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Cambridge, 2004)
26. D.B. Ress, M.L. Harlow, R.M. Marshall, U.J. McMahan, Methods for generating
high-resolution structural models from electron microscope tomography data. Structure
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27. A. Bartesaghi, G. Sapiro, S. Subramaniam, An energy-based three-dimensional segmentation approach for the quantitative interpretation of electron tomograms. IEEE Trans. Image
Proc. 14, 1314–1323 (2005)
28. R.T. Whitaker, V. Elangovan, A direct approach to estimating surfaces in tomographic data.
Med. Image Anal. 6, 235–249 (2002)
29. S. Osher, J.A. Sethian, Fronts propagating wirh curvature dependent speed: algorithms based
on Hamilton-Jacobi formulations. J. Comp. Phys. 79, 12–49 (1988)
30. R.A. Ali, M.J. Landsberg, E. Knauth, G.P. Morgan, B.J. Marsh, B. Hankamer, A 3D image
filter for parameter-free segmentation of macromolecular structures from electron tomograms. PLoS ONE 7, e33697 (2012)
31. K. Sandberg, M. Brega, Segmentation of thin structures in electron micrographs using
orientation fields. J. Struct. Biol. 157, 403–415 (2007)
32. C. Bajaj, Z.Y. Yu, M. Auer, Volumetric feature extraction and visualization of tomographic
molecular imaging. J. Struct. Biol. 144, 132–143 (2003)
33. A. Martinez-Sanchez, I. Garcia, J.J. Fernandez, A differential structure approach to
membrane segmentation in electron tomography. J. Struct. Biol. 175, 372–383 (2011)
34. A. Martinez-Sanchez, I. Garcia, J.J. Fernandez, A ridge-based framework for segmentation
of 3D electron microscopy datasets. J. Struct. Biol. 181, 61–70 (2013)
35. A. Martinez-Sanchez, I. Garcia, S. Asano, V. Lucic, J.J. Fernandez, Robust membrane
detection based on tensor voting for electron tomography. J. Struct. Biol. 186, 49–61 (2014)
36. J. Bigun, Optimal orientation detection of linear symmetry. IEEE 1st Int. Conf. Comp. Vis. 1
(1987)
37. S. Beucher, F. Meyer, The morphological approach to segmentation: the watershed
transformation, in Mathematical morphology in image processing, ed. by E.R. Dougherty
(Marcel Dekker, New York, 1993), pp. 433–481
38. L. Vincent, P. Soille, Watersheds in digital space: an efficient algorithm based on immersion
simulations. IEEE Trans. Pattern Anal. Mach. Intell. 13, 583–598 (1991)
39. N. Volkmann, A novel three-dimensional variant of the watershed transform for
segmentation of electron density maps. J. Struct. Biol. 138, 123–129 (2002)
40. S. Pruggnaller, M. Mayr, A.S. Frangakis, A visualization and segmentation toolbox for
electron microscopy. J. Struct. Biol. 164, 161–165 (2008)
41. T.D. Goddard, C.C. Huang, T.E. Ferrin, Visualizing density maps with UCSF Chimera.
J. Struct. Biol. 157, 281–287 (2007)
42. G. Pintilie, J. Zhang, W. Chiu, D. Gossard, Identifying components in 3D density maps of
protein nanomachines by multi-scale segmentation. IEEE NIH Life Sci. Syst. Appl.
Workshop. 2009, 44–47 (2009)
43. E. Garduño, M. Wong-Barnum, N. Volkmann, M.H. Ellisman, Segmentation of electron
tomographic data sets using fuzzy set theory principles. J. Struct. Biol. 162, 368–379 (2008)
44. A.S. Frangakis, R. Hegerl, Segmentation of two- and three-dimensional data from electron
microscopy using eigenvector analysis. J. Struct. Biol. 138, 105–113 (2002)
45. B.J. Marsh, N. Volkmann, J.R. McIntosh, K.E. Howell, Direct continuities between
cisternae at different levels of the Golgi complex in glucose-stimulated mouse islet beta cells.
