20.4.2.3 3-D Cell Analysis

Chapter Contents (Back)
Cells.

Fernandez-Gonzalez, R., Barcellos-Hoff, M.H., Ortiz-de-Solórzano, C.,
A Tool for the Quantitative Spatial Analysis of Complex Cellular Systems,
IP(14), No. 9, September 2005, pp. 1300-1313.
IEEE DOI 0508

See also Iterative Voting for Inference of Structural Saliency and Characterization of Subcellular Events. BibRef

Han, J.[Ju], Chang, H.[Hang], Yang, Q.[Qing], Barcellos-Hoff, M.H.[Mary Helen], Parvin, B.[Bahram],
3D Segmentation of Mammospheres for Localization Studies,
ISVC06(I: 518-527).
Springer DOI 0611
BibRef

Narasimha, R.[Rajesh], Ouyang, H.[Hua], Gray, A.[Alexander], McLaughlin, S.W.[Steven W.], Subramaniam, S.[Sriram],
Automatic joint classification and segmentation of whole cell 3D images,
PR(42), No. 6, June 2009, pp. 1067-1079.
Elsevier DOI 0902
Mitochondria; Texture features; Segmentation; Classification; Automated techniques; Machine learning; Cancer detection BibRef

Hodneland, E., Bukoreshtliev, N.V., Eichler, T.W., Tai, X.C.[Xue-Cheng], Gurke, S., Lundervold, A., Gerdes, H.H.,
A Unified Framework for Automated 3-D Segmentation of Surface-Stained Living Cells and a Comprehensive Segmentation Evaluation,
MedImg(28), No. 5, May 2009, pp. 720-738.
IEEE DOI 0905
BibRef

Zanella, C., Campana, M., Rizzi, B., Melani, C., Sanguinetti, G.R.[Gonzalo R.], Bourgine, P., Mikula, K., Peyrieras, N., Sarti, A.,
Cells Segmentation From 3-D Confocal Images of Early Zebrafish Embryogenesis,
IP(19), No. 3, March 2010, pp. 770-781.
IEEE DOI 1003
BibRef

Dufour, A.C., Liu, T.Y.[Tzu-Yu], Ducroz, C., Tournemenne, R., Cummings, B., Thibeaux, R., Guillen, N., Hero, A.O., Olivo-Marin, J.C.,
Signal Processing Challenges in Quantitative 3-D Cell Morphology: More than meets the eye,
SPMag(32), No. 1, January 2015, pp. 30-40.
IEEE DOI 1502
biomechanics BibRef

Hernandez-Herrera, P.[Paul], Montoya, F.[Fernando], Rendón-Mancha, J.M.[Juan M.], Darszon, A.[Alberto], Corkidi, G.[Gabriel],
3-D+t Human Sperm Flagellum Tracing in Low SNR Fluorescence Images,
MedImg(37), No. 10, October 2018, pp. 2236-2247.
IEEE DOI 1810
BibRef
Earlier:
Sperm Flagellum Center-Line Tracing in Fluorescence 3D+t Low SNR Stacks Using an Iterative Minimal Path Method,
ICIAR17(437-445).
Springer DOI 1706
Periodic structures, Machine learning algorithms, Signal to noise ratio, Training, segmentation BibRef

Waithe, D.[Dominic], Hailstone, M.[Martin], Lalwani, M.K.[Mukesh Kumar], Parton, R.[Richard], Yang, L.[Lu], Patient, R.[Roger], Eggeling, C.[Christian], Davis, I.[Ilan],
3-D Density Kernel Estimation for Counting in Microscopy Image Volumes Using 3-D Image Filters and Random Decision Trees,
BioImage16(I: 244-255).
Springer DOI 1611
BibRef

Lutton, E.J., Collier, S., Bretschneider, T.,
A Curvature-Enhanced Random Walker Segmentation Method for Detailed Capture of 3D Cell Surface Membranes,
MedImg(40), No. 2, February 2021, pp. 514-526.
IEEE DOI 2102
Image segmentation, Microscopy, Mathematical model, Thresholding (Imaging), Surface morphology, random walker segmentation BibRef


Agus, M., Gobbetti, E., Pintore, G., Calě, C., Schneider, J.,
WISH: efficient 3D biological shape classification through Willmore flow and Spherical Harmonics decomposition,
Microscopy20(4184-4194)
IEEE DOI 2008
Shape, Robustness, Harmonic analysis, Manifolds, Nanobioscience BibRef

Jiang, J., Kao, P., Belteton, S.A., Szymanski, D.B., Manjunath, B.S.,
Accurate 3D Cell Segmentation Using Deep Features and CRF Refinement,
ICIP19(1555-1559)
IEEE DOI 1910
Cell segmentation, convolutional neural networks, 3D U-Net, 3D watershed, conditional random field BibRef

Kang, M.S.[Mi-Sun], Kim, H.R.[Hye-Ryun], Kim, M.H.[Myoung-Hee],
Cell Classification in 3D Phase-Contrast Microscopy Images via Self-Organizing Maps,
ISVC14(II: 652-661).
Springer DOI 1501
BibRef

del Bue, A., Zanacchi, F.C., Diaspro, A.,
Super-Resolution 3D Reconstruction of Thick Biological Samples: A Computer Vision Perspective,
AccBio13(178-183)
IEEE DOI 1403
very detailed 3D descriptions of cells. Use structure of cell and distortions of light. BibRef

Ducroz, C.[Christel], Olivo-Marin, J.C.[Jean-Christophe], Dufour, A.[Alexandre],
Automatic detection of 3D cell protrusions using spherical wavelets,
ICIP13(3499-3502)
IEEE DOI 1402
3D microscopy BibRef

Elhayek, A.[Ahmed], Welk, M.[Martin], Weickert, J.[Joachim],
Simultaneous Interpolation and Deconvolution Model for the 3-D Reconstruction of Cell Images,
DAGM11(316-325).
Springer DOI 1109
BibRef

Jaeger, S.[Stefan], Palaniappan, K.[Kannappan], Casas-Delucchi, C.S.[Corella S.], Cardoso, M.C.[M. Cristina],
Classification of cell cycle phases in 3D confocal microscopy using PCNA and chromocenter features,
ICCVGIP10(412-418).
DOI Link 1111
BibRef

Jaeger, S.[Stefan], Palaniappan, K.[Kannappan], Casas-Delucchi, C.S.[Corella S.], Cardoso, M.C.[M. Cristina],
Dual Channel Colocalization for Cell Cycle Analysis Using 3D Confocal Microscopy,
ICPR10(2580-2583).
IEEE DOI 1008
BibRef

de Alarcon, P.A., Pascual-Montano, A.D., Gupta, A., Carazo, J.M.,
Modeling shape and topology of 3d images of biological specimens,
ICPR02(I: 79-82).
IEEE DOI 0211
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Histopathology, Tissue Analysis .


Last update:Nov 1, 2021 at 09:26:50