20.4.2.2 HEp-2 Cell Analysis, Human Epithelial Type 2 Cells

Chapter Contents (Back)
HEp-2. Epithelial Cells.

Velduis, J.H.[Jim H.], Brodland, G.W.[G. Wayne],
A deformable block-matching algorithm for tracking epithelial cells,
IVC(17), No. 12, October 1999, pp. 905-911.
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Foggia, P., Percannella, G.[Gennaro], Soda, P.[Paolo], Vento, M.[Mario],
Benchmarking HEp-2 Cells Classification Methods,
MedImg(32), No. 10, 2013, pp. 1878-1889.
IEEE DOI 1311
BibRef
Earlier: A2, A3, A4, Only:
Mitotic HEp-2 Cells Recognition under Class Skew,
CIAP11(II: 353-362).
Springer DOI 1109
benchmark testing BibRef

Foggia, P.[Pasquale], Percannella, G.[Gennaro], Saggese, A.[Alessia], Vento, M.[Mario],
Pattern recognition in stained HEp-2 cells: Where are we now?,
PR(47), No. 7, 2014, pp. 2305-2314.
Elsevier DOI 1404
Indirect Immunofluorescence images BibRef

Wiliem, A.[Arnold], Sanderson, C.[Conrad], Wong, Y.K.[Yong-Kang], Hobson, P.[Peter], Minchin, R.F.[Rodney F.], Lovell, B.C.[Brian C.],
Automatic classification of Human Epithelial type 2 cell Indirect Immunofluorescence images using Cell Pyramid Matching,
PR(47), No. 7, 2014, pp. 2315-2324.
Elsevier DOI 1404
Indirect Immunofluorescence tests BibRef

Wiliem, A., Wong, Y.K.[Yong-Kang], Sanderson, C., Hobson, P., Chen, S.K.[Shao-Kang], Lovell, B.C.,
Classification of Human Epithelial type 2 cell indirect immunofluoresence images via codebook based descriptors,
WACV13(95-102).
IEEE DOI 1303
BibRef

Yang, Y.[Yan], Wiliem, A.[Arnold], Alavi, A.[Azadeh], Lovell, B.C.[Brian C.], Hobson, P.[Peter],
Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns,
PR(47), No. 7, 2014, pp. 2325-2337.
Elsevier DOI 1404
BibRef
Earlier: A1, A2, A3, A5, Only:
Classification of Human Epithelial Type 2 Cell Images Using Independent Component Analysis,
ICIP13(733-737)
IEEE DOI 1402
HEp-2 cells classification. Correlation BibRef

Wiliem, A.[Arnold], Vemulapalli, R.[Raviteja], Lovell, B.C.[Brian C.],
Explicit discriminative representation for improved classification of manifold features,
PRL(80), No. 1, 2016, pp. 121-128.
Elsevier DOI 1609
Riemannian manifolds BibRef

Wiliem, A.[Arnold], Hobson, P.[Peter], Lovell, B.C.[Brian C.],
Discovering discriminative cell attributes for HEp-2 specimen image classification,
WACV14(423-430)
IEEE DOI 1406
Design automation BibRef

Chen, S.K.[Shao-Kang], Wiliem, A.[Arnold], Sanderson, C.[Conrad], Lovell, B.C.[Brian C.],
Matching image sets via adaptive multi convex hull,
WACV14(1074-1081)
IEEE DOI 1406
Complexity theory BibRef

Zhao, K.[Kun], Wiliem, A.[Arnold], Chen, S.K.[Shao-Kang], Lovell, B.C.[Brian C.],
Manifold convex hull (MACH): Satisfying a need for SPD,
ICIP16(251-255)
IEEE DOI 1610
Computational modeling BibRef

Alavi, A.[Azadeh], Wiliem, A.[Arnold], Zhao, K.[Kun], Lovell, B.C.[Brian C.], Sanderson, C.[Conrad],
Random projections on manifolds of Symmetric Positive Definite matrices for image classification,
WACV14(301-308)
IEEE DOI 1406
Covariance matrices BibRef

Snell, V., Christmas, W.J., Kittler, J.V.,
HEp-2 fluorescence pattern classification,
PR(47), No. 7, 2014, pp. 2338-2347.
Elsevier DOI 1404
BibRef
Earlier:
Texture and shape in fluorescence pattern identification for auto-immune disease diagnosis,
ICPR12(3750-3753).
WWW Link. 1302
IIF image BibRef