Proc. Natl. Acad. Sci. U. S. A. 101, 5565–5570 (2004)
46. F. Moussavi, G. Heitz, F. Amat, L.R. Comolli, D. Koller, M. Horowitz, 3D segmentation of
cell boundaries from whole cell cryogenic electron tomography volumes. J. Struct. Biol. 170,
134–145 (2010)
314
N. Volkmann
image data using IMOD. J. Struct. Biol. 116, 71–76 (1996)
25. D. Stalling, H. Hege, M. Westerhoff, Amira—a highly interactive system for visual data
analysis. In Visualization Handbook ed. by C.R. Johnson, C.D. Hansen (Academic Press,
Cambridge, 2004)
26. D.B. Ress, M.L. Harlow, R.M. Marshall, U.J. McMahan, Methods for generating
high-resolution structural models from electron microscope tomography data. Structure
12, 1763–1774 (2004)
27. A. Bartesaghi, G. Sapiro, S. Subramaniam, An energy-based three-dimensional segmentation approach for the quantitative interpretation of electron tomograms. IEEE Trans. Image
Proc. 14, 1314–1323 (2005)
28. R.T. Whitaker, V. Elangovan, A direct approach to estimating surfaces in tomographic data.
Med. Image Anal. 6, 235–249 (2002)
29. S. Osher, J.A. Sethian, Fronts propagating wirh curvature dependent speed: algorithms based
on Hamilton-Jacobi formulations. J. Comp. Phys. 79, 12–49 (1988)
30. R.A. Ali, M.J. Landsberg, E. Knauth, G.P. Morgan, B.J. Marsh, B. Hankamer, A 3D image
filter for parameter-free segmentation of macromolecular structures from electron tomograms. PLoS ONE 7, e33697 (2012)
31. K. Sandberg, M. Brega, Segmentation of thin structures in electron micrographs using
orientation fields. J. Struct. Biol. 157, 403–415 (2007)
32. C. Bajaj, Z.Y. Yu, M. Auer, Volumetric feature extraction and visualization of tomographic
molecular imaging. J. Struct. Biol. 144, 132–143 (2003)
33. A. Martinez-Sanchez, I. Garcia, J.J. Fernandez, A differential structure approach to
membrane segmentation in electron tomography. J. Struct. Biol. 175, 372–383 (2011)
34. A. Martinez-Sanchez, I. Garcia, J.J. Fernandez, A ridge-based framework for segmentation
of 3D electron microscopy datasets. J. Struct. Biol. 181, 61–70 (2013)
35. A. Martinez-Sanchez, I. Garcia, S. Asano, V. Lucic, J.J. Fernandez, Robust membrane
detection based on tensor voting for electron tomography. J. Struct. Biol. 186, 49–61 (2014)
36. J. Bigun, Optimal orientation detection of linear symmetry. IEEE 1st Int. Conf. Comp. Vis. 1
(1987)
37. S. Beucher, F. Meyer, The morphological approach to segmentation: the watershed
transformation, in Mathematical morphology in image processing, ed. by E.R. Dougherty
(Marcel Dekker, New York, 1993), pp. 433–481
38. L. Vincent, P. Soille, Watersheds in digital space: an efficient algorithm based on immersion
simulations. IEEE Trans. Pattern Anal. Mach. Intell. 13, 583–598 (1991)
39. N. Volkmann, A novel three-dimensional variant of the watershed transform for
segmentation of electron density maps. J. Struct. Biol. 138, 123–129 (2002)
40. S. Pruggnaller, M. Mayr, A.S. Frangakis, A visualization and segmentation toolbox for
electron microscopy. J. Struct. Biol. 164, 161–165 (2008)
41. T.D. Goddard, C.C. Huang, T.E. Ferrin, Visualizing density maps with UCSF Chimera.
J. Struct. Biol. 157, 281–287 (2007)
42. G. Pintilie, J. Zhang, W. Chiu, D. Gossard, Identifying components in 3D density maps of
protein nanomachines by multi-scale segmentation. IEEE NIH Life Sci. Syst. Appl.
Workshop. 2009, 44–47 (2009)
43. E. Garduño, M. Wong-Barnum, N. Volkmann, M.H. Ellisman, Segmentation of electron
tomographic data sets using fuzzy set theory principles. J. Struct. Biol. 162, 368–379 (2008)
44. A.S. Frangakis, R. Hegerl, Segmentation of two- and three-dimensional data from electron
microscopy using eigenvector analysis. J. Struct. Biol. 138, 105–113 (2002)
45. B.J. Marsh, N. Volkmann, J.R. McIntosh, K.E. Howell, Direct continuities between
cisternae at different levels of the Golgi complex in glucose-stimulated mouse islet beta cells.
Proc. Natl. Acad. Sci. U. S. A. 101, 5565–5570 (2004)
46. F. Moussavi, G. Heitz, F. Amat, L.R. Comolli, D. Koller, M. Horowitz, 3D segmentation of
cell boundaries from whole cell cryogenic electron tomography volumes. J. Struct. Biol. 170,
134–145 (2010)
314
N. Volkmann