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Ariano, R.E.,
Mantsch, H.H.,
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MedImg(26), No. 7, July 2007, pp. 1010-1016.
IEEE DOI
0707
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Lehmussola, A.,
Ruusuvuori, P.,
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PIEEE(96), No. 8, August 2008, pp. 1348-1360.
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0804
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0909
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Earlier:
Efficient Acquisition and Learning of Fluorescence Microscope Data
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ICIP07(VI: 245-248).
IEEE DOI
0709
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Srinivasa, G.[Gowri],
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Active Mask Segmentation of Fluorescence Microscope Images,
IP(18), No. 8, August 2009, pp. 1817-1829.
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0907
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McCann, M.T.,
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deconvolution
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IEEE DOI
0909
BibRef
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IEEE DOI
1002
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1103
Tissue autofluorescence.
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Kolev, K.[Kalin],
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Elsevier DOI
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3D segmentation; Convex optimization; Vesicle membrane analysis;
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1203
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Multiview Deblurring for 3-D Images from Light-Sheet-Based Fluorescence
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1204
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Yuan, L.[Liang],
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Zhu, J.,
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Object Tracking With Particle Filtering in Fluorescence Microscopy
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IEEE DOI
1201
BibRef
Maska, M.,
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Segmentation and Shape Tracking of Whole Fluorescent Cells Based
on the Chan-Vese Model,
MedImg(32), No. 6, 2013, pp. 995-1006.
IEEE DOI
1307
biodiffusion; cancer; fluorescence; lung; Chan-Vese model;
graph cut frameworks
BibRef
Arslan, S.,
Ersahin, T.,
Cetin-Atalay, R.,
Gunduz-Demir, C.,
Attributed Relational Graphs for Cell Nucleus Segmentation
in Fluorescence Microscopy Images,
MedImg(32), No. 6, 2013, pp. 1121-1131.
IEEE DOI
1307
fluorescence microscopy image; Attributed relational graph
BibRef
Huang, C.,
Shih, P.,
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Lee, I.,
Hsu, H.,
Huang, H.,
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AMPFLUID: Aggregation Magnified Post-Assay Fluorescence for
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PIEEE(103), No. 2, February 2015, pp. 225-235.
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1504
Charge coupled devices
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Zhang, G.L.[Guang-Lei],
Pu, H.[Huangsheng],
He, W.[Wei],
Liu, F.[Fei],
Luo, J.W.[Jian-Wen],
Bai, J.[Jing],
Bayesian Framework Based Direct Reconstruction of Fluorescence
Parametric Images,
MedImg(34), No. 6, June 2015, pp. 1378-1391.
IEEE DOI
1506
Bayes methods
BibRef
Tominaga, S.[Shoji],
Hirai, K.[Keita],
Horiuchi, T.[Takahiko],
Estimation of bispectral Donaldson matrices of fluorescent objects by
using two illuminant projections,
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DOI Link
1506
Imaging systems; Multispectral and hyperspectral imaging
BibRef
Basset, A.,
Boulanger, J.,
Salamero, J.,
Bouthemy, P.,
Kervrann, C.,
Adaptive Spot Detection With Optimal Scale Selection in Fluorescence
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1509
Computer architecture
BibRef
Huelsnitz, T.[Thomas],
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Interferometric imaging with three objectives,
JOSA-A(33), No. 2, February 2016, pp. 179-191.
DOI Link
1602
Fluorescence microscopy
BibRef
Zhu, B.,
Rasmussen, J.C.,
Litorja, M.,
Sevick-Muraca, E.M.,
Determining the Performance of Fluorescence Molecular Imaging Devices
Using Traceable Working Standards With SI Units of Radiance,
MedImg(35), No. 3, March 2016, pp. 802-811.
IEEE DOI
1603
Cameras
BibRef
Dimiccoli, M.[Mariella],
Jacob, J.P.[Jean-Pascal],
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MVA(27), No. 4, May 2016, pp. 511-527.
WWW Link.
1605
BibRef
Amiot, C.[Carole],
Girard, C.,
Chanussot, J.[Jocelyn],
Pescatore, J.,
Desvignes, M.,
Spatio-Temporal Multiscale Denoising of Fluoroscopic Sequence,
MedImg(35), No. 6, June 2016, pp. 1565-1574.
IEEE DOI
1606
Biomedical imaging
BibRef
Priego, B.[Blanca],
Veganzones, M.A.[Miguel A.],
Chanussot, J.[Jocelyn],
Amiot, C.[Carole],
Prieto, A.[Abraham],
Duro, R.[Richard],
Spatio-temporal cellular automata-based filtering for image sequence
denoising: Application to fluoroscopic sequences,
ICIP13(548-552)
IEEE DOI
1402
Automata
BibRef
Negash, A.[Awoke],
Labouesse, S.[Simon],
Sandeau, N.[Nicolas],
Allain, M.[Marc],
Giovannini, H.[Hugues],
Idier, J.[Jerome],
Heintzmann, R.[Rainer],
Chaumet, P.C.[Patrick C.],
Belkebir, K.[Kamal],
Sentenac, A.[Anne],
Improving the axial and lateral resolution of three-dimensional
fluorescence microscopy using random speckle illuminations,
JOSA-A(33), No. 6, June 2016, pp. 1089-1094.
DOI Link
1606
Speckle imaging; Three-dimensional microscopy
BibRef
Gorpas, D.,
Ma, D.,
Bec, J.,
Yankelevich, D.R.,
Marcu, L.,
Real-Time Visualization of Tissue Surface Biochemical Features
Derived From Fluorescence Lifetime Measurements,
MedImg(35), No. 8, August 2016, pp. 1802-1811.
IEEE DOI
1608
Fluorescence
BibRef
Small, A.[Alex],
Multifluorophore localization as a percolation problem:
limits to density and precision,
JOSA-A(33), No. 7, July 2016, pp. B21-B30.
DOI Link
1608
Probability theory, stochastic processes, and statistics
BibRef
Chakrova, N.[Nadya],
Rieger, B.[Bernd],
Stallinga, S.[Sjoerd],
Deconvolution methods for structured illumination microscopy,
JOSA-A(33), No. 7, July 2016, pp. B12-B20.
DOI Link
1608
Deconvolution; Inverse problems; Fluorescence microscopy
BibRef
Zhang, Y.[Yide],
Khan, A.A.[Aamir A.],
Vigil, G.D.[Genevieve D.],
Howard, S.S.[Scott S.],
Investigation of signal-to-noise ratio in frequency-domain
multiphoton fluorescence lifetime imaging microscopy,
JOSA-A(33), No. 7, July 2016, pp. B1-B11.
DOI Link
1608
Fluorescence microscopy
BibRef
Vigil, G.D.[Genevieve D.],
Zhang, Y.[Yide],
Khan, A.A.[Aamir A.],
Howard, S.S.[Scott S.],
Description of deep saturated excitation multiphoton microscopy for
super-resolution imaging,
JOSA-A(34), No. 7, July 2017, pp. 1217-1223.
DOI Link
1708
Superresolution, Fluorescence microscopy, , Nonlinear, optics
BibRef
Svoboda, D.[David],
Ulman, V.[Vladimír],
MitoGen: A Framework for Generating 3D Synthetic Time-Lapse Sequences
of Cell Populations in Fluorescence Microscopy,
MedImg(36), No. 1, January 2017, pp. 310-321.
IEEE DOI
1701
BibRef
Earlier:
Generation of Synthetic Image Datasets for Time-Lapse Fluorescence
Microscopy,
ICIAR12(II: 473-482).
Springer DOI
1206
Algorithm design and analysis
BibRef
Ulman, V.[Vladimír],
Orému, Z.[Zoltán],
Svoboda, D.[David],
TRAgen: A Tool for Generation of Synthetic Time-Lapse Image Sequences
of Living Cells,
CIAP15(I:623-634).
Springer DOI
1511
BibRef
An, Y.,
Liu, J.,
Zhang, G.,
Jiang, S.,
Ye, J.,
Chi, C.,
Tian, J.,
Compactly Supported Radial Basis Function-Based Meshless Method for
Photon Propagation Model of Fluorescence Molecular Tomography,
MedImg(36), No. 2, February 2017, pp. 366-373.
IEEE DOI
1702
Finite element analysis
BibRef
Labouesse, S.,
Negash, A.,
Idier, J.,
Bourguignon, S.,
Mangeat, T.,
Liu, P.,
Sentenac, A.,
Allain, M.,
Joint Reconstruction Strategy for Structured Illumination Microscopy
With Unknown Illuminations,
IP(26), No. 5, May 2017, pp. 2480-2493.
IEEE DOI
1704
BibRef
Earlier: A1, A8, A3, A4, A2, A6, A7, Only:
Fluorescence blind structured illumination microscopy:
A new reconstruction strategy,
ICIP16(3166-3170)
IEEE DOI
1610
Image reconstruction
BibRef
Li, J.Z.[Ji-Zhou],
Xue, F.[Feng],
Blu, T.[Thierry],
Fast and accurate three-dimensional point spread function computation
for fluorescence microscopy,
JOSA-A(34), No. 6, June 2017, pp. 1029-1034.
DOI Link
1706
Fluorescence microscopy, Three-dimensional, microscopy
BibRef
Storath, M.,
Rickert, D.,
Unser, M.,
Weinmann, A.,
Fast Segmentation From Blurred Data in 3D Fluorescence Microscopy,
IP(26), No. 10, October 2017, pp. 4856-4870.
IEEE DOI
1708
deconvolution, fluorescence, graphics processing units,
image restoration, image segmentation, optical microscopy,
parallel processing, 3D Potts model, 3D image segmentation,
3D wide field fluorescence microscopy data, data blurring,
decoupled subproblem, noncubic grid,
piecewise constant Mumford-Shah model, sequential CPU version,
space discretization, splitting approach,
BibRef
Storath, M.,
Weinmann, A.,
Fast Median Filtering for Phase or Orientation Data,
PAMI(40), No. 3, March 2018, pp. 639-652.
IEEE DOI
1802
Complexity theory, Image edge detection, MATLAB,
Optical interferometry, Robustness, Runtime, Smoothing methods,
phase data
BibRef
Wang, S.,
Arena, E.T.,
Eliceiri, K.W.,
Yuan, M.,
Automated and Robust Quantification of Colocalization in Dual-Color
Fluorescence Microscopy: A Nonparametric Statistical Approach,
IP(27), No. 2, February 2018, pp. 622-636.
IEEE DOI
1712
Biology, Correlation, Measurement, Microscopy, Robustness,
Statistical analysis, Testing, colocalization,
scan statistics
BibRef
Wang, S.,
Arena, E.T.,
Becker, J.T.,
Bement, W.M.,
Sherer, N.M.,
Eliceiri, K.W.,
Yuan, M.,
Spatially Adaptive Colocalization Analysis in Dual-Color Fluorescence
Microscopy,
IP(28), No. 9, Sep. 2019, pp. 4471-4485.
IEEE DOI
1908
Microscopy, Indexes, Testing, Proteins, Kernel, Fluorescence,
Colocalization, fluorescence microscopy, hypothesis testing,
kernel method
BibRef
Grushnikov, A.[Andrey],
Niwayama, R.[Ritsuya],
Kanade, T.[Takeo],
Yagi, Y.S.[Yasu-Shi],
3D level set method for blastomere segmentation of preimplantation
embryos in fluorescence microscopy images,
MVA(29), No. 1, January 2018, pp. 125-134.
WWW Link.
1801
BibRef
Fortun, D.,
Guichard, P.,
Hamel, V.,
Sorzano, C.O.S.,
Banterle, N.,
Gönczy, P.,
Unser, M.,
Reconstruction From Multiple Particles for 3D Isotropic Resolution in
Fluorescence Microscopy,
MedImg(37), No. 5, May 2018, pp. 1235-1246.
IEEE DOI
1805
Estimation, Image reconstruction, Image resolution, Microscopy,
Proteins, Protein localization,
pose estimation
BibRef
Vivona, L.[Letizia],
Cascio, D.[Donato],
Taormina, V.[Vincenzo],
Raso, G.[Giuseppe],
Automated approach for indirect immunofluorescence images
classification based on unsupervised clustering method,
IET-CV(12), No. 7, October 2018, pp. 989-995.
DOI Link
1809
BibRef
Samuylov, D.K.,
Székely, G.,
Paul, G.,
A Bayesian Framework for the Analog Reconstruction of Kymographs From
Fluorescence Microscopy Data,
IP(28), No. 1, January 2019, pp. 410-425.
IEEE DOI
1810
Geometry, Image reconstruction, Photometry, Microscopy,
Image resolution, Inverse problems, Analog reconstruction,
virtual microscope
BibRef
Ahmed, M.F.,
Yasar, S.,
Cho, S.H.,
A Monte Carlo Model of a Benchtop X-Ray Fluorescence Computed
Tomography System and Its Application to Validate a
Deconvolution-Based X-Ray Fluorescence Signal Extraction Method,
MedImg(37), No. 11, November 2018, pp. 2483-2492.
IEEE DOI
1811
Detectors, Photonics, X-ray imaging, Economic indicators,
II-VI semiconductor materials, Cadmium compounds, Collimators,
X-ray detector response
BibRef
Samuylov, D.K.,
Purwar, P.,
Székely, G.,
Paul, G.,
Modeling Point Spread Function in Fluorescence Microscopy With a
Sparse Gaussian Mixture: Tradeoff Between Accuracy and Efficiency,
IP(28), No. 8, August 2019, pp. 3688-3702.
IEEE DOI
1907
calibration, fluorescence, Gaussian processes,
image reconstruction, image resolution, image restoration,
virtual microscope framework
BibRef
Bentz, B.Z.,
Lin, D.,
Patel, J.A.,
Webb, K.J.,
Multiresolution Localization With Temporal Scanning for
Super-Resolution Diffuse Optical Imaging of Fluorescence,
IP(29), No. 1, 2020, pp. 830-842.
IEEE DOI
1910
Optical imaging, Spatial resolution, Neurons, Optical scattering,
Mathematical model, Super-resolution, optical imaging,
matching pursuit
BibRef
Tominaga, S.[Shoji],
Hirai, K.[Keita],
Horiuchi, T.[Takahiko],
Spectral reconstruction of fluorescent objects with mutual
illumination effects,
JOSA-A(36), No. 9, September 2019, pp. 1512-1522.
DOI Link
1912
Fluorescent markers, Fluorescent materials, Light intensity,
Liquid crystal filters, Reconstruction algorithms, Spectral imaging
BibRef
Chandler, T.[Talon],
Shroff, H.[Hari],
Oldenbourg, R.[Rudolf],
La Riviere, P.[Patrick],
Spatio-angular fluorescence microscopy I. Basic theory,
JOSA-A(36), No. 8, August 2019, pp. 1334-1345.
DOI Link
1912
Electric fields, Image processing, Imaging systems,
Imaging techniques, Optical transfer functions, Point spread function
BibRef
Chandler, T.[Talon],
Shroff, H.[Hari],
Oldenbourg, R.[Rudolf],
La Riviere, P.[Patrick],
Spatio-angular fluorescence microscopy II. Paraxial 4f imaging,
JOSA-A(36), No. 8, August 2019, pp. 1346-1360.
DOI Link
1912
Electric fields, Fourier transforms, Imaging systems,
Point spread function, Pupil, Spatial frequency
BibRef
Yi, H.[Huangjian],
Jiao, P.[Pu],
Li, X.N.[Xiao-Nan],
Peng, J.Y.[Jin-Ye],
He, X.W.[Xiao-Wei],
Three-way decision based reconstruction frame for fluorescence
molecular tomography,
JOSA-A(35), No. 11, November 2018, pp. 1814-1822.
DOI Link
1912
Anisotropic diffusion, Finite element method, Image quality,
Imaging systems, Inverse problems, Numerical simulation
BibRef
Field, J.J.[Jeffrey J.],
Wernsing, K.A.[Keith A.],
Squier, J.A.[Jeff A.],
Bartels, R.A.[Randy A.],
Three-dimensional single-pixel imaging of incoherent light with
spatiotemporally modulated illumination,
JOSA-A(35), No. 8, August 2018, pp. 1438-1449.
DOI Link
1912
Aberration compensation, Microscopy, Image formation theory,
Fluorescence microscopy, Interference microscopy, Wave propagation
BibRef
Negash, A.[Awoke],
Labouesse, S.[Simon],
Chaumet, P.C.[Patrick C.],
Belkebir, K.[Kamal],
Giovannini, H.[Hugues],
Allain, M.[Marc],
Idier, J.[Jerome],
Sentenac, A.[Anne],
Two-photon speckle illumination for super-resolution microscopy,
JOSA-A(35), No. 6, June 2018, pp. 1028-1033.
DOI Link
1912
Speckle imaging, Fluorescence microscopy,
Three-dimensional microscopy, Diffraction limit, Speckle patterns
BibRef
Jung, S.,
Kim, T.,
Lee, W.,
Kim, H.,
Kim, H.S.,
Im, H.,
Ye, S.,
Dynamic In Vivo X-ray Fluorescence Imaging of Gold in Living Mice
Exposed to Gold Nanoparticles,
MedImg(39), No. 2, February 2020, pp. 526-533.
IEEE DOI
2002
Cameras, Economic indicators, Photonics, Collimators, X-ray imaging,
In vivo, X-ray fluorescence, pinhole, gold nanoparticles, in vivo,
molecular imaging
BibRef
Zhu, B.,
Kwon, S.,
Rasmussen, J.C.,
Litorja, M.,
Sevick-Muraca, E.M.,
Comparison of NIR Versus SWIR Fluorescence Image Device Performance
Using Working Standards Calibrated With SI Units,
MedImg(39), No. 4, April 2020, pp. 944-951.
IEEE DOI
2004
Molecular and cellular imaging, optical imaging/OCT/DOT,
evaluation and performance, system design, validation
BibRef
Chow, J.C.K.,
Boyd, S.K.,
Lichti, D.D.,
Ronsky, J.L.,
Robust Self-Supervised Learning of Deterministic Errors in
Single-Plane (Monoplanar) and Dual-Plane (Biplanar) X-Ray Fluoroscopy,
MedImg(39), No. 6, June 2020, pp. 2051-2060.
IEEE DOI
2006
Calibration, photogrammetry, X-ray, fluoroscopy
BibRef
Bentz, B.Z.,
Mahalingam, S.M.,
Ysselstein, D.,
Montenegro, P.C.,
Cannon, J.R.,
Rochet, J.,
Low, P.S.,
Webb, K.J.,
Localization of Fluorescent Targets in Deep Tissue With Expanded Beam
Illumination for Studies of Cancer and the Brain,
MedImg(39), No. 7, July 2020, pp. 2472-2481.
IEEE DOI
2007
Mathematical model, Radio frequency, Nonhomogeneous media, Imaging,
Detectors, Brain modeling, Tumors, Fluorescence imaging,
inverse problems
BibRef
Mukherjee, S.,
Gonzalez-Gomez, C.,
Danglot, L.,
Lagache, T.,
Olivo-Marin, J.,
Generalizing the Statistical Analysis of Objects' Spatial Coupling in
Bioimaging,
SPLetters(27), 2020, pp. 1085-1089.
IEEE DOI
2007
Spatial statistics, colocalization, Ripley's K-function, coupling,
fluorescence microscopy, level sets
BibRef
Dai, Q.Q.[Qi-Qin],
Chopp, H.,
Pouyet, E.[Emeline],
Cossairt, O.[Oliver],
Walton, M.[Marc],
Katsaggelos, A.K.[Aggelos K.],
Adaptive Image Sampling Using Deep Learning and Its Application on
X-Ray Fluorescence Image Reconstruction,
MultMed(22), No. 10, October 2020, pp. 2564-2578.
IEEE DOI
2009
Image reconstruction, Image sampling, Imaging, X-ray imaging,
Machine learning, Spatial resolution, Adaptive sampling, inpainting
BibRef
Dai, Q.Q.[Qi-Qin],
Pouyet, E.[Emeline],
Cossairt, O.[Oliver],
Walton, M.[Marc],
Casadio, F.[Francesca],
Katsaggelos, A.K.[Aggelos K.],
X-Ray fluorescence image super-resolution using dictionary learning,
IVMSP16(1-5)
IEEE DOI
1608
Dictionaries
BibRef
Meng, H.,
Gao, Y.,
Yang, X.,
Wang, K.,
Tian, J.,
K-Nearest Neighbor Based Locally Connected Network for Fast
Morphological Reconstruction in Fluorescence Molecular Tomography,
MedImg(39), No. 10, October 2020, pp. 3019-3028.
IEEE DOI
2010
Image reconstruction, Photonics, Fluorescence, Inverse problems,
Surface reconstruction, In vivo, Surface morphology,
brain
BibRef
Kim, D.S.[Dong Sik],
Lee, E.[Eunae],
Measurement of the Lag Correction Factor in Low-Dose Fluoroscopic
Imaging,
MedImg(40), No. 6, June 2021, pp. 1661-1672.
IEEE DOI
2106
Detectors, X-rays, Logic gates, Heuristic algorithms,
Thin film transistors, Electron tubes, Imaging, Exposure leak,
lag correction factor
BibRef
Andrle, A.[Anna],
Farchmin, N.[Nando],
Hagemann, P.[Paul],
Heidenreich, S.[Sebastian],
Soltwisch, V.[Victor],
Steidl, G.[Gabriele],
Invertible Neural Networks Versus MCMC for Posterior Reconstruction in
Grazing Incidence X-ray Fluorescence,
SSVM21(528-539).
Springer DOI
2106
BibRef
Kromp, F.[Florian],
Fischer, L.[Lukas],
Bozsaky, E.[Eva],
Ambros, I.M.[Inge M.],
Dörr, W.[Wolfgang],
Beiske, K.[Klaus],
Ambros, P.F.[Peter F.],
Hanbury, A.[Allan],
Taschner-Mandl, S.[Sabine],
Evaluation of Deep Learning Architectures for Complex
Immunofluorescence Nuclear Image Segmentation,
MedImg(40), No. 7, July 2021, pp. 1934-1949.
IEEE DOI
2107
Image segmentation, Computer architecture, Deep learning,
Microscopy, Microprocessors, Training, Task analysis,
nuclear image segmentation
BibRef
Li, R.Q.[Rui-Qi],
Xie, X.L.[Xiao-Liang],
Zhou, X.H.[Xiao-Hu],
Liu, S.Q.[Shi-Qi],
Ni, Z.L.[Zhen-Liang],
Zhou, Y.J.[Yan-Jie],
Bian, G.B.[Gui-Bin],
Hou, Z.G.[Zeng-Guang],
Real-Time Multi-Guidewire Endpoint Localization in Fluoroscopy Images,
MedImg(40), No. 8, August 2021, pp. 2002-2014.
IEEE DOI
2108
Location awareness, Surgery, Instruments, Task analysis, Detectors,
Real-time systems, Retina, Guidewire endpoint,
surgical instrument
BibRef
Lee, J.B.[Jung-Bin],
Kim, S.H.[Seong-Han],
Kim, J.[Jeongho],
Son, B.J.[Byeong Jae],
Yoon, C.H.[Chang Ho],
Kim, H.K.[Hong Kyun],
Kim, K.H.[Ki Hean],
Moxifloxacin-Based Extended Depth-of-Field Fluorescence Microscopy
for Real-Time Conjunctival Goblet Cell Examination,
MedImg(41), No. 8, August 2022, pp. 2004-2008.
IEEE DOI
2208
Imaging, Microscopy, Lenses, Mice, Mirrors, Fluorescence, Standards,
Extended depth-of-field, fluorescence microscopy,
ocular surface diseases
BibRef
Berker, Y.[Yannick],
ElHarouni, D.[Dina],
Peterziel, H.[Heike],
Fiesel, P.[Petra],
Witt, O.[Olaf],
Oehme, I.[Ina],
Schlesner, M.[Matthias],
Oppermann, S.[Sina],
Patient-by-Patient Deep Transfer Learning for Drug-Response Profiling
Using Confocal Fluorescence Microscopy of Pediatric Patient-Derived
Tumor-Cell Spheroids,
MedImg(41), No. 12, December 2022, pp. 3981-3999.
IEEE DOI
2212
Drugs, Cancer, Image segmentation, Computer architecture,
Microprocessors, Tumors, Molecular and cellular imaging, translation
BibRef
Wu, C.P.[Chuan-Peng],
Li, L.[Liang],
First Demonstration of Compton Camera Used for X-Ray Fluorescence
Imaging,
MedImg(42), No. 5, May 2023, pp. 1314-1324.
IEEE DOI
2305
Photonics, Cameras, Imaging, X-ray imaging, Scattering, Detectors,
Image reconstruction, Compton camera, X-ray fluorescence (XRF),
Timepix3 detector
BibRef
Chen, G.[Ge],
Wang, J.J.[Jian-Jun],
Wang, H.L.[Hai-Lin],
Wen, J.M.[Jin-Ming],
Gao, Y.[Yi],
Xu, Y.J.[Yong-Jian],
Fluorescence Microscopy Images Denoising Via Deep Convolutional
Sparse Coding,
SP:IC(117), 2023, pp. 117003.
Elsevier DOI
2308
Deep convolutional neural network,
Fluorescence microscopy images denoising, Deep learning
BibRef
Huang, L.J.[Luo-Jie],
Liu, Y.K.[Yi-Kang],
Chen, L.[Li],
Chen, E.Z.[Eric Z.],
Chen, X.[Xiao],
Sun, S.[Shanhui],
Robust Landmark-Based Stent Tracking in X-ray Fluoroscopy,
ECCV22(XXII:201-216).
Springer DOI
2211
BibRef
Ahmad, A.[Ali],
Frindel, C.[Carole],
Rousseau, D.[David],
Sorting cells from fluorescent markers organization in confocal
microscopy: 3D versus 2D images,
IPTA20(1-6)
IEEE DOI
2206
Microscopy, Organizations, Fluorescence, Task analysis, Lenses,
Confocal microscopy, fluorescent markers organization, texture,
point spread function
BibRef
Cooke, C.L.[Colin L.],
Kong, F.[Fanjie],
Chaware, A.[Amey],
Zhou, K.C.[Kevin C.],
Kim, K.[Kanghyun],
Xu, R.[Rong],
Ando, D.M.[D. Michael],
Yang, S.J.[Samuel J.],
Konda, P.C.[Pavan Chandra],
Horstmeyer, R.[Roarke],
Physics-Enhanced Machine Learning for Virtual Fluorescence Microscopy,
ICCV21(3783-3793)
IEEE DOI
2203
Training, Optical microscopy, Microscopy, Lighting, Fluorescence,
Optical fiber networks, Optical imaging, Medical, biological,
Vision applications and systems
BibRef
Maksoud, S.,
Zhao, K.,
Hobson, P.,
Jennings, A.,
Lovell, B.C.,
SOS: Selective Objective Switch for Rapid Immunofluorescence Whole
Slide Image Classification,
CVPR20(3861-3870)
IEEE DOI
2008
Feature extraction, Spatial resolution, Switches, Task analysis,
Training, Protocols
BibRef
Sekh, A.A.,
Opstad, I.S.[I. Sundvor],
Birgisdottir, Ĺ.B.,
Myrmel, T.,
Ahluwalia, B.S.,
Agarwal, K.,
Prasad, D.K.,
Learning Nanoscale Motion Patterns of Vesicles in Living Cells,
CVPR20(14011-14020)
IEEE DOI
2008
Microscopy, Nanoscale devices, Nanobioscience, Videos, Fluorescence,
Tracking, Optical microscopy
BibRef
Zhang, Y.[Yide],
Zhu, Y.[Yinhao],
Nichols, E.[Evan],
Wang, Q.[Qingfei],
Zhang, S.Y.[Si-Yuan],
Smith, C.[Cody],
Howard, S.[Scott],
A Poisson-Gaussian Denoising Dataset With Real Fluorescence Microscopy
Images,
CVPR19(11702-11710).
IEEE DOI
2002
BibRef
Koyamatsu, K.[Koji],
Hidaka, D.[Daichi],
Okabe, T.[Takahiro],
Lensch, H.P.A.[Hendrik P. A.],
Reflective and Fluorescent Separation Under Narrow-Band Illumination,
CVPR19(7569-7577).
IEEE DOI
2002
BibRef
Li, D.,
Barbu, A.,
Training a CNN for Guidewire Detection,
ICIP19(2214-2218)
IEEE DOI
1910
guidewire detection, fluoroscopy, convo-lutional neural networks,
spherical quadrature filters
BibRef
Sluzewski, M.F.[M. Filip],
Tvrdik, P.[Petr],
Acton, S.T.[Scott T.],
Segmentation of Cortical Spreading Depression Wavefronts Through
Local Similarity Metric,
ICIP19(1485-1489)
IEEE DOI
1910
Biomedical Image Analysis, Image and Video Segmentation,
Microscopy, Neuroimaging
BibRef
Maka, M.,
Necasová, T.,
Wiesner, D.,
Sorokin, D.V.,
Peterlík, I.,
Ulman, V.,
Svoboda, D.,
Toward Robust Fully 3D Filopodium Segmentation and Tracking in
Time-Lapse Fluorescence Microscopy,
ICIP19(819-823)
IEEE DOI
1910
Benchmark dataset, synthetic image data, filopodium segmentation,
filopodium tracking
BibRef
Shao, H.,
Wang, Y.,
Chen, Y.,
A Two-Phase Segmentation Method for Drosophila Olfactory Glomeruli,
ICIP19(265-269)
IEEE DOI
1910
olfactory glomerulus, confocal fluorescence image,
pseudo-background, segmentation.
BibRef
Abreu, A.,
Frenoist, F.X.,
Valitutti, S.,
Brousset, P.,
Denčfle, P.,
Naegel, B.,
Wemmert, C.,
Model-based graph segmentation in 2-D fluorescence microsecopy images,
ICPR18(3844-3849)
IEEE DOI
1812
Image segmentation, Vegetation, Clustering algorithms,
Task analysis, Image edge detection, Microscopy, Forestry
BibRef
Abousamra, S.,
Adar, S.,
Elia, N.,
Shilkrot, R.,
Localization and Tracking in 4D Fluorescence Microscopy Imagery,
Microscopy18(2371-23718)
IEEE DOI
1812
Microscopy, Bridges,
Task analysis, Embryo, Image segmentation
BibRef
Asano, Y.[Yuta],
Meguro, M.[Misaki],
Wang, C.[Chao],
Lam, A.[Antony],
Zheng, Y.Q.[Yin-Qiang],
Okabe, T.[Takahiro],
Sato, I.[Imari],
Coded Illumination and Imaging for Fluorescence Based Classification,
ECCV18(VIII: 511-526).
Springer DOI
1810
BibRef
On, V.,
Zahedi, A.,
Bhanu, B.,
3D Reconstruction of Phase Contrast Images Using Focus Measures,
ICIP18(101-105)
IEEE DOI
1809
Fluorescence, Microscopy,
Regression tree analysis, Lung, Image segmentation,
Regression
BibRef
Levine, J.,
Grangetto, M.,
Varrecchia, M.,
Olmo, G.,
Detection and Tracking of Astral Microtubules in Fluorescence
Microscopy Images,
ICIP18(361-365)
IEEE DOI
1809
Microscopy, Standards, Image segmentation, Signal to noise ratio,
Heuristic algorithms, Fluorescence, Drugs,
microtubules
BibRef
Nourbakhsh, F.,
Abdeladim, L.,
Clavreul, S.,
Loulier, K.,
Beaurepaire, E.,
Livet, J.,
Chessel, A.,
Neural Cell Segmentation in Large-Scale 3D Color Fluorescence
Microscopy Images for Developemental Neuroscience,
ICIP18(3828-3832)
IEEE DOI
1809
Image segmentation, Neurons,
Computer architecture, Microscopy, Microprocessors,
segmentation
BibRef
Feng, Y.,
Chai, X.,
Ba, Q.,
Yang, G.,
Quality Assessment of Synthetic Fluorescence Microscopy Images for
Image Segmentation,
ICIP19(814-818)
IEEE DOI
1910
Quality assessment, synthetic image, fluorescence microscopy,
generative adversarial network, image segmentation
BibRef
Chai, X.,
Ba, Q.,
Yang, G.,
Characterizing Robustness and Sensitivity of Convolutional Neural
Networks in Segmentation of Fluorescence Microscopy Images,
ICIP18(3838-3842)
IEEE DOI
1809
Image segmentation, Robustness, Sensitivity, Microscopy,
Active appearance model, Biology, Training, Segmentation,
mitochondria
BibRef
Wu, L.M.[Li-Ming],
Han, S.[Shuo],
Chen, A.[Alain],
Salama, P.[Paul],
Dunn, K.W.[Kenneth W.],
Delp, E.J.[Edward J.],
RCNN-SliceNet: A Slice and Cluster Approach for Nuclei Centroid
Detection in Three-Dimensional Fluorescence Microscopy Images,
CVMI21(3750-3760)
IEEE DOI
2109
Location awareness, Training, Solid modeling, Image segmentation,
Microscopy, Object detection
BibRef
Fu, C.,
Lee, S.,
Ho, D.J.,
Han, S.[Shuo],
Salama, P.[Paul],
Dunn, K.W.[Kenneth W.],
Delp, E.J.[Edward J.],
Three Dimensional Fluorescence Microscopy Image Synthesis and
Segmentation,
Microscopy18(2302-23028)
IEEE DOI
1812
Image segmentation, Microscopy,
Solid modeling, Mathematical model
BibRef
Ho, D.J.,
Fu, C.,
Salama, P.[Paul],
Dunn, K.W.[Kenneth W.],
Delp, E.J.[Edward J.],
Nuclei Segmentation of Fluorescence Microscopy Images Using Three
Dimensional Convolutional Neural Networks,
Microscopy17(834-842)
IEEE DOI
1709
Electron microscopy, Fluorescence, Image segmentation,
Training, Two, dimensional, displays
BibRef
Lorenz, K.S.[Kevin S.],
Salama, P.[Paul],
Dunn, K.W.[Kenneth W.],
Delp, E.J.[Edward J.],
Three dimensional segmentation of fluorescence microscopy images
using active surfaces,
ICIP13(1153-1157)
IEEE DOI
1402
Active contours
BibRef
Osokin, A.[Anton],
Chessel, A.[Anatole],
Carazo Salas, R.E.[Rafael E.],
Vaggi, F.[Federico],
GANs for Biological Image Synthesis,
ICCV17(2252-2261)
IEEE DOI
1802
Generative Adversarial Networks.
Synthesis of these images.
biomedical optical imaging, cellular biophysics,
medical image processing, optical microscopy, proteins, GAN,
BibRef
Aydin, A.S.,
Dubey, A.,
Dovrat, D.,
Aharoni, A.,
Shilkrot, R.,
CNN Based Yeast Cell Segmentation in Multi-modal Fluorescent
Microscopy Data,
Microscopy17(753-759)
IEEE DOI
1709
Computer architecture, DNA, Image segmentation, Lighting,
Microprocessors, Microscopy
BibRef
Gupta, A.[Anindya],
Suveer, A.[Amit],
Lindblad, J.[Joakim],
Dragomir, A.[Anca],
Sintorn, I.M.[Ida-Maria],
Sladoje, N.[Nataa],
Convolutional Neural Networks for False Positive Reduction of
Automatically Detected Cilia in Low Magnification TEM Images,
SCIA17(I: 407-418).
Springer DOI
1706
BibRef
Kondratev, A.Y.[Alexandr Y.],
Sorokin, D.V.[Dmitry V.],
Automatic detection of laser-induced structures in live cell
fluorescent microscopy images using snakes with geometric constraints,
ICPR16(331-336)
IEEE DOI
1705
Active contours, Algorithm design and analysis, Bleaching,
Feature extraction, Image registration, Image sequences, Microscopy
BibRef
Holden, M.[Mark],
Intramolecular FRET Efficiency Measures for Time-Lapse Fluorescence
Microscopy Images,
ACIVS16(105-116).
Springer DOI
1611
BibRef
Smal, I.[Ihor],
Meijering, E.[Erik],
Poisson Point Processes for Solving Stochastic Inverse Problems in
Fluorescence Microscopy,
BioImage16(I: 326-338).
Springer DOI
1611
BibRef
Puybareau, E.,
Talbot, H.,
Bequignon, E.,
Louis, B.,
Pelle, G.,
Papon, J.F.,
Coste, A.,
Najman, L.,
Automating the measurement of physiological parameters:
A case study in the image analysis of cilia motion,
ICIP16(1240-1244)
IEEE DOI
1610
Biomedical measurement
BibRef
Yu, Y.,
Wang, J.,
Acton, S.T.,
Automatic detection of direct radiation for digital fluoroscopy
optimization,
ICIP16(3379-3383)
IEEE DOI
1610
Feature extraction
BibRef
Ohara, N.,
Zheng, Y.,
Sato, I.,
Nakamura, T.,
Yamaguchi, M.,
Simultaneous linear separation and unmixing of fluorescent and
reflective components from a single hyperspectral image,
ICIP16(4344-4348)
IEEE DOI
1610
Decision support systems
BibRef
Craciun, P.,
Zerubia, J.B.[Josiane B.],
Stochastic geometry for multiple object tracking in fluorescence
microscopy,
ICIP16(444-448)
IEEE DOI
1610
Biological system modeling
BibRef
Al-Durgham, K.[Kaleel],
Lichti, D.D.[Derek D.],
Kuntze, G.[Gregor],
Sharma, G.[Gulshan],
Ronsky, J.[Janet],
Toward an Automatic Calibration of Dual Fluoroscopy Imaging Systems,
ISPRS16(B5: 757-764).
DOI Link
1610
BibRef
Koos, K.,
Molnar, J.,
Horvath, P.,
DIC Microscopy Image Reconstruction Using a Novel Variational
Framework,
DICTA15(1-7)
IEEE DOI
1603
image reconstruction
BibRef
Samak, A.,
Wiliem, A.,
Hobson, P.,
Walsh, M.,
Ditchmen, T.,
Troskie, A.,
Barksdale, S.,
Edwards, R.,
Jennings, A.,
Lovell, B.C.,
An Optimization Approach to Scanning Skin Direct Immunofluorescence
Specimens,
DICTA15(1-8)
IEEE DOI
1603
fluorescence
BibRef
Gharipour, A.,
Liew, A.W.C.,
A Multi-Kernel Local Level Set Image Segmentation Algorithm for
Fluorescence Microscopy Images,
DICTA15(1-5)
IEEE DOI
1603
BibRef
And:
Level Set Based Segmentation of Cell Nucleus in Fluorescence
Microscopy Images Using Correntropy-Based K-Means Clustering,
DICTA15(1-5)
IEEE DOI
1603
fluorescence
biology computing
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Aichert, A.[André],
Wang, J.[Jian],
Schaffert, R.[Roman],
Dörfler, A.[Arnd],
Hornegger, J.[Joachim],
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Epipolar Consistency in Fluoroscopy for Image-Based Tracking,
BMVC15(xx-yy).
DOI Link
1601
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Amiot, C.,
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Fluorosocopic sequence denoising using a motion compensated
multi-scale temporal filtering,
ICIP15(691-695)
IEEE DOI
1512
Fluoroscopic sequences
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Zhang, F.[Fan],
Cai, W.D.[Wei-Dong],
Song, Y.[Yang],
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Morgan, L.[Lucy],
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Buddle, L.[Lachlan],
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Beating cilia identification in fluorescence microscope images for
accurate CBF measurement,
ICIP15(4496-4500)
IEEE DOI
1512
Beating cilia
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Lihavainen, E.[Eero],
Mäkelä, J.[Jarno],
Spelbrink, J.N.[Johannes N.],
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Detecting and Tracking the Tips of Fluorescently Labeled Mitochondria
in U2OS Cells,
CIAP15(II:363-372).
Springer DOI
1511
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Shi, C.[Chenyu],
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Automatic Differentiation of u- and n-serrated Patterns in Direct
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CAIP15(I:513-521).
Springer DOI
1511
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Jensen, C.B.[Casper Bo],
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1506
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Erdil, E.,
Yagci, A.M.,
Argunsah, A.O.,
Ramiro-Cortes, Y.,
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Israely, I.,
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A tool for automatic dendritic spine detection and analysis. Part I:
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IPTA12(167-171)
IEEE DOI
1503
two-photon fluorescence microscopy images.
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Majtner, T.[Tomas],
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Texture analysis using 3D Gabor features and 3D MPEG-7 Edge Histogram
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IC3D14(1-7)
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1503
Histograms
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Majtner, T.[Toma],
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RSURF: The Efficient Texture-Based Descriptor for Fluorescence
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ICPR14(1194-1199)
IEEE DOI
1412
Accuracy
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Tominaga, S.[Shoji],
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Measurement and Modeling of Bidirectional Characteristics of
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ICISP14(35-42).
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1406
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Keuper, M.[Margret],
Schmidt, T.[Thorsten],
Temerinac-Ott, M.[Maja],
Padeken, J.[Jan],
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Blind Deconvolution of Widefield Fluorescence Microscopic Data by
Regularization of the Optical Transfer Function (OTF),
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OTF regularization; blind deconvolution; widefield microscopy
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Lam, A.[Antony],
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Spectral Modeling and Relighting of Reflective-Fluorescent Scenes,
CVPR13(1452-1459)
IEEE DOI
1309
fluorescence; hyperspectral imaging; relighting
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Neves, J.C.[Joăo C.],
Castro, H.[Helena],
Proença, H.[Hugo],
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Automatic Annotation of Leishmania Infections in Fluorescence
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ICIAR13(613-620).
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1307
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Tracking Growing Axons by Particle Filtering in 3D + t Fluorescent
Two-Photon Microscopy Images,
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1304
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Roudot, P.[Philippe],
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IEEE DOI
1302
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Comparison of 3D Texture-Based Image Descriptors in Fluorescence
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IWCIA14(186-195).
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1405
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Earlier:
Extension of Tamura Texture Features for 3D Fluorescence Microscopy,
3DIMPVT12(301-307).
IEEE DOI
1212
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Zhang, D.,
Muller, J.p.,
Lavender, S.,
Walton, D.,
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Fluorescent Analysis of Photosynthetic Microbes and Polycyclic Aromatic
Hydrocarbons Linked To Optical Remote Sensing,
ISPRS12(XXXIX-B8:555-559).
DOI Link
1209
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Jimenez, M.J.,
Rucco, M.,
Vicente-Munuera, P.,
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Topological Data Analysis for Self-organization of Biological Tissues,
IWCIA17(229-242).
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1706
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Sáez, A.[Aurora],
Montero-Sánchez, A.[Adoración],
Escudero, L.M.[Luis M.],
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Serrano, C.[Carmen],
Segmentation of Muscle Fibres in Fluorescence Microscopy Images,
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Springer DOI
1206
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Liang, L.[Liang],
Xu, Y.K.[Ying-Ke],
Shen, H.Y.[Hong-Ying],
de Camilli, P.[Pietro],
Toomre, D.K.[Derek K.],
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Automatic detection of subcellular particles in fluorescence microscopy
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MMBIA12(161-166).
IEEE DOI
1203
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Held, C.[Christian],
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Comparison of Methods for Splitting of Touching and Overlapping
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ICIAR12(II: 456-464).
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1206
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Hiware, S.[Sameer],
Porwal, P.[Pradyot],
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ICIP11(2037-2040).
IEEE DOI
1201
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Xiong, W.[Wei],
Chia, S.C.[Shue-Ching],
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Automated nuclei clump decomposition for image analysis in neuronal
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ICIP11(1577-1580).
IEEE DOI
1201
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Matuszewski, B.J.,
Murphy, M.F.,
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Histace, A.,
Precioso, F.,
Segmentation of cellular structures in actin tagged fluorescence
confocal microscopy images,
ICIP11(3081-3084).
IEEE DOI
1201
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ICIP11(3085-3088).
IEEE DOI
1201
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Chalfoun, J.[Joe],
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Peskin, A.P.[Adele P.],
Elliott, J.T.[John T.],
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A Human Inspired Local Ratio-Based Algorithm for Edge Detection in
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ISVC10(I: 23-34).
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1011
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Lu, Y.T.[Yan-Ting],
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Automated Cell Phase Classification for Zebrafish Fluorescence
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ICPR10(2584-2587).
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1008
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Lesko, M.[Milan],
Kato, Z.[Zoltan],
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Live Cell Segmentation in Fluorescence Microscopy via Graph Cut,
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IEEE DOI
1008
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Chenouard, N.[Nicolas],
Buisson, J.[Johanna],
Bloch, I.[Isabelle],
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Curvelet analysis of kymograph for tracking bi-directional particles in
fluorescence microscopy images,
ICIP10(3657-3660).
IEEE DOI
1009
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Wu, L.S.[Le-Shin],
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A Hypothesis Testing Approach for Fluorescent Blob Identification,
ICPR10(2476-2479).
IEEE DOI
1008
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Wang, K.[Kui],
Ng, S.K.[Shu-Kay],
McLachlan, G.J.[Geoffrey J.],
Multivariate Skew t-Mixture Models:
Applications to Fluorescence-Activated Cell Sorting Data,
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IEEE DOI
0912
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Krämer, P.,
Boto, F.,
Wald, D.,
Bessy, F.,
Paloc, C.,
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Letamendia, A.,
Ibarbia, I.,
Holgado, O.,
Virto, J.M.,
Comparison of Segmentation Algorithms for the Zebrafish Heart in
Fluorescent Microscopy Images,
ISVC09(II: 1041-1050).
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0911
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Soda, P.[Paolo],
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Analysis and Classification of Crithidia Luciliae Fluorescent Images,
CIAP09(558-566).
Springer DOI
0909
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Soda, P.[Paolo],
Iannello, G.[Giulio],
Decomposition Methods and Learning Approaches for Imbalanced Dataset:
An Experimental Integration,
ICPR10(3117-3120).
IEEE DOI
1008
BibRef
Pölönen, H.[Harri],
Tohka, J.[Jussi],
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Automatic Quantification of Fluorescence from Clustered Targets in
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SCIA09(667-675).
Springer DOI
0906
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Helmuth, J.A.[Jo A.],
Sbalzarini, I.F.[Ivo F.],
Deconvolving Active Contours for Fluorescence Microscopy Images,
ISVC09(I: 544-553).
Springer DOI
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Tracking Cells, Deformations, Motion, Real-Time Analysis .