Faraki, M.[Masoud], Harandi, M.T.[Mehrtash T.], Wiliem, A.[Arnold], Lovell, B.C.[Brian C.],
Fisher tensors for classifying human epithelial cells,
PR(47), No. 7, 2014, pp. 2348-2359.
Elsevier DOI 1404
Riemannian manifolds BibRef

Iannello, G.[Giulio], Percannella, G.[Gennaro], Soda, P.[Paolo], Vento, M.[Mario],
Mitotic cells recognition in HEp-2 images,
PRL(45), No. 1, 2014, pp. 136-144.
Elsevier DOI 1407
Computer aided diagnosis BibRef

di Cataldo, S.[Santa], Bottino, A.[Andrea], Ul Islam, I.[Ihtesham], Vieira, T.F.[Tiago Figueiredo], Ficarra, E.[Elisa],
Subclass Discriminant Analysis of morphological and textural features for HEp-2 staining pattern classification,
PR(47), No. 7, 2014, pp. 2389-2399.
Elsevier DOI 1404
Indirect Immunofluorescence BibRef

di Cataldo, S.[Santa], Bottino, A.[Andrea], Ficarra, E.[Elisa], Macii, E.[Enrico],
Applying textural features to the classification of HEp-2 cell patterns in IIF images,
ICPR12(3349-3352).
WWW Link. 1302
BibRef

Liu, L.Q.[Ling-Qiao], Wang, L.[Lei],
HEp-2 cell image classification with multiple linear descriptors,
PR(47), No. 7, 2014, pp. 2400-2408.
Elsevier DOI 1404
HEp-2 cell BibRef

Stoklasa, R.[Roman], Majtner, T.[Tomáš], Svoboda, D.[David],
Efficient k-NN based HEp-2 cells classifier,
PR(47), No. 7, 2014, pp. 2409-2418.
Elsevier DOI 1404
HEp-2 cells BibRef

Svoboda, D.[David], Ulman, V.[Vladimír],
Towards a Realistic Distribution of Cells in Synthetically Generated 3D Cell Populations,
CIAP13(II:429-438).
Springer DOI 1309
BibRef

Shen, L.L.[Lin-Lin], Lin, J.M.[Jia-Ming], Wu, S.Y.[Sheng-Yin], Yu, S.[Shiqi],
HEp-2 image classification using intensity order pooling based features and bag of words,
PR(47), No. 7, 2014, pp. 2419-2427.
Elsevier DOI 1404
HEp-2 cell classification BibRef

Nosaka, R.[Ryusuke], Fukui, K.[Kazuhiro],
HEp-2 cell classification using rotation invariant co-occurrence among local binary patterns,
PR(47), No. 7, 2014, pp. 2428-2436.
Elsevier DOI 1404
Indirect immunofluorescence BibRef

Larsen, A.B.L.[Anders Boesen Lindbo], Vestergaard, J.S., Larsen, R.[Rasmus],
HEp-2 Cell Classification Using Shape Index Histograms With Donut-Shaped Spatial Pooling,
MedImg(33), No. 7, July 2014, pp. 1573-1580.
IEEE DOI 1407
Accuracy BibRef

Larsen, A.B.L.[Anders Boesen Lindbo], Dahl, A.B.[Anders Bjorholm], Larsen, R.[Rasmus],
Oriented Shape Index Histograms for Cell Classification,
SCIA15(16-25).
Springer DOI 1506
BibRef

Ponomarev, G.V.[Gennady V.], Arlazarov, V.L.[Vladimir L.], Gelfand, M.S.[Mikhail S.], Kazanov, M.D.[Marat D.],
ANA HEp-2 cells image classification using number, size, shape and localization of targeted cell regions,
PR(47), No. 7, 2014, pp. 2360-2366.
Elsevier DOI 1404
Immunofluorescent images BibRef

Ponomarev, G.V.[Gennady V.], Kazanov, M.D.[Marat D.],
Classification of ANA HEp-2 slide images using morphological features of stained patterns,
PRL(82, Part 1), No. 1, 2016, pp. 79-84.
Elsevier DOI 1612
ANA HEp-2 image BibRef

