. Peter expressed a desire for more direct comparison to a greater variety of related work, in particular global macrostructure models such as Gibbs tracking and spin-glass models. Direct comparison to related work of other sorts, including signal regularization schemes and microstructure models, is also needed.
  3. Several commenters felt that the distinction between the geometry-based curve-clustering process and the image-based bundle-adjustment process was insufficiently clear.
  4. Spike and others were concerned that the "black-box math" used to describe the curve-clustering algorithm's cluster configuration energy function is insufficiently specific. What is the principled reason for the algorithm to choose a middle ground between 300,000 singleton clusters and one whole-brain cluster?
  5. Eugene asked for clarification of the order in which curve clusters are selected for candidate merges, as well as the consequences of different ordering choices.
  6. David and Spike both felt that the anatomical assumptions and prior knowledge that are applied to various steps in the macrostructure-fitting process required stronger justifications from the biological literature.
  7. Chad and others were concerned that the nature of the optimization algorithm for image-based bundle refinement is not specified. How does it relate to established techniques?
  8. Ben asked how image differences would be translated into a space of candidate bundle refinements.
  9. The entire committee asked how the image-based bundle-adjustment optimization algorithm would avoid overfitting.
  10. Peter asked how the model will accomodate white matter fascicles that terminate outside of the brain.
  11. Spike asked how the modeling system's macrostructure reconstruction will be validated, whether it would be stable across subjects and acquisitions, and whether it would correspond reasonably (perhaps in a subset relationship) with anatomists' conception of the macrostructure.
  12. Spike asked whether the fitting process would be idempotent, up to variation due to noise. If not, would chained applications of the process converge quickly? If not, why not? If so, what is the nature of the fixed-point solution?
  13. David mentioned that the stated choice of a Rician distribution for axon diameters seems inappropriate.
  14. Ben and others expressed concern about the feasibility of the proposed research schedule.