Subject: Re: C493: Space-Time Tradeoffs for Parallel 3D Reconstruction Algorithms for Virus Structure Determination From: "Dan C.Marinescu" Date: Fri, 30 Mar 2001 17:19:42 -0500 To: fox@csit.fsu.edu CC: dcm@cs.purdue.edu Dear Dr. Fox: I attach a pdf version of the revised paper and a rebuttal to comments from the reviewer. Thank you for your assistance. dan marinescu Geoffrey Fox wrote: > I append a referee report on your interesting paper > C493: Space-Time Tradeoffs for Parallel 3D Reconstruction Algorithms for Virus Structure Determination > > I would be happy to publish your paper if you addressed the changes > suggested by the referee. This looks quite possible with modest extensions. > Please put your work in context of other algorithms suggested > Please include a discussion of your changes and their answer to the > referees in your resubmittal. > > I thank you for your interest in Concurrency and Computation: Practice > and Experience. > Please continue to send us other good papers! > > Please send all communication -- including the resubmission -- > electronically > if possible using the address > fox@csit.fsu.edu > > If you should need a "real address", please use: > Geoffrey Fox > Computational Science and Information Technology > Florida State University > 400 Dirac Science Library > Tallahassee Florida 32306-4120 > > Phone 3152546387 > > ------------------------------------------------------------------------ > > I think it is good that researchers are beginning to develop various > approaches to the problem of high speed 3D reconstruction from 2D projection > data. In particular it is nice that algorithms for asymmetric data are being > developed since they have a very broad application area. > > The paper has some fundamental flaws if it is supposed to compete with work > in the field of 3D reconstruction in general; certainly the audience > interested in this kind of software development is also found in the area > of medical applications, from PET SPECT and NMR to the more similar CT > procedures. The work presented here is of the type non-iterative > 3D reconstruction algorithm, which has been the most used procedure in > biological research, but which nowadays are rather far from what is achieved > with methods used in the medical application areas by iterative methods of > various kinds (including maximum likelihood techniques). Even in a virus > icosahedral reconstruction application a maximum entropy algorithm has been > developed and shown in practice to perform well. These methods are not so > well parallelized yet, but the current paper doesn't even discuss these > methods and/or if the presented algorithm with increased speed will > be a survivor in the longer perspective in spite of the lower qualitative > and quantitive performance (compared to iterative procedures). > > A second flaw is the lack of discussion of prior art: it is well known that > a parallel implementation of the filtered backprojection algorithm, used for > asymmetric objects, is up and running since some years at the supercomputer > center in San Diego. At least a minimal discussion must be present were the > work is compared with the papers from collaborators around Dr. Mark > Ellismans group at NCMIR in San Diego. > > A technical remark is that the discrepancies between the icosahedrally > averaged center of the non-icosahedral region in the slices shown in figs > 5&6 are not discussed in detail, but nontheless very interesting (the > symmetry seen here is a generated artefact) because it means that the > two reconstruction methods really gives different results, not only a > speed-up factor for the presented algorithm. The interpolation algorithm > used to place the 2D DFT into the 3D space have not been evaluated or > more analytically commented upon. > > The paper has its strength in the analysis of the number of operations > used at different steps in the algorithm, but unless the critique above is > met, the paper is more like a technical report and shouldn't be published in > a scientific journal. I think it is good that researchers are beginning to develop various approaches to the problem of high speed 3D reconstruction from 2D projection data. In particular it is nice that algorithms for asymmetric data are being developed since they have a very broad application area. The paper has some fundamental flaws if it is supposed to compete with work in the field of 3D reconstruction in general; certainly the audience interested in this kind of software development is also found in the area of medical applications, from PET SPECT and NMR to the more similar CT procedures. >> Agree. But it is important to realize that there are >> fundamental differences between medical 3D reconstruction >> and the one in cryo-TEM. We outline these differences >> in Section 2 of the paper. The work presented here is of the type non-iterative 3D reconstruction algorithm, >> The 3D reconstruction per se is non-iterative >> but, as pointed out in the paper, it is performed >> repeatedly after the orientations of the particles >> are estimated. So the entire process is iterative. >> This is one of the reasons why we need an efficient >> algorithm. which has been the most used procedure in biological research, but which nowadays are rather far from what is achieved with methods used in the medical application areas by iterative methods of various kinds (including maximum likelihood techniques). Even in a virus icosahedral reconstruction application a maximum entropy algorithm has been developed and shown in practice to perform well. These methods are not so well parallelized yet, but the current paper doesn't even discuss these methods and/or if the presented algorithm with increased speed will be a survivor in the longer perspective in spite of the lower qualitative and quantitive performance (compared to iterative procedures). >> Agree. We included several paragraphs in Section 2 >> covering maximum likelihood methods, and added 4 (four) >> references for this topic. A second flaw is the lack of discussion of prior art: it is well known that a parallel implementation of the filtered backprojection algorithm, used for asymmetric objects, is up and running since some years at the supercomputer center in San Diego. At least a minimal discussion must be present were the work is compared with the papers from collaborators around Dr. Mark Ellismans group at NCMIR in San Diego. >> Agree. We added a "related work" section and more >> references. The number of references increased from >> 18 to 28. We could not find any reference to parallel >> reconstruction algorithms at NCMIR. I contacted Mark but >> I did not get a pointer to a reference in his replay so >> I assume that the results have not been published yet. >> If the reviewer is aware of such a reference it would be >> useful to share it with us. A technical remark is that the discrepancies between the icosahedrally averaged center of the non-icosahedral region in the slices shown in figs 5&6 are not discussed in detail, but nontheless very interesting (the symmetry seen here is a generated artefact) because it means that the two reconstruction methods really gives different results, not only a speed-up factor for the presented algorithm. >> Of course. A point which we did to mention in the original version >> of the paper is that our algorithm leads to a better quality solution >> because it incorporates the CTF correction, as discussed on pages >> 13-15 of the revised version. The interpolation algorithm used to place the 2D DFT into the 3D space have not been evaluated or more analytically commented upon. >> A number of references for the sequential algorithm are given. >> There is no point to include in this paper a detailed analysis of the >> sequential algorithm, published elsewhere. >> Nevertheless, we added Figure 3 to illustrate the >> one-dimensional interpolation. The paper has its strength in the analysis of the number of operations used at different steps in the algorithm, but unless the critique above is met, the paper is more like a technical report and shouldn't be published in a scientific journal. Dan Marinescu Professor Purdue University Computer Sciences Dan Marinescu Professor Purdue University Computer Sciences Computer Sciences Building Room CS 172 West Lafayette In 47907 USA Fax: (765) 494 0739 Home: (765) 463 6038 Work: (765) 494 6018 Additional Information: Last Name Marinescu First Name Dan Version 2.1