Theodorakopoulos, I.[Ilias], Kastaniotis, D.[Dimitris], Economou, G.[George], Fotopoulos, S.[Spiros],
HEp-2 cells classification via sparse representation of textural features fused into dissimilarity space,
PR(47), No. 7, 2014, pp. 2367-2378.
Elsevier DOI 1404
HEp-2 cells BibRef

Kastaniotis, D.[Dimitris], Fotopoulou, F.[Foteini], Theodorakopoulos, I.[Ilias], Economou, G.[George], Fotopoulos, S.[Spiros],
HEp-2 cell classification with Vector of Hierarchically Aggregated Residuals,
PR(65), No. 1, 2017, pp. 47-57.
Elsevier DOI 1702
HEp-2 cell classification BibRef

Kong, X.F.[Xiang-Fei], Li, K.[Kuan], Cao, J.J.[Jing-Jing], Yang, Q.X.[Qing-Xiong], Wenyin, L.[Liu],
HEp-2 cell pattern classification with discriminative dictionary learning,
PR(47), No. 7, 2014, pp. 2379-2388.
Elsevier DOI 1404
HEp-2 cell classification BibRef

Xu, X.[Xiang], Lin, F.[Feng], Ng, C.[Carol], Leong, K.P.[Khai Pang],
Automated classification for HEp-2 cells based on linear local distance coding framework,
JIVP(2015), No. 1, 2015, pp. 13.
DOI Link 1506
BibRef
Earlier:
Linear Local Distance coding for classification of HEp-2 staining patterns,
WACV14(393-400)
IEEE DOI 1406
Encoding BibRef

Xu, X.[Xiang], Lin, F.[Feng], Ng, C.[Carol], Leong, K.P.[Khai Pang],
Encoding rotation invariant features in HEP-2 cell classification,
ICIP15(1384-1388)
IEEE DOI 1512
ANA BibRef

Manivannan, S.[Siyamalan], Li, W.[Wenqi], Akbar, S.[Shazia], Wang, R.X.[Rui-Xuan], Zhang, J.G.[Jian-Guo], McKenna, S.J.[Stephen J.],
An automated pattern recognition system for classifying indirect immunofluorescence images of HEp-2 cells and specimens,
PR(51), No. 1, 2016, pp. 12-26.
Elsevier DOI 1601
Anti-nuclear antibody test BibRef

Qi, X.B.[Xian-Biao], Zhao, G.Y.[Guo-Ying], Chen, J.[Jie], Pietikäinen, M.[Matti],
Exploring illumination robust descriptors for human epithelial type 2 cell classification,
PR(60), No. 1, 2016, pp. 420-429.
Elsevier DOI 1609
HEp-2 cell classification BibRef

Zou, R.S., Tomasi, C.,
Deformable Graph Model for Tracking Epithelial Cell Sheets in Fluorescence Microscopy,
MedImg(35), No. 7, July 2016, pp. 1625-1635.
IEEE DOI 1608
biological techniques BibRef

Hobson, P.[Peter], Lovell, B.C.[Brian C.], Percannella, G.[Gennaro], Saggese, A.[Alessia], Vento, M.[Mario], Wiliem, A.[Arnold],
Computer Aided Diagnosis for Anti-Nuclear Antibodies HEp-2 images: Progress and challenges,
PRL(82, Part 1), No. 1, 2016, pp. 3-11.
Elsevier DOI 1612
BibRef
Earlier: A1, A2, A3, A5, A6, Only:
Classifying Anti-nuclear Antibodies HEp-2 Images: A Benchmarking Platform,
ICPR14(3233-3238)
IEEE DOI 1412
ANA test. Accuracy BibRef

Hobson, P.[Peter], Lovell, B.C.[Brian C.], Percannella, G.[Gennaro], Saggese, A.[Alessia], Vento, M.[Mario], Wiliem, A.[Arnold],
HEp-2 staining pattern recognition at cell and specimen levels: Datasets, algorithms and results,
PRL(82, Part 1), No. 1, 2016, pp. 12-22.
Elsevier DOI 1612
ANA test BibRef

Han, X.H.[Xian-Hua], Chen, Y.W.[Yen-Wei], Xu, G.[Gang],
Integration of spatial and orientation contexts in local ternary patterns for HEp-2 cell classification,
PRL(82, Part 1), No. 1, 2016, pp. 23-27.
Elsevier DOI 1612
HEp-2 image classification BibRef

