21.5.1 Eye, Cornea, Corneal Images

Chapter Contents (Back)
Cornea. Corneal Images. Eye.

Hachicha, A., Simon, S., Samson, J., Hanna, K.,
The use of gray-level information and fitting techniques for precise measurement of corneal curvature and thickness,
CVGIP(47), No. 2, August 1989, pp. 131-164.
Elsevier DOI 0501
BibRef

Cambier, J.L.[James L.], Strods, S.J.[Salvins J.],
Method and apparatus for obtaining the topography of an object,
US_Patent5,159,361, Oct 27, 1992
WWW Link. Specifically the cornea. BibRef 9210

Zapater, V., Martinez-Costa, L., Ayala, G.,
A granulometric analysis of specular microscopy images of human corneal endothelia,
CVIU(97), No. 3, March 2005, pp. 297-314.
Elsevier DOI 0412
BibRef

Zapater, V., Martínez-Costa, L., Ayala, G.,
Classifying human endothelial cells based on individual granulometric size distributions,
IVC(20), No. 11, September 2002, pp. 783-791.
Elsevier DOI 0209
BibRef

Ayala, G., Díaz, M.E., Martínez-Costa, L.,
Granulometric moments and corneal endothelium status,
PR(34), No. 6, June 2001, pp. 1219-1227.
Elsevier DOI 0103
BibRef

Gutiérrez, J., Ayala, G., Díaz, M.E.,
Set Descriptors for Visual Evaluation of Human Corneal Endothelia,
CVIU(84), No. 2, November 2001, pp. 249-263.
DOI Link 0203
BibRef

Sebastian, R., Díaz, E., Ayala, G., Díaz, M.E., Zoncu, R., Toomre, D.,
Studying endocytosis in space and time by means of temporal Boolean models,
PR(39), No. 11, November 2006, pp. 2175-2185.
Elsevier DOI 0608
Temporal Boolean model; Endocytosis; Clathrin; Total internal reflection fluorescence microscopy (TIRFM)
See also Analysis of Spatially and Temporally Overlapping Events with Application to Image Sequences. BibRef

Tang, M., Shekhar, R., Huang, D.,
Mean Curvature Mapping for Detection of Corneal Shape Abnormality,
MedImg(24), No. 3, March 2005, pp. 424-428.
IEEE Abstract. 0501
BibRef

King-Smith, P.E.[P. Ewen], Fink, B.A.[Barbara A.], Nichols, J.J.[Jason J.], Nichols, K.K.[Kelly K.], Hill, R.M.[Richard M.],
Interferometric imaging of the full thickness of the precorneal tear film,
JOSA-A(23), No. 9, September 2006, pp. 2097-2104.
WWW Link. 0610
BibRef

Wu, D.[Dijia], Boyer, K.L.[Kim L.], Nichols, J.J.[Jason J.], King-Smith, P.E.[Peter E.],
Texture based prelens tear film segmentation in interferometry images,
MVA(21), No. 3, April 2010, pp. xx-yy.
Springer DOI 1003
BibRef

Wu, D.[Dijia], Boyer, K.L.[Kim L.],
Markov random field based phase demodulation of interferometric images,
CVIU(115), No. 6, June 2011, pp. 759-770.
Elsevier DOI 1104
BibRef
Earlier:
Sign ambiguity resolution for phase demodulation in interferometry with application to prelens tear film analysis,
CVPR10(2807-2814).
IEEE DOI 1006
Sign ambiguity; 2[pi] ambiguity; Phase unwrapping; Phase demodulation; Fringe pattern analysis; Interferometric imaging BibRef

Shih, C.C.A.[Cho-Chi-Ang], Huang, C.C.[Chih-Chung], Zhou, Q.[Qifa], Shung, K.K.,
High-Resolution Acoustic-Radiation-Force-Impulse Imaging for Assessing Corneal Sclerosis,
MedImg(32), No. 7, 2013, pp. 1316-1324.
IEEE DOI 1307
biological tissues BibRef

Polette, A., Mari, J.L., Brunette, I., Meunier, J.,
Comparison of quasi-spherical surfaces: Application to corneal biometry,
IET-Bio(5), No. 3, 2016, pp. 212-219.
DOI Link 1609
biometrics (access control) BibRef
Earlier:
Comparison of quasi-spherical surfaces using spherical harmonics: Application to corneal biometry,
IPTA14(1-5)
IEEE DOI 1503
iris recognition BibRef

Iyer, R.V., Nasrin, F., See, E., Mathews, S.,
Smoothing Splines on Unit Ball Domains with Application to Corneal Topography,
MedImg(36), No. 2, February 2017, pp. 518-526.
IEEE DOI 1702
Cornea BibRef

Pavlatos, E., Chen, H., Clayson, K., Pan, X., Liu, J.,
Imaging Corneal Biomechanical Responses to Ocular Pulse Using High-Frequency Ultrasound,
MedImg(37), No. 2, February 2018, pp. 663-670.
IEEE DOI 1802
Biomechanics, Cornea, Kernel, Radio frequency, Speckle, Strain, Ultrasonic imaging, Eye, biomechanical modeling, ultrasound, validation BibRef

Vigueras-Guillén, J.P.[Juan P.], Andrinopoulou, E., Engel, A.[Angela], Lemij, H.G.[Hans G.], van Rooij, J.[Jeroen], Vermeer, K.A.[Koenraad A.], van Vliet, L.J.[Lucas J.],
Corneal Endothelial Cell Segmentation by Classifier-Driven Merging of Oversegmented Images,
MedImg(37), No. 10, October 2018, pp. 2278-2289.
IEEE DOI 1810
BibRef
Earlier: A1, A3, A4, A5, A6, A7, Only:
Improved Accuracy and Robustness of a Corneal Endothelial Cell Segmentation Method Based on Merging Superpixels,
ICIAR18(631-638).
Springer DOI 1807
Microscopy, Image segmentation, Cornea, In vivo, Support vector machines, Optical microscopy, Merging, support vector machines BibRef

Nasrin, F., Iyer, R.V., Mathews, S.M.,
Simultaneous Estimation of Corneal Topography, Pachymetry, and Curvature,
MedImg(37), No. 11, November 2018, pp. 2463-2473.
IEEE DOI 1811
Surface topography, Cornea, Splines (mathematics), Optical imaging, Measurement, Smoothing methods, Corneal curvature, true mean curvature BibRef

Kumar, M.[Mohit], Puhan, N.B.[Niladri B.],
RANSAC lens boundary feature based kernel SVM for transparent contact lens detecTion,
IET-Bio(8), No. 3, May 2019, pp. 177-184.
DOI Link 1904
BibRef

Zhao, Y.T.[Yi-Tian], Zhang, J.[Jiong], Pereira, E.[Ella], Zheng, Y.L.[Ya-Lin], Su, P.[Pan], Xie, J.Y.[Jian-Yang], Zhao, Y.F.[Yi-Fan], Shi, Y.G.[Yong-Gang], Qi, H.[Hong], Liu, J.[Jiang], Liu, Y.H.[Yong-Huai],
Automated Tortuosity Analysis of Nerve Fibers in Corneal Confocal Microscopy,
MedImg(39), No. 9, September 2020, pp. 2725-2737.
IEEE DOI 2009
BibRef
And: Corrections: MedImg(39), No. 11, November 2020, pp. 3758-3758.
IEEE DOI 2011
Biomedical imaging, Blood vessels, Microscopy, Estimation, Lighting, Retina, Corneal nerve, tortuosity, enhancement, segmentation, curvature BibRef

Wang, Y.Q.[Yi-Qian], Zhang, J.[Junkang], Cavichini, M., Bartsch, D.U.G., Freeman, W.R., Nguyen, T.Q.[Truong Q.], An, C.[Cheolhong],
Robust Content-Adaptive Global Registration for Multimodal Retinal Images Using Weakly Supervised Deep-Learning Framework,
IP(30), 2021, pp. 3167-3178.
IEEE DOI 2103
Retina, Image segmentation, Feature extraction, Image registration, Imaging, Convolution, Pipelines, Image registration, content-adaptive convolution BibRef

An, C.[Cheolhong], Wang, Y.Q.[Yi-Qian], Zhang, J.[Junkang], Nguyen, T.Q.[Truong Q.],
Self-Supervised Rigid Registration for Multimodal Retinal Images,
IP(31), 2022, pp. 5733-5747.
IEEE DOI 2209
Retina, Image segmentation, Image registration, Feature extraction, Self-supervised learning, Task analysis, Feature detection, convolutional neural network BibRef

Jameel, S.K.[Samer Kais], Aydin, S.[Sezgin], Ghaeb, N.H.[Nebras H.],
Machine Learning Techniques for Corneal Diseases Diagnosis: A Survey,
IJIG(21), No. 2 2021, pp. 2150016.
DOI Link 2105
BibRef

Wang, L.[Lei], Shen, M.X.[Mei-Xiao], Chang, Q.[Qian], Shi, C.[Ce], Chen, Y.[Yang], Zhou, Y.H.[Yu-Heng], Zhang, Y.C.[Yan-Chun], Pu, J.T.[Jian-Tao], Chen, H.[Hao],
Automated delineation of corneal layers on OCT images using a boundary-guided CNN,
PR(120), 2021, pp. 108158.
Elsevier DOI 2109
Corneal layers, OCT images, Segmentation, Convolutional neural networks BibRef

Mou, L.[Lei], Qi, H.[Hong], Liu, Y.H.[Yong-Huai], Zheng, Y.L.[Ya-Lin], Matthew, P.[Peter], Su, P.[Pan], Liu, J.[Jiang], Zhang, J.[Jiong], Zhao, Y.T.[Yi-Tian],
DeepGrading: Deep Learning Grading of Corneal Nerve Tortuosity,
MedImg(41), No. 8, August 2022, pp. 2079-2091.
IEEE DOI 2208
Feature extraction, Image segmentation, Diseases, Visualization, Diabetes, Training, Estimation, Corneal confocal microscopy, deep learning BibRef

Firat, M.[Murat], Çankaya, C.[Cem], Çinar, A.[Ahmet], Tuncer, T.[Taner],
Automatic detection of keratoconus on Pentacam images using feature selection based on deep learning,
IJIST(32), No. 5, 2022, pp. 1548-1560.
DOI Link 2209
deep learning, feature selection, keratoconus, Pentacam four maps refractive BibRef

Zhang, Y.L.[Ying-Lin], Xi, R.L.[Rui-Ling], Zeng, L.X.[Ling-Xi], Towey, D.[Dave], Bai, R.B.[Rui-Bin], Higashita, R.[Risa], Liu, J.[Jiang],
Structural Priors Guided Network for the Corneal Endothelial Cell Segmentation,
MedImg(43), No. 1, January 2024, pp. 309-320.
IEEE DOI 2401
BibRef

Rong, D.[Dingyi], Zhao, Z.Y.[Zhong-Yin], Wu, Y.[Yue], Ke, B.[Bilian], Ni, B.[Binging],
Prediction of Myopia Eye Axial Elongation With Orthokeratology Treatment via Dense I2I Based Corneal Topography Change Analysis,
MedImg(43), No. 3, March 2024, pp. 1149-1164.
IEEE DOI Code:
WWW Link. 2403
Lenses, Surfaces, Cornea, Force, Elongation, Geometry, Predictive models, Image-to-image, myopia progression control, transformer, U-Former, physics-inspired model BibRef


Wang, K.[Ke], Wang, G.Y.[Guang-Yu], Zhang, K.[Kang], Chen, T.[Ting],
An Adversarial Collaborative-Learning Approach for Corneal Scar Segmentation with Ocular Anterior Segment Photography,
ICIP21(1-5)
IEEE DOI 2201
Photography, Training, Image segmentation, Annotations, Feature extraction, Generative adversarial networks, Lesions, Adversarial BibRef

Noor, S.S.M., Michael, K., Marshall, S., Ren, J., Tschannerl, J., Kao, F.J.,
The properties of the cornea based on hyperspectral imaging: Optical biomedical engineering perspective,
WSSIP16(1-4)
IEEE DOI 1608
biomedical optical imaging BibRef

Polette, A.[Arnaud], Auvinet, E.[Edouard], Mari, J.L.[Jean-Luc], Brunette, I.[Isabelle], Meunier, J.[Jean],
Construction of a Mean Surface for the Variability Study of the Cornea,
CRV14(328-335)
IEEE DOI 1406
Accuracy BibRef

Cullen, J., Fieguth, P.W., Pounder, S., Whitear, K.,
Analysis of Corneal Images for Assessing Contact Lens Trauma,
ICIP00(Vol I: 176-179).
IEEE DOI 0008
BibRef

Ritter, N., Owens, R., Cooper, J., van Saarloos, P.P.,
Location of the pupil-iris border in slit-lamp images of the cornea,
CIAP99(740-745).
IEEE DOI 9909
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Optic Disc Location, Optic Disc Detection .


Last update:Mar 16, 2024 at 20:36:19