20 years of splines and biomedical imaging: The prehistory
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1 20 years of splines and biomedical imaging: The prehistory Michael Unser Biomedical Imaging Group EPFL, Lausanne Switzerland BIG's 20th Birthday, March 23, 2018, EPFL, Switzerland
2 1981: Master in EE 1984: Ph.D. in EE : Visiting Fellow : Scientist National Institutes of health, Biomedical Engineering and Instrumentation Program : Associate Professor 2000-present: Full Professor : Electron microscopy volume Volume 55 April Biophysical Journal 713 Interactions between actin and myosin filaments, in skeletal muscle visualized in frozen-hydrated thin sections B. L. Trus,* A. C. Steven,t A. W. McDowall,ll M. Unser, J. Dubochet,11 and R. J. Podolskyt *Computer Systems Laboratory, Division of Computer Research and Technology, *Laboratory of Physical Biology, National Institute of Arthritis, Musculoskeletal and Skin Diseases, Biological Engineering and Instrumentation Branch, National Institutes of Health, Bethesda, Maryland 20892; and 'European Molecular Biology Laboratory, D-6900 Heidelberg, Federal Republic of Germany ABSTRACT For the purpose of determining net interactions between actin and myosin filaments in muscle cells, perhaps the single most informative view of the myofilament lattice is its averaged axial projection. We have studied frozen-hydrated transverse thin sections with the goal of obtaining axial projections that are not subject to the limitations of conventional thin sectioning (suspect preservation of native structure) or of equatorial x-ray diffraction analysis (lack of experimental phases). In principle, good preservation of native structure may be achieved with fast freezing, followed by low-dose electron imaging of unstained vitrified cryosections. In practice, however, cryosections undergo large-scale distortions, including irreversible compression; furthermore, phase contrast imaging results in a nonlinear relationship between the projected density of the specimen and the optical density of the micrograph. To overcome these limitations, we have devised methods of image restoration and generalized correlation averaging, and applied them to cryosections of rabbit psoas fibers in both the relaxed and rigor states. Thus visualized, myosin filaments appear thicker than actin filaments by a much smaller margin than in conventional thin sections, and particularly so for rigor muscle. This may result from a significant fraction of the myosin S 1 -cross-bridges averaging out in projection and thus contributing only to the baseline of projected density. Entering rigor incurs a loss of density from an annulus around the myosin filament, with a compensating accumulation of density around the actin filament. This redistribution of mass represents attachment of the fraction of cross-bridges that are visible above background. Myosin filaments in the "nonoverlap" zone appear to broaden on entering rigor, suggesting that, on deprivation of ATP, cross-bridges in situ move outwards even without actin in their immediate proximity. Ultramicroscopy 30 (1989) North-Holland, Amsterdam SHORT NOTE THE SPECII~L SIGNAL-TO-NOISE RATIO RESOLUTION CRITERION: COMPUTATIONAL EFFICIENCY AND STATISTICAL PRECISION Michael UNSER *'* * Biomedical Engineering and Instrumentation Branch, National Institutes of Health, Bethesda, Maryland 20892, USA Benes L. TRUS Computer Systems Laboratory, Division of Computer Research and Technology, National Institutes of Health, Bethesda, Maryland 20892, USA Joachim FRANK Wadsworth Center for Laboratories and Research, New York State Department of Health, Albany, New York 12201, USA and Alasdair C. STEVEN Laboratory of Physical Biology, National Institute of Arthritis, Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA Jacques Dubochet, Joachim Frank, Richard Henderson Nobel Prize in Chemistry 2017 Received 14 March 1989 This note describes a practical improvement in the computational efficiency of the spectral signal-to-noise ratio (SSNR) resolution criterion for correlation-averaged images. The total set of N images is randomly partitioned into n s subsets, each subset is separately averaged, and a reduced form of the SSNR is computed from these average images. In general, larger values of n s achieve lower statistical uncertainty, while smaller values of ng are computationally more expedient. It is shown that, for negatively stained data, a judicious compromise is achieved with 10 < n s _< 20, regardless of how large N may be. "for developing cryo-electron microscopy for the high-resolution structure determination of biomolecules in solution" 4
3 : Splines and signal processing 5
4 : Splines and wavelets 7
5 San Diego 2003 Lumini 2009
6 : Wavelets in medicine and biology CRC Press,
7 BIG s research agenda Mathematical imaging Splines Wavelets Medical imaging Advanced image processing in biology Theoretical aspects f T Tf + n noise 14
8
9 One BIG Memory: going fractional IEEE Signal Processing Magazine November 1999 a scientific career June
Temperature-induced Structural Changes in the Myosin Thick Filament of
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