Nanni, L.[Loris], Lumini, A.[Alessandra], Caetano dos Santos, F.L.[Florentino Luciano], Paci, M.[Michelangelo], Hyttinen, J.[Jari],
Ensembles of dense and dense sampling descriptors for the HEp-2 cells classification problem,
PRL(82, Part 1), No. 1, 2016, pp. 28-35.
Elsevier DOI 1612
HEp-2 cell classification BibRef

Qi, X.B.[Xian-Biao], Zhao, G.Y.[Guo-Ying], Chen, J.[Jie], Pietikäinen, M.[Matti],
HEp-2 cell classification: The role of Gaussian Scale Space Theory as a pre-processing approach,
PRL(82, Part 1), No. 1, 2016, pp. 36-43.
Elsevier DOI 1612
HEp-2 cell classification BibRef

Sarrafzadeh, O.[Omid], Rabbani, H.[Hossein], Dehnavi, A.M.[Alireza Mehri], Talebi, A.[Ardeshir],
Analyzing features by SWLDA for the classification of HEp-2 cell images using GMM,
PRL(82, Part 1), No. 1, 2016, pp. 44-55.
Elsevier DOI 1612
Indirect immunofluorescence BibRef

Cascio, D.[Donato], Taormina, V.[Vincenzo], Cipolla, M.[Marco], Bruno, S.[Salvatore], Fauci, F.[Francesco], Raso, G.[Giuseppe],
A multi-process system for HEp-2 cells classification based on SVM,
PRL(82, Part 1), No. 1, 2016, pp. 56-63.
Elsevier DOI 1612
Hep-2 cells classification BibRef

Ensafi, S.[Shahab], Lu, S.[Shijian], Kassim, A.A.[Ashraf A.], Tan, C.L.[Chew Lim],
Accurate HEp-2 cell classification based on Sparse Coding of Superpixels,
PRL(82, Part 1), No. 1, 2016, pp. 64-71.
Elsevier DOI 1612
Autoimmune diseases BibRef

Gragnaniello, D.[Diego], Sansone, C.[Carlo], Verdoliva, L.[Luisa],
Cell image classification by a scale and rotation invariant dense local descriptor,
PRL(82, Part 1), No. 1, 2016, pp. 72-78.
Elsevier DOI 1612
HEp-2000 cell classification BibRef

Li, G., Li, H., Duan, X., Zhou, Q., Zhou, J., Oldham, K.R., Wang, T.D.,
Visualizing Epithelial Expression in Vertical and Horizontal Planes With Dual Axes Confocal Endomicroscope Using Compact Distal Scanner,
MedImg(36), No. 7, July 2017, pp. 1482-1490.
IEEE DOI 1707
Biomedical optical imaging, Micromechanical devices, Mirrors, Optical device fabrication, Optical imaging, Optical scattering, Molecular and cellular imaging, endoscopy, gastrointestinal tract, optical imaging, system, design BibRef

Li, Y., Shen, L., Yu, S.,
HEp-2 Specimen Image Segmentation and Classification Using Very Deep Fully Convolutional Network,
MedImg(36), No. 7, July 2017, pp. 1561-1572.
IEEE DOI 1707
Computer architecture, Convolution, Feature extraction, Image segmentation, Pattern recognition, Training, Transforms, Cell patterns, classification, fully convolutional network, segmentation BibRef

Lei, H.[Haijun], Han, T.[Tao], Zhou, F.[Feng], Yu, Z.[Zhen], Qin, J.[Jing], Elazab, A.[Ahmed], Lei, B.[Baiying],
A deeply supervised residual network for HEp-2 cell classification via cross-modal transfer learning,
PR(79), 2018, pp. 290-302.
Elsevier DOI 1804
HEp-2 cell classification, Residual network, Deeply supervised ResNet, Cross-modal transfer learning BibRef

Shen, L.L.[Lin-Lin], Jia, X.[Xi], Li, Y.[Yuexiang],
Deep cross residual network for HEp-2 cell staining pattern classification,
PR(82), 2018, pp. 68-78.
Elsevier DOI 1806
Convolutional neural network, Cross connection, Deep cross residual network, HEp-2 classification BibRef


Kastaniotis, D., Ntinou, I., Tsourounis, D., Economou, G., Fotopoulos, S.,
Attention-Aware Generative Adversarial Networks (ATA-GANs),
IVMSP18(1-5)
IEEE DOI 1809
Cams, Training, Generators, Task analysis, Generative adversarial networks, Biological system modeling, HEp-2 cells BibRef

Tavares Vieira, R., Negri, T., Cavichiolli, A., Gonzaga, A.,
Human Epithelial Type 2 (HEp-2) Cell Classification by Using a Multiresolution Texture Descriptor,
WVC17(1-6)
IEEE DOI 1804
biomedical optical imaging, cellular biophysics, diseases, feature extraction, fluorescence, image classification, texture BibRef

Rodrigues, L.F., Naldi, M.C., Mari, J.F.,
HEp-2 Cell Image Classification Based on Convolutional Neural Networks,
WVC17(13-18)
IEEE DOI 1804
cellular biophysics, convergence, diseases, image classification, learning (artificial intelligence), medical image processing, staining patterns classification BibRef

Li, H.W.[Hong-Wei], Huang, H.[Hao], Zheng, W.S., Xie, X.H.[Xiao-Hua], Zhang, J.,
HEp-2 specimen classification via deep CNNs and pattern histogram,
ICPR16(2145-2149)
IEEE DOI 1705
Convolution, Feature extraction, Histograms, Image segmentation, Neural networks, Support vector machines, Training BibRef

Li, Y.[Yuexiang], Shen, L., Zhou, X.[Xiande], Yu, S.[Shiqi],
HEp-2 specimen classification with fully convolutional network,
ICPR16(96-100)
IEEE DOI 1705
Computer architecture, Diseases, Feature extraction, Image segmentation, Microprocessors, Pattern recognition, Training, cell patterns, classification, fully convolutional network, segmentation BibRef

Prasath, V.B.S., Kassim, Y.M., Oraibi, Z.A., Guiriec, J.B., Hafiane, A., Seetharaman, G., Palaniappan, K.,
HEp-2 cell classification and segmentation using motif texture patterns and spatial features with random forests,
ICPR16(90-95)
IEEE DOI 1705
Image segmentation, Imaging, Pattern recognition, Radio frequency, Support vector machines, Training, Vegetation BibRef

BS, D.[Divya], Subramaniam, K., HR, N.[Nanjundaswamy],
HEp-2 cell classification using artificial neural network approach,
ICPR16(84-89)
IEEE DOI 1705
Artificial neural networks, Classification algorithms, Feature extraction, Histograms, Pattern recognition, Principal component analysis, Training BibRef

Jia, X.[Xi], Shen, L.L.[Lin-Lin], Zhou, X.[Xiande], Yu, S.[Shiqi],
Deep convolutional neural network based HEp-2 cell classification,
ICPR16(77-80)
IEEE DOI 1705
Computer architecture, Feature extraction, Immune system, Microprocessors, Pattern recognition, Testing, Training, CNN, Hep-2, class-balanced, classification BibRef

Al-Dulaimi, K., Banks, J., Tomeo-Reyes, I., Chandran, V.,
Automatic segmentation of HEp-2 cell Fluorescence microscope images using level set method via geometric active contours,
ICPR16(81-83)
IEEE DOI 1705
BibRef
And: A1, A3, A2, A4:
White Blood Cell Nuclei Segmentation Using Level Set Methods and Geometric Active Contours,
DICTA16(1-7)
IEEE DOI 1701
Active contours, Fluorescence, Image segmentation, Immune system, Level set, MATLAB, Morphological operations, HEp-2 cell segmentation, geometric active contours, level, set, method Active contours BibRef

Zhou, X.D.[Xian-De], Li, Y.X.[Yue-Xiang], Wu, W.F.[Wen-Feng], Shen, L.L.[Lin-Lin],
HEP-2 cell image classification using local features and K-means clustering based joint sparse representation,
ICWAPR16(179-183)
IEEE DOI 1611
Detectors BibRef

Anam, A.M., Rushdi, M.A., Fahmy, A.S.,
Enhancement of low-resolution HEp-2 cell image classification using partial least-square regression,
ICIP16(1245-1249)
IEEE DOI 1610
Correlation BibRef

Miros, A., Wiliem, A., Holohan, K., Ball, L., Hobson, P., Lovell, B.C.,
A Benchmarking Platform for Mitotic Cell Classification of ANA IIF HEp-2 Images,
DICTA15(1-6)
IEEE DOI 1603
diseases BibRef

Gupta, K.[Krati], Gupta, V.[Vibha], Bhavsar, A.[Arnav], Sao, A.K.[Anil K.],
Class-specific hierarchical classification for HEP-2 specimen images,
ICIP15(641-645)
IEEE DOI 1512
Class-specific features; Hierarchical framework; Specimen-level images BibRef

Jiang, X.Y.[Xiao-Yi], Percannella, G.[Gennaro], Vento, M.[Mario],
A Verification-Based Multithreshold Probing Approach to HEp-2 Cell Segmentation,
CAIP15(II:266-276).
Springer DOI 1511
BibRef

Zhao, Y.[Yan], Gao, Z.M.[Zhi-Min], Wang, L.[Lei], Zhou, L.P.[Lu-Ping],
Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering,
DICTA14(1-8)
IEEE DOI 1502
feature extraction BibRef

Ensafi, S.[Shahab], Lu, S.[Shijian], Kassim, A.A.[Ashraf A.], Tan, C.L.[Chew Lim],
Automatic CAD System for HEp-2 Cell Image Classification,
ICPR14(3321-3326)
IEEE DOI 1412
Accuracy BibRef

Fakhrzadeh, A.[Azadeh], Spörndly-Nees, E.[Ellinor],
Epithelial Cell Segmentation in Histological Images of Testicular Tissue Using Graph-Cut,
CIAP13(II:201-208).
Springer DOI 1309
BibRef

Fakhrzadeh, A.[Azadeh], Spörndly-Nees, E.[Ellinor], Holm, L., Hendriks, C.L.L.,
Analyzing Tubular Tissue in Histopathological Thin Sections,
DICTA12(1-6).
IEEE DOI 1303
BibRef

Doshi, N.P.[Niraj P.], Schaefer, G.[Gerald],
Automatic Classification of HEp-2 Cells Using Multi-dimensional Local Binary Patterns,
ACPR13(293-297)
IEEE DOI 1408
diseases See also comprehensive benchmark of local binary pattern algorithms for texture retrieval, A. BibRef

Doshi, N.P., Schaefer, G.,
Texture Classification Using Multi-dimensional LBP Variance,
ACPR13(672-676)
IEEE DOI 1408
computer vision BibRef

Schaefer, G., Doshi, N.P., Krawczyk, B.,
HEp-2 Cell Classification Using Multi-dimensional Local Binary Patterns and Ensemble Classification,
ACPR13(951-955)
IEEE DOI 1408
feature selection BibRef

Iannello, G.[Giulio], Onofri, L.[Leonardo], Soda, P.[Paolo],
A Slightly Supervised Approach for Positive/Negative Classification of Fluorescence Intensity in HEp-2 Images,
CIAP13(II:319-328).
Springer DOI 1309
BibRef

Soda, P.[Paolo], Iannello, G.[Giulio],
A Hybrid Multi-Expert Systems for HEp-2 Staining Pattern Classification,
CIAP07(685-690).
IEEE DOI 0709
BibRef

Ersoy, I., Bunyak, F., Peng, J., Palaniappan, K.,
HEp-2 cell classification in IIF images using Shareboost,
ICPR12(3362-3365).
WWW Link. 1302
BibRef

Ghosh, S.[Subarna], Chaudhary, V.[Vipin],
Feature analysis for automatic classification of HEp-2 florescence patterns: Computer-Aided Diagnosis of Auto-immune diseases,
ICPR12(174-177).
WWW Link. 1302
BibRef

Li, K.[Kuan], Yin, J.P.[Jian-Ping], Lu, Z.[Zhi], Kong, X.F.[Xiang-Fei], Zhang, R.[Rui], Liu, W.[Wenyin],
Multiclass boosting SVM using different texture features in HEp-2 cell staining pattern classification,
ICPR12(170-173).
WWW Link. 1302
BibRef

Strandmark, P.[Petter], Ulen, J.[Johannes], Kahl, F.[Fredrik],
HEp-2 staining pattern classification,
ICPR12(33-36).
WWW Link. 1302
BibRef

Mazo, C.[Claudia], Trujillo, M.[Maria], Salazar, L.[Liliana],
Automatic Classification of Coating Epithelial Tissue,
CIARP14(311-318).
Springer DOI 1411
BibRef
Earlier:
An Automatic Segmentation Approach of Epithelial Cells Nuclei,
CIARP12(567-574).
Springer DOI 1209
BibRef

Wiliