4.9.9 Electron Microscope Images and Sensors

Chapter Contents (Back)
Electron Microscope.
See also Medical Applications, Microscope Image Analysis.

Matson, W.L.[William L.], McKinstry, H.A., Johnson, Jr., G.G., White, E.W., McMillan, R.E.,
Computer processing of SEM images by contour analyses,
PR(2), No. 4, December 1970, pp. 303-306.
Elsevier DOI 0309
scanning electron microscope images. BibRef

Sandler, S.S.[Sheldon S.],
Direct three-dimensional analysis of electron micrograph pictures,
PR(4), No. 4, December 1972, pp. 353-359.
Elsevier DOI 0309
The method consists of presenting a unique relation between the projection pictures and the original densities. BibRef

Kriete, A., Haucke, M., Gerlach, B., Harms, H., Aus, H.M.,
A Preprocessing Method for the Contrast Enhancement of TV-Scanned Electron Microscopic Images,
PR(17), No. 3, 1984, pp. 305-311.
Elsevier DOI BibRef 8400

White, E.W., Mayberry, K., Johnson, Jr., G.G.,
Computer analysis of multi-channel SEM and X-ray images from fine particles,
PR(4), No. 2, May 1972, pp. 173-192.
Elsevier DOI 0309
Scanning electron microscope BibRef

Favre, A., Keller, H.,
Local image transformation: An application in biological electron microscopy,
PR(13), No. 2, 1981, pp. 177-187.
Elsevier DOI 0309
BibRef

Phillips, T.Y.[Tsai-Yun], Davis, L.S.[Larry S.], Rosenfeld, A.[Azriel],
Automatic Segmentation of Electron Micrographs of Berea Sandstone Cross-Sections,
PR(16), No. 4, 1983, pp. 385-400.
Elsevier DOI 0309
BibRef

Kriete, A., Aus, H.M.,
On-Line Processing of Transmission Electron Microscopic Images,
PRL(4), 1986, pp. 285-292. BibRef 8600

Selfridge, P.G.[Peter G.],
Locating Neuron Boundaries in Electron Micrograph Images Using 'Primal Sketch' Primitives,
CVGIP(34), No. 2, May 1986, pp. 156-165.
Elsevier DOI BibRef 8605
And:
Tracing Neurons Through Serial Sections: Using Knowledge of Shape to Improve Performance,
CVPR86(418-420). Shows that iso-intensity contours do not work, but does not mention other edge techniques. Use edges, search techniques, and prediction of position. BibRef

Zapata, E.L., Benavides, I., Rivera, F.F., Bruguera, J.D., Pena, T.F., Carazo, J.M.,
Image reconstruction on hypercube computers: Application to electron microscopy,
SP(27), No. 1, 1992, pp. 51-64. BibRef 9200

Ong, S.H., Giam, S.T., Jayasooriah, Sinniah, R.,
Adaptive window-based tracking for the detection of membrane structures in kidney electron micrographs,
MVA(6), No. 4, 1993, pp. 215-223. BibRef 9300

Vrhel, M.J., Unser, M.,
Multichannel Restoration with Limited A Priori Information,
IP(8), No. 4, April 1999, pp. 527-536.
IEEE DOI electron microscopy of biological macromolecules BibRef 9904

Vrhel, M.J., Trus, B.L.,
Multi-channel restoration of electron micrographs,
ICIP95(II: 516-519).
IEEE DOI 9510
BibRef

Kayaalp, A., Rao, A.R.[A. Ravishankar], Jain, R.,
Scanning Electron Microscope-Based Stereo Analysis,
MVA(3), No. 4, 1990, pp. 231-246. BibRef 9000
Earlier: CVPR89(429-434).
IEEE DOI BibRef

Herman, G.T.[Gabor T.], Marabini, R.[Roberto], Carazo, J.M.[José-María], Garduño, E.[Edgar], Lewitt, R.M.[Robert M.], Matej, S.[Samuel],
Image processing approaches to biological three-dimensional electron microscopy,
IJIST(11), No. 1, 2000, pp. 12-29. 0005
BibRef

Marabini, R., Sorzano, C.O.S., Matej, S., Fernandez, J.J., Carazo, J.M., Herman, G.T.,
3-D Reconstruction of 2-D Crystals in Real Space,
IP(13), No. 4, April 2004, pp. 549-561.
IEEE DOI 0404
BibRef
And: Corrections: IP(13), No. 8, August 2004, pp. 1157-1157.
IEEE DOI BibRef

Ruiz, V.G., Fernández, J.J., López, M.F., García, I.,
Progressive Image Transmission in Telemicroscopy: A Quantitative Approach for Electron Microscopy Images of Biological Specimens,
RealTimeImg(8), No. 6, December 2002, pp. 519-544.
DOI Link 0304
BibRef

Pattichis, M.S., Pattichis, C.S., Avraam, M., Bovik, A.C., Kyriacou, K.,
AM-FM texture segmentation in electron microscopic muscle imaging,
MedImg(19), No. 12, December 2000, pp. 1253-1257.
IEEE Top Reference. 0110
BibRef

Sorzano, C.O.S., Marabini, R., Herman, G.T., Carazo, J.M.,
Multiobjective algorithm parameter optimization using multivariate statistics in three-dimensional electron microscopy reconstruction,
PR(38), No. 12, December 2005, pp. 2587-2601.
Elsevier DOI 0510
BibRef

Salzenstein, F.[Fabien], Montgomery, P.C.[Paul C.], Montaner, D.[Denis], Boudraa, A.O.[Abdel-Ouahab],
Teager-Kaiser Energy and Higher-Order Operators in White-Light Interference Microscopy for Surface Shape Measurement,
JASP(2005), No. 17, 2005, pp. 2804-2815.
WWW Link. 0603
BibRef

Sorzano, C.O.S.[Carlos O. S.], Velazquez-Muriel, J.A., Marabini, R., Herman, G.T., Carazo, J.M.[José María],
Volumetric restrictions in single particle 3DEM reconstruction,
PR(41), No. 2, February 2008, pp. 616-626.
Elsevier DOI 0711
Tomography, Constrained reconstruction, Electron microscopy, Single particles BibRef

Lee, S.H.[Seung-Hee], Doerschuk, P.C., Johnson, J.E.,
Multiclass Maximum-Likelihood Symmetry Determination and Motif Reconstruction of 3-D Helical Objects From Projection Images for Electron Microscopy,
IP(20), No. 7, July 2011, pp. 1962-1976.
IEEE DOI 1107
BibRef

Prust, C.J., Doerschuk, P.C., Johnson, J.E.,
3-D Reconstructions of Tailed Bacteriophages from CYRO Electron Microscopy Images,
ICIP06(917-920).
IEEE DOI 0610
BibRef

Hermann, G.[Gilles], Coudray, N.[Nicolas], Buessler, J.L.[Jean-Luc], Caujolle-Bert, D.[Daniel], Rémigy, H.W.[Hervé-William], Urban, J.P.[Jean-Philippe],
ANIMATED-TEM: a toolbox for electron microscope automation based on image analysis,
MVA(23), No. 4, July 2012, pp. 691-711.
WWW Link. 1206
BibRef

Venkatakrishnan, S.V., Drummy, L.F., Jackson, M.A., de Graef, M., Simmons, J., Bouman, C.A.,
A Model Based Iterative Reconstruction Algorithm For High Angle Annular Dark Field-Scanning Transmission Electron Microscope (HAADF-STEM) Tomography,
IP(22), No. 11, 2013, pp. 4532-4544.
IEEE DOI 1310
biology computing BibRef

Hu, T., Nunez-Iglesias, J., Vitaladevuni, S., Scheffer, L., Xu, S., Bolorizadeh, M., Hess, H., Fetter, R., Chklovskii, D.B.,
Electron Microscopy Reconstruction of Brain Structure Using Sparse Representations Over Learned Dictionaries,
MedImg(32), No. 12, 2013, pp. 2179-2188.
IEEE DOI 1312
Brain BibRef

Ito, K.[Koichi], Suzuki, A.[Ayako], Aoki, T.[Takafumi], Tsuneta, R.[Ruriko],
Image-based magnification calibration for electron microscope,
MVA(25), No. 1, January 2014, pp. 185-197.
WWW Link. 1402
BibRef

Wang, L., Singer, A., Wen, Z.,
Orientation Determination of Cryo-EM Images Using Least Unsquared Deviations,
SIIMS(6), No. 4, 2013, pp. 2450-2483.
DOI Link 1402
cryo-electron microscopy BibRef

Ober, R.J., Tahmasbi, A., Ram, S., Lin, Z.P.[Zhi-Ping], Ward, E.S.,
Quantitative Aspects of Single-Molecule Microscopy: Information-theoretic analysis of single-molecule data,
SPMag(32), No. 1, January 2015, pp. 58-69.
IEEE DOI 1502
image processing BibRef

Chen, Y.H.[Yu-Hui], Wei, D., Newstadt, G., de Graef, M., Simmons, J., Hero, A.,
Parameter Estimation in Spherical Symmetry Groups,
SPLetters(22), No. 8, August 2015, pp. 1152-1155.
IEEE DOI 1502
crystal orientation BibRef

Katsevich, E., Katsevich, A., Singer, A.,
Covariance Matrix Estimation for the Cryo-EM Heterogeneity Problem,
SIIMS(8), No. 1, 2015, pp. 126-185.
DOI Link 1503
cryo-electron microscopy. BibRef

Jensen, K.H., Sigworth, F.J., Brandt, S.S.,
Removal of Vesicle Structures From Transmission Electron Microscope Images,
IP(25), No. 2, February 2016, pp. 540-552.
IEEE DOI 1601
Adaptation models BibRef

Huang, C., Tagare, H.D.,
Robust w-Estimators for Cryo-EM Class Means,
IP(25), No. 2, February 2016, pp. 893-906.
IEEE DOI 1601
Correlation BibRef

Gaddam, C.K.[Chethan K.], Huang, C.H.[Chung-Hsuan], Wal, R.L.V.[Randy L. Vander],
Quantification of nano-scale carbon structure by HRTEM and lattice fringe analysis,
PRL(76), No. 1, 2016, pp. 90-97.
Elsevier DOI 1605
Lattice fringe analysis BibRef

Chao, J.[Jerry], Ward, E.S.[E. Sally], Ober, R.J.[Raimund J.],
Fisher information theory for parameter estimation in single molecule microscopy: tutorial,
JOSA-A(33), No. 7, July 2016, pp. B36-B57.
DOI Link 1608
Probability theory, stochastic processes, and statistics BibRef

Ashok, A.[Amit], Piestun, R.[Rafael], Stallinga, S.[Sjoerd],
Single molecule image formation, reconstruction and processing: introduction,
JOSA-A(33), No. 7, July 2016, pp. SMI1-SMI2.
DOI Link 1608
General, General physics BibRef

Sheppard, C.J.R.[Colin J. R.], Castello, M.[Marco], Tortarolo, G.[Giorgio], Vicidomini, G.[Giuseppe], Diaspro, A.[Alberto],
Image formation in image scanning microscopy, including the case of two-photon excitation,
JOSA-A(34), No. 8, August 2017, pp. 1339-1350.
DOI Link 1708
Optical transfer functions, Confocal microscopy, Fluorescence microscopy, Scanning microscopy, Multiphoton, processes BibRef

Andén, J.[Joakim], Singer, A.[Amit],
Structural Variability from Noisy Tomographic Projections,
SIIMS(11), No. 2, 2018, pp. 1441-1492.
DOI Link 1807
cryo-electron microscopy BibRef

Che, C.Q.[Cheng-Qian], Lin, R.G.[Ruo-Gu], Zeng, X.R.[Xiang-Rui], Elmaaroufi, K.[Karim], Galeotti, J.[John], Xu, M.[Min],
Improved deep learning-based macromolecules structure classification from electron cryo-tomograms,
MVA(29), No. 8, November 2018, pp. 1227-1236.
Springer DOI 1811
BibRef

Liu, C., Zeng, X.R.[Xiang-Rui], Lin, R.G.[Ruo-Gu], Liang, X., Freyberg, Z., Xing, E., Xu, M.[Min],
Deep Learning Based Supervised Semantic Segmentation of Electron Cryo-Subtomograms,
ICIP18(1578-1582)
IEEE DOI 1809
Image segmentation, Signal to noise ratio, Semantics, Decoding, Convolutional neural networks BibRef

Ma, C.[Chao], Bendory, T.[Tamir], Boumal, N.[Nicolas], Sigworth, F.[Fred], Singer, A.[Amit],
Heterogeneous Multireference Alignment for Images With Application to 2D Classification in Single Particle Reconstruction,
IP(29), No. 1, 2020, pp. 1699-1710.
IEEE DOI 1912
Cryo-electron microscopy. Signal to noise ratio, Image reconstruction, Photomicrography, Noise measurement, Noise level, Principal component analysis, Ice, single particle reconstruction BibRef

He, Y.C.[Yu-Chen], Kang, S.H.[Sung Ha],
Lattice Identification and Separation: Theory and Algorithm,
SIIMS(12), No. 4, 2019, pp. 2063-2096.
DOI Link 1912
BibRef
Earlier:
Lattice Metric Space Application to Grain Defect Detection,
SSVM19(381-392).
Springer DOI 1909
Atomic scale. Not food. BibRef

Bermúdez-Chacón, R., Altingövde, O., Becker, C., Salzmann, M., Fua, P.,
Visual Correspondences for Unsupervised Domain Adaptation on Electron Microscopy Images,
MedImg(39), No. 4, April 2020, pp. 1256-1267.
IEEE DOI 2004
Image segmentation, Adaptation models, Visualization, Training, Electron microscopy, Machine learning, Electron microscopy, domain adaptation BibRef

Zehni, M.[Mona], Donati, L.[Laurène], Soubies, E.[Emmanuel], Zhao, Z.Z.[Zhi-Zhen], Unser, M.[Michael],
Joint Angular Refinement and Reconstruction for Single-Particle Cryo-EM,
IP(29), 2020, pp. 6151-6163.
IEEE DOI 2005
Single-particle cryo-EM, joint reconstruction, continuous angular refinement, ADMM, gradient descent BibRef

Qian, Y., Xu, J., Drummy, L.F., Ding, Y.,
Effective Super-Resolution Methods for Paired Electron Microscopic Images,
IP(29), 2020, pp. 7317-7330.
IEEE DOI 2007
Optical imaging, Training, Electron optics, Deep learning, Electron microscopic image, deep learning, paired-image super-resolution BibRef

Xie, H., Liang, J., Wang, Z., Liao, M., Li, X.,
Scanning Imaging Restoration of Moving or Dynamically Deforming Objects,
IP(29), 2020, pp. 7290-7305.
IEEE DOI 2007
Scanning electron microscopy, Optical imaging, Strain, Optical distortion, Image restoration, Numerical analysis, Non-uniform blur BibRef

Cao, Y.[Yue], Liu, S.G.[Shi-Gang], Peng, Y.[Yali], Li, J.[Jun],
DenseUNet: densely connected UNet for electron microscopy image segmentation,
IET-IPR(14), No. 12, October 2020, pp. 2682-2689.
DOI Link 2010
BibRef

Andén, J.[Joakim], Romero, J.L.[José Luis],
Multitaper Estimation on Arbitrary Domains,
SIIMS(13), No. 3, 2020, pp. 1565-1594.
DOI Link 2010
estimating spectral densities, Electron microscope. BibRef

Rosen, E.[Eitan], Shkolnisky, Y.[Yoel],
Common Lines Ab Initio Reconstruction of D_2-Symmetric Molecules in Cryo-Electron Microscopy,
SIIMS(13), No. 4, 2020, pp. 1898-1944.
DOI Link 2012
BibRef

Heimowitz, A.[Ayelet], Sharon, N.[Nir], Singer, A.[Amit],
Centering Noisy Images with Application to Cryo-EM,
SIIMS(14), No. 2, 2021, pp. 689-716.
DOI Link 2107
Center of mass, or geometric median computations. BibRef

Liu, Y.[Yi], Ji, S.W.[Shui-Wang],
CleftNet: Augmented Deep Learning for Synaptic Cleft Detection From Brain Electron Microscopy,
MedImg(40), No. 12, December 2021, pp. 3507-3518.
IEEE DOI 2112
Feature extraction, Synapses, Task analysis, Logic gates, Deep learning, Shape, Electron microscopy, label augmentation BibRef

Wang, J.[Jia], Lan, C.[Chuwen], Wang, C.Y.[Cai-Yong], Gao, Z.[Zehua],
Deep learning super-resolution electron microscopy based on deep residual attention network,
IJIST(31), No. 4, 2021, pp. 2158-2169.
DOI Link 2112
attention mechanism, deep learning, electron microscope, residual learning, super-resolution BibRef

Kacher, J.[Josh], Xie, Y.[Yao], Voigt, S.P.[Sven P.], Zhu, S.X.[Shi-Xiang], Yuchi, H.[Henry], Key, J.[Jordan], Kalidindi, S.R.[Surya R.],
In Situ Transmission Electron Microscopy: Signal processing challenges and examples,
SPMag(39), No. 1, January 2022, pp. 89-103.
IEEE DOI 2201
Materials science and technology, Image analysis, Data analysis, Transmission electron microscopy, Statistical analysis, Data collection BibRef

Huang, Q.[Qinwen], Zhou, Y.[Ye], Liu, H.F.[Hsuan-Fu], Bartesaghi, A.[Alberto],
Weakly Supervised Learning for Joint Image Denoising and Protein Localization in Cryo-Electron Microscopy,
WACV22(3260-3269)
IEEE DOI 2202
Proteins, Training, Image segmentation, Tomography, Video surveillance, Biology, Grouping and Shape BibRef

d'Avigneau, A.M.[A. Marie], Singh, S.S.[Sumeetpal S.], Ober, R.J.[Raimund J.],
Limits of Accuracy for Parameter Estimation and Localization in Single-Molecule Microscopy via Sequential Monte Carlo Methods,
SIIMS(15), No. 1, 2022, pp. 139-171.
DOI Link 2204
BibRef

Kreymer, S.[Shay], Singer, A.[Amit], Bendory, T.[Tamir],
An Approximate Expectation-Maximization for Two-Dimensional Multi-Target Detection,
SPLetters(29), 2022, pp. 1087-1091.
IEEE DOI 2205
Signal to noise ratio, Noise measurement, Autocorrelation, Approximation algorithms, Rotation measurement, Size measurement, cryo-electron microscopy BibRef

Bendory, T.[Tamir], Hadi, I.[Ido], Sharon, N.[Nir],
Compactification of the Rigid Motions Group in Image Processing,
SIIMS(15), No. 3, 2022, pp. 1041-1078.
DOI Link 2208
BibRef

Deng, S.Y.[Shi-Yu], Huang, W.[Wei], Chen, C.[Chang], Fu, X.[Xueyang], Xiong, Z.W.[Zhi-Wei],
A Unified Deep Learning Framework for ssTEM Image Restoration,
MedImg(41), No. 12, December 2022, pp. 3734-3746.
IEEE DOI 2212
Serial section transmission electron microscopy. Image restoration, Optical imaging, Adaptive optics, Optical attenuators, Deep learning, Strain, Neurons, deep learning BibRef

Bendory, T.[Tamir], Boumal, N.[Nicolas], Leeb, W.[William], Levin, E.[Eitan], Singer, A.[Amit],
Toward Single Particle Reconstruction without Particle Picking: Breaking the Detection Limit,
SIIMS(16), No. 2, 2023, pp. 886-910.
DOI Link 2306
BibRef

Diepeveen, W.[Willem], Lellmann, J.[Jan], Oktem, O.[Ozan], Schonlieb, C.B.[Carola-Bibiane],
Regularizing Orientation Estimation in Cryogenic Electron Microscopy Three-Dimensional Map Refinement through Measure-Based Lifting over Riemannian Manifolds,
SIIMS(16), No. 3, 2023, pp. 1440-1490.
DOI Link 2309
BibRef

Somani, A.[Ayush], Banerjee, P.[Pragyan], Agarwal, K.[Krishna], Rastogi, M.[Manu], Prasad, D.K.[Dilip K.], Habib, A.[Anowarul],
Image Inpainting with Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy,
DL-UIA23(3113-3122)
IEEE DOI 2309
BibRef

Huang, C.Y.[Chao-Yan], Wu, T.T.[Ting-Ting], Li, J.C.[Jun-Cheng], Dong, B.[Bin], Zeng, T.Y.[Tie-Yong],
Single-particle reconstruction in cryo-EM based on three-dimensional weighted nuclear norm minimization,
PR(143), 2023, pp. 109736.
Elsevier DOI 2310
Single-particle reconstruction, Cryogenic electron microscopy, Forward-backward splitting algorithm, Three-dimensional weighted nuclear norm minimization BibRef


Chen, M.H.[Ming-Hao], Renuka, M.B.[Mukesh Bangalore], Mi, L.[Lu], Lichtman, J.[Jeff], Shavit, N.[Nir], Meirovitch, Y.[Yaron],
Learning to Correct Sloppy Annotations in Electron Microscopy Volumes,
CVMI23(4273-4284)
IEEE DOI 2309
BibRef

Nguyen, N.P.[Nguyen P.], Surya, R.[Ramakrishna], Maschmann, M.[Matthew], Calyam, P.[Prasad], Palaniappan, K.[Kannappan], Bunyak, F.[Filiz],
Self-supervised Orientation-guided Deep Network for Segmentation of Carbon Nanotubes in SEM Imagery,
Scarce22(412-428).
Springer DOI 2304
BibRef

Wang, Y.H.[Yuan-Hao], Idoughi, R.[Ramzi], Heidrich, W.[Wolfgang],
Joint Motion-Correction and Reconstruction in Cryo-Em Tomography,
ICIP22(1101-1105)
IEEE DOI 2211
Image resolution, Limiting, Tomography, Fiducial markers, Iterative methods, Image reconstruction, Computational Imaging BibRef

Huang, Q.[Qinwen], Zhou, Y.[Ye], Liu, H.F.[Hsuan-Fu], Bartesaghi, A.[Alberto],
Accurate Detection of Proteins in Cryo-Electron Tomograms from Sparse Labels,
ECCV22(XXI:644-660).
Springer DOI 2211
BibRef

Levy, A.[Axel], Poitevin, F.[Frédéric], Martel, J.[Julien], Nashed, Y.[Youssef], Peck, A.[Ariana], Miolane, N.[Nina], Ratner, D.[Daniel], Dunne, M.[Mike], Wetzstein, G.[Gordon],
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images,
ECCV22(XXI:540-557).
Springer DOI 2211
BibRef

Wang, T.Y.[Tian-Yang], Li, B.[Bo], Zhang, J.[Jing], Zeng, X.R.[Xiang-Rui], Uddin, M.R.[Mostofa Rafid], Wu, W.[Wei], Xu, M.[Min],
Deep Active Learning for Cryo-Electron Tomography Classification,
ICIP22(1611-1615)
IEEE DOI 2211
Training, Uniform resource locators, Solid modeling, Uncertainty, Tomography, Rendering (computer graphics), Deep active learning, Classification BibRef

Yu, Z.[Zifan], Trindade, B.M.[Bruno Machado], Green, M.[Michael], Zhang, Z.[Zhikang], Sneha, P.[Pullela], Tavakoli, E.B.[Erfan Bank], Pawlowicz, C.[Christopher], Ren, F.[Fengbo],
A Data-Driven Approach for Automated Integrated Circuit Segmentation of Scan Electron Microscopy Images,
ICIP22(2851-2855)
IEEE DOI 2211
Integrated circuits, Image segmentation, Scanning electron microscopy, Wires, Industry applications, integrated circuit segmentation BibRef

Han, H.Q.[Hong-Qing], Dmitrieva, M.[Mariia], Sauer, A.[Alexander], Tam, K.H.[Ka Ho], Rittscher, J.[Jens],
Self-Supervised Voxel-Level Representation Rediscovers Subcellular Structures in Volume Electron Microscopy,
CVMI22(1873-1882)
IEEE DOI 2210
Representation learning, Measurement, Solid modeling, Image segmentation, Biological system modeling BibRef

Kniesel, H.[Hannah], Ropinski, T.[Timo], Bergner, T.[Tim], Devan, K.S.[Kavitha Shaga], Read, C.[Clarissa], Walther, P.[Paul], Ritschel, T.[Tobias], Hermosilla, P.[Pedro],
Clean Implicit 3D Structure from Noisy 2D STEM Images,
CVPR22(20730-20740)
IEEE DOI 2210
Training, Solid modeling, Transmission electron microscopy, Microscopy, Data models, Noise measurement, Medical, Self- semi- meta- unsupervised learning BibRef

He, B.[Bintao], Zhang, F.[Fa], Zhang, H.[Huanshui], Han, R.[Renmin],
A Hybrid Frequency-Spatial Domain Model for Sparse Image Reconstruction in Scanning Transmission Electron Microscopy,
ICCV21(2662-2671)
IEEE DOI 2203
Scanning electron microscopy, Transmission electron microscopy, Frequency-domain analysis, Microscopy, Computational modeling, Optimization and learning methods BibRef

Zeng, Y.C.[Yu-Chen], Howe, G.[Gregory], Yi, K.[Kai], Zeng, X.[Xiangrui], Zhang, J.[Jing], Chang, Y.W.[Yi-Wei], Xu, M.[Min],
Unsupervised Domain Alignment Based Open Set Structural Recognition of Macromolecules Captured By Cryo-Electron Tomography,
ICIP21(106-110)
IEEE DOI 2201
Deep learning, Image recognition, Systematics, Image analysis, Training data, Tomography, Cryo-Electron Tomography, Open-set learning BibRef

Xin, T.[Tong], Chen, B.[Bohao], Chen, X.[Xi], Han, H.[Hua],
UTR: Unsupervised Learning of Thickness-Insensitive Representations for Electron Microscope Image,
ICIP21(155-159)
IEEE DOI 2201
Image registration, Scanning electron microscopy, Neurites, Neural circuits, Morphology, Feature extraction, FIB-SEM BibRef

Fan, Y.F.[Yi-Feng], Zhao, Z.Z.[Zhi-Zhen],
Cryo-Electron Microscopy Image Denoising Using Multi-Frequency Vector Diffusion Maps,
ICIP21(3463-3467)
IEEE DOI 2201
Interpolation, Noise reduction, Signal processing algorithms, Signal processing, Image reconstruction, Image denoising, image denoising BibRef

Watkins, L.[Luisa], Seidel, S.W.[Sheila W.], Peng, M.[Minxu], Agarwal, A.[Akshay], Yu, C.C.[Christopher C.], Goyal, V.K.[Vivek K],
Robustness of Time-Resolved Measurement to Unknown and Variable Beam Current in Particle Beam Microscopy,
ICIP21(3487-3491)
IEEE DOI 2201
Scanning electron microscopy, Particle beams, Correlation, Particle beam measurements, Atmospheric measurements, scanning electron microscopy BibRef

Friedrich, T.[Thomas], Yu, C.P.[Chu-Ping], Verbeek, J.[Johan], Pennycook, T.[Timothy], van Aert, S.[Sandra],
Phase Retrieval from 4-Dimensional Electron Diffraction Datasets,
ICIP21(3453-3457)
IEEE DOI 2201
Training, Electric potential, Sensitivity, Convolutional neural networks, Electron microscopy, CBED BibRef

Monardo, V.[Vincent], Iyer, A.[Abhiram], Donegan, S.[Sean], de Graef, M.[Marc], Chi, Y.[Yuejie],
Plug-And-Play Image Reconstruction Meets Stochastic Variance-Reduced Gradient Methods,
ICIP21(2868-2872)
IEEE DOI 2201
Gradient methods, Image coding, Runtime, Superresolution, Stochastic processes, Electron microscopy, plug-and-play, image reconstruction BibRef

Nashed, Y.S.G.[Youssef S. G.], Poitevin, F.[Frédéric], Gupta, H.[Harshit], Woollard, G.[Geoffrey], Kagan, M.[Michael], Yoon, C.H.[Chun Hong], Ratner, D.[Daniel],
CryoPoseNet: End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data,
LCI21(4049-4059)
IEEE DOI 2112
Solid modeling, Image resolution, Pose estimation, Pipelines, Decoding BibRef

Pinetz, T.[Thomas], Kobler, E.[Erich], Doberstein, C.[Christian], Berkels, B.[Benjamin], Effland, A.[Alexander],
Total Deep Variation for Noisy Exit Wave Reconstruction in Transmission Electron Microscopy,
SSVM21(491-502).
Springer DOI 2106
BibRef

Khadangi, A.[Afshin], Boudier, T.[Thomas], Rajagopal, V.[Vijay],
EM-net: Deep learning for electron microscopy image segmentation,
ICPR21(31-38)
IEEE DOI 2105
Deep learning, Measurement, Training, Image segmentation, Scanning electron microscopy, cell architecture BibRef

Singla, A.[Aayush], Lippmann, B.[Bernhard], Graeb, H.[Helmut],
Recovery of 2D and 3D Layout Information through an Advanced Image Stitching Algorithm using Scanning Electron Microscope Images,
ICPR21(3860-3867)
IEEE DOI 2105
Scanning electron microscopy, Semiconductor devices, Layout, Software algorithms, Software BibRef

Sinha, A.[Ashish], Suresh, K.S.,
Deep Learning Based Dimple Segmentation for Quantitative Fractography,
IML20(463-474).
Springer DOI 2103
BibRef

Ghosh, A., Chaudhry, R., Rajwade, A.,
AB Initio Tomography With Object Heterogeneity and Unknown Viewing Parameters,
ICIP19(1257-1261)
IEEE DOI 1910
Cryo-electron microscopy, Heterogeneity, Tomography, Ab initio reconstruction BibRef

Quan, T.M., Hildebrand, D.G.C., Lee, K., Thomas, L.A., Kuan, A.T., Lee, W.A., Jeong, W.,
Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data,
CLI19(3804-3813)
IEEE DOI 2004
electron microscopy, image denoising, learning (artificial intelligence), medical image processing, GAN BibRef

Min, S.B.[Shao-Bo], Chen, X.J.[Xue-Jin], Xie, H.T.[Hong-Tao], Zha, Z.J.[Zheng-Jun], Bi, G.Q.[Guo-Qiang], Wu, F.[Feng], Zhang, Y.D.[Yong-Dong],
Accurate Segmentation of Synaptic Cleft with Contour Growing Concatenated with a Convnet,
ICIP19(1420-1424)
IEEE DOI 1910
Analyze the macromolecular complexes related to neurotransmitter transmission. High noise. Electron micrographs. Synaptic cleft, fully convolutional networks, active contours, contour growing, segmentation BibRef

Chan, R.H.[Raymond H.], Lazzaro, D.[Damiana], Morigi, S.[Serena], Sgallari, F.[Fiorella],
A Non-convex Nonseparable Approach to Single-Molecule Localization Microscopy,
SSVM19(498-509).
Springer DOI 1909
BibRef

Bodduna, K.[Kireeti], Weickert, J.[Joachim], Frangakis, A.S.[Achilleas S.],
Hough Based Evolutions for Enhancing Structures in 3D Electron Microscopy,
CAIP19(I:102-112).
Springer DOI 1909
BibRef

Molina-Abril, H.[Helena], Diaz del Rio, F.[Fernando], Guerrero-Lebrero, M.P.[Maria P.], Real, P.[Pedro], Barcena, G.[Guillermo], Braza, V.[Veronica], Guerrero, E.[Elisa], Gonzalez, D.[David], Galindo, P.L.[Pedro L.],
Topological Homogeneity for Electron Microscopy Images,
CTIC19(166-178).
Springer DOI 1901
BibRef

Michels, Y., Baudrier, E., Mazo, L.,
Radial Function Based Ab-Initio Tomographic Reconstruction for Cryo Electron Microscopy,
ICIP18(1178-1182)
IEEE DOI 1809
Image reconstruction, Signal to noise ratio, Reconstruction algorithms, unknown directions BibRef

Anoshina, N.A., Krylov, A.S., Sorokin, D.V.,
Correlation-based 2D registration method for single particle cryo-EM images,
IPTA17(1-6)
IEEE DOI 1804
electron microscopy, image reconstruction, image registration, image resolution, iterative methods, 2D registration method, EMDB, cryo-electron microscopy BibRef

Pape, C.[Constantin], Beier, T.[Thorsten], Li, P.[Peter], Jain, V.[Viren], Bock, D.D.[Davi D.], Kreshuk, A.[Anna],
Solving Large Multicut Problems for Connectomics via Domain Decomposition,
BioIm17(1-10)
IEEE DOI 1802
Electron microscopy volumes. Approximation algorithms, Image reconstruction, Image segmentation, Merging, Neurons, Partitioning algorithms, Pipelines BibRef

Sreehari, S., Venkatakrishnan, S.V., Bouman, K.L., Simmons, J.P., Drummy, L.F., Bouman, C.A.,
Multi-Resolution Data Fusion for Super-Resolution Electron Microscopy,
NTIRE17(1084-1092)
IEEE DOI 1709
Image resolution, Interpolation, Libraries, Noise reduction, Transmission, electron, microscopy BibRef

Liu, Q.[Qing], Yang, X.P.[Xiao-Ping], Zhao, X.L.[Xiao-Long], Ling, W.J.[Wei-Jun], Lu, F.P.[Fei-Ping], Zhao, Y.X.[Yu-Xiang],
Microscopic image enhancement of Chinese Herbal Medicine based on fuzzy set,
ICIVC17(299-302)
IEEE DOI 1708
Electron microscopy, Feature extraction, Finite element analysis, Fuzzy sets, Image enhancement, Laplace equations, Chinese herbal medicine, fuzzy set, image enhancement, microscopic, image BibRef

Abdollahzadeh, A.[Ali], Acar, E.[Erman], Peltonen, S.[Sari], Ruotsalainen, U.[Ulla],
Local Adaptive Wiener Filtering for Class Averaging in Single Particle Reconstruction,
SCIA17(II: 233-244).
Springer DOI 1706
cryo-electron microscopy. BibRef

Arnal, R.D., Wojtas, D.H., Millane, R.P.,
Progress towards imaging biological filaments using X-ray free-electron lasers,
IVCNZ20(1-6)
IEEE DOI 2012
BibRef
Earlier: A3, A2, A1:
Extreme imaging: Macromolecular imaging using x-ray free-electron lasers,
ICVNZ16(1-6)
IEEE DOI 1701
Free electron lasers, Imaging, X-ray lasers, X-ray diffraction, Biology, X-ray imaging, structural biology. Crystallography BibRef

Štepka, K.[Karel], Maška, M.[Martin], Pálenik, J.J.[Jakub Jozef], Pospíchalová, V.[Vendula], Kotrbová, A.[Anna], Ilkovics, L.[Ladislav], Klemová, D.[Dobromila], Hampl, A.[Aleš], Bryja, V.[Vítezslav], Matula, P.[Pavel],
Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy,
BioImage16(I: 318-325).
Springer DOI 1611
BibRef

Colabrese, S., Castello, M., Vicidomini, G., del Bue, A.,
Learning-based approach to boost detection rate and localisation accuracy in single molecule localisation microscopy,
ICIP16(3184-3188)
IEEE DOI 1610
Diffraction BibRef

Gong, Y., Doerschuk, P.C.,
3-D understanding of electron microscopy images of nano bio objects by computing generative mechanical models,
ICIP16(3161-3165)
IEEE DOI 1610
Biological system modeling BibRef

Michels, Y., Baudrier, É.,
Retrieving the parameters of cryo Electron Microscopy dataset in the heterogeneous ab-initio case,
ICIP16(3189-3193)
IEEE DOI 1610
Estimation BibRef

Lin, Y.Z.[You-Zuo], Kandel, Y.[Yudhishthir], Zotta, M.[Matthew], Lifshin, E.[Eric],
SEM resolution improvement using semi-blind restoration with hybrid L1-L2 regularization,
Southwest16(33-36)
IEEE DOI 1605
Scanning electron microscopy. Image resolution BibRef

Liu, T.[Ting], Zhang, M.M.[Miao-Miao], Javanmardi, M.[Mehran], Ramesh, N.[Nisha], Tasdizen, T.[Tolga],
SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation,
ECCV16(I: 144-159).
Springer DOI 1611
BibRef

Liu, T.[Ting], Seyedhosseini, M.[Mojtaba], Ellisman, M.[Mark], Tasdizen, T.[Tolga],
Watershed merge forest classification for electron microscopy image stack segmentation,
ICIP13(4069-4073)
IEEE DOI 1402
Machine learning BibRef

Liu, T.[Ting], Jurrus, E.[Elizabeth], Seyedhosseini, M.[Mojtaba], Ellisman, M.[Mark], Tasdizen, T.[Tolga],
Watershed merge tree classification for electron microscopy image segmentation,
ICPR12(133-137).
WWW Link. 1302
BibRef

Parag, T., Ciresan, D.C., Giusti, A.,
Efficient Classifier Training to Minimize False Merges in Electron Microscopy Segmentation,
ICCV15(657-665)
IEEE DOI 1602
Algorithm design and analysis BibRef

Wang, Q.[Qiu], Doerschuk, P.C.[Peter C.],
3-D image reconstruction for bio nanomachines with helical symmetry: Image formation theory,
ICIP15(892-896)
IEEE DOI 1512
cryo electron microscopy BibRef

Gong, Y.[Yunye], Doerschuk, P.C.[Peter C.],
Determining fluctuation in bio-nanomachines from electron microscopy images,
ICIP15(262-265)
IEEE DOI 1512
cryo electron microscopy BibRef

Shenoy, R.[Renuka], Shih, M.C.[Min-Chi], Rose, K.[Kenneth],
Segmentation of cells in electron microscopy images through multimodal label transfer,
ICIP15(103-107)
IEEE DOI 1512
Electron Microscopy, Multimodal, Segmentation BibRef

Xu, X.P.[Xiao-Ping], Page, C.[Christopher], Volkmann, N.[Niels],
Efficient Extraction of Macromolecular Complexes from Electron Tomograms Based on Reduced Representation Templates,
CAIP15(I:423-431).
Springer DOI 1512
BibRef

Sousa, R.G.[Ricardo Gamelas], Esteves, T.[Tiago], Rocha, S.[Sara], Figueiredo, F.[Francisco], Quelhas, P.[Pedro], Silva, L.M.[Luís M.],
Automatic Detection of Immunogold Particles from Electron Microscopy Images,
ICIAR15(377-384).
Springer DOI 1507
BibRef

Bhadouria, V.S.[Vivek Singh], Ghoshal, D.[Dibyendu],
Edge detection in electron microscopy biological images using statistical dispersion,
IMVIP12(96-100).
IEEE DOI 1302
BibRef

Habibullah, Ur Rehman, O.[Obaid], Pota, H.R., Petersen, I.R.,
Internal reference model based optimal LQG controller for atomic force microscope,
ICARCV12(294-299).
IEEE DOI 1304
BibRef

Lind, J.[Jonathan], Rollett, A.D.[Anthony D.], Pokharel, R.[Reeju], Hefferan, C.[Christopher], Li, S.F.[Shiu-Fai], Lienert, U.[Ulrich], Suter, R.[Robert],
Image processing in experiments on, and simulations of plastic deformation of polycrystals,
ICIP14(4877-4881)
IEEE DOI 1502
Diffraction BibRef

Egelman, E.H.[Edward H.],
New advances in imaging polymers at near-atomic resolution,
ICIP14(2071-2074)
IEEE DOI 1502
Detectors BibRef

Wang, Y.F.[Yun-Feng], Kilpatrick, J.I.[Jason I.], Jarvis, S.P.[Suzanne P.], Boland, F.[Frank], Kokaram, A.[Anil], Corrigan, D.[David],
Automated registration of low and high resolution atomic force microscopy images using scale invariant features,
ICIP14(5866-5870)
IEEE DOI 1502
Atomic force microscopy BibRef

Le Guen, V.[Vincent], Paul, N.[Nicolas],
A Scanning Electron Microscope image segmentation method for steam generator fouling rate estimation,
ICIP14(4447-4451)
IEEE DOI 1502
Clustering algorithms BibRef

Thierry, R.[Raphael], Kirschmann, M.[Moritz], Hummel, E.[Eric], Hawes, C.[Chris], Genoud, C.[Christel],
Demon registration for 3D images obtained by serial block face scanning electron microscopy,
ICIP14(3587-3591)
IEEE DOI 1502
Algorithm design and analysis BibRef

Nam, D.[David], Mantell, J.[Judith], Hodgson, L.[Lorna], Bull, D.R.[David R.], Verkade, P.[Paul], Achim, A.[Alin],
Feature-based registration for correlative light and electron microscopy images,
ICIP14(3567-3571)
IEEE DOI 1502
Image registration BibRef

Sorzano, C.O.S., Vargas, J., Oton, J., Abrishami, V., de la Rosa-Trevin, J.M., del Riego, S., Fernandez-Alderete, A., Martinez-Rey, C., Marabini, R., Carazo, J.M.,
An image processing approach to the simulation of electron microscopy volumes of atomic structures,
ICIP14(2095-2099)
IEEE DOI 1502
Atomic clocks BibRef

Jin, Q.Y.[Qi-Yu], Sorzano, C.O.S.[Carlos Oscar Sanchez], Callebaut, I.[Isabelle], Tama, F.[Florence], Jonic, S.[Slavica],
Elastic image registration to fully explore macromolecular dynamics by electron microscopy,
ICIP14(2075-2079)
IEEE DOI 1502
Assembly BibRef

Tafti, A.P.[A. Pahlavan], Kirkpatrick, A.B., Owen, H.A., Yu, Z.,
3D Microscopy Vision Using Multiple View Geometry and Differential Evolutionary Approaches,
ISVC14(II: 141-152).
Springer DOI 1501
BibRef

Roels, J.[Joris], Aelterman, J.[Jan], de Vylder, J.[Jonas], Luong, H.[Hiep], Saeys, Y.[Yvan], Lippens, S.[Saskia], Philips, W.[Wilfried],
Noise Analysis and Removal in 3D Electron Microscopy,
ISVC14(I: 31-40).
Springer DOI 1501
BibRef

Iwahori, Y.J.[Yu-Ji], Funahashi, K.[Kenji], Woodham, R.J.[Robert J.], Bhuyan, M.K.,
Neural Network Based Image Modification for Shape from Observed SEM Images,
ICPR14(2131-2136)
IEEE DOI 1412
Scanning Electron Microscope. BibRef

Azadi, S.[Samaneh], Maitin-Shepard, J.[Jeremy], Abbeel, P.[Pieter],
Optimization-Based Artifact Correction for Electron Microscopy Image Stacks,
ECCV14(II: 219-235).
Springer DOI 1408
BibRef

Lee, H.G.[Hyun-Gyu], Choi, M.K.[Min-Kook], Lee, S.C.[Sang-Chul],
Grain-oriented segmentation of scanning electron microscope images,
ICIP13(4029-4033)
IEEE DOI 1402
Nanostructures;Ti foil;anodization;grain structure;image segmentation BibRef

Yang, H.F.[Huei-Fang], Choe, Y.[Yoonsuck],
An Interactive Editing Framework for Electron Microscopy Image Segmentation,
ISVC11(I: 400-409).
Springer DOI 1109
BibRef

Papa, J.P.[João P.], Pereira, C.R.[Clayton R.], de Albuquerque, V.H.C.[Victor H.C.], Silva, C.C.[Cleiton C.], Falcão, A.X.[Alexandre X.], Tavares, J.M.R.S.[João Manuel R.S.],
Precipitates Segmentation from Scanning Electron Microscope Images through Machine Learning Techniques,
IWCIA11(456-468).
Springer DOI 1105
BibRef

Veeraraghavan, A.[Ashok], Genkin, Alex.V., Vitaladevuni, S.[Shiv], Scheffer, L.[Lou], Xu, S.[Shan], Hess, H.[Harald], Fetter, R.[Richard], Cantoni, M.[Marco], Knott, G.[Graham], Chklovskii, D.[Dmitri],
Increasing depth resolution of electron microscopy of neural circuits using sparse tomographic reconstruction,
CVPR10(1767-1774).
IEEE DOI Video of talk:
WWW Link. 1006
BibRef

Kim, D.S.[Dong Sik],
Intensity compensation of the mitochondria tilted image sequence obtained from the transmission electron microscopy,
ICIP09(1777-1780).
IEEE DOI 0911
BibRef

Mendizibal, A., Cabrera, J., Salgado, L., Garcia, N., Gonzalez, J.C.,
Unsupervised segmentation algorithm of HRTEM images,
ICIP04(IV: 2757-2760).
IEEE DOI 0505
high resolution transmission electron microscopy. BibRef

Bilbao-Castro, J.R., Carazo, J.M., Garcia, L., Fernandez, J.J.,
Parallel iterative reconstruction methods for structure determination of biological specimens by electron microscopy,
ICIP03(I: 565-568).
IEEE DOI 0312
BibRef

Barcucci, E., del Lungol, A., Nivat, M., Pinzani, R., Zurli, A.,
Reconstructing digital sets from X-rays,
CIAP97(I: 166-173).
Springer DOI 9709
tomography, 3D chrystals from 2D electron microscope images. BibRef

Skoglund, U., Ofverstedt, L.G.,
Image 3-D Reconstruction from Electron Micrographs,
SSAB97(Medical) 9703
BibRef

Saad, A., Chiu, W., Thuman-Commike, P.A.,
Multiresolution approach to automatic detection of spherical particles from electron cryomicroscopy images,
ICIP98(III: 846-850).
IEEE DOI 9810
BibRef

van Dyck, D., Op de Beeck, M.,
How image processing can push electron microscopy to its limits,
ICIP95(III: 41-44).
IEEE DOI 9510
BibRef

van Dyck, D., Op de Beeck, M., Tang, D., Jansen, J., Zandbergen, H.W.,
A global entropy criterion for focus tuning in exit wavefunction reconstruction in high resolution electron microscopy,
ICIP96(I: 737-740).
IEEE DOI 9610
BibRef

van Dyck, D., Op de Beeck, M., Coene, W.,
Object wavefunction reconstruction in high resolution electron microscopy,
ICIP94(III: 295-298).
IEEE DOI 9411
BibRef

Cop, M., Dengler, J.,
A multiresolution approach to the 3D reconstruction of a 50S ribosome from an EM-tilt series solving the alignment problem without gold particles,
ICPR90(I: 733-737).
IEEE DOI 9006
electron microscopy BibRef

Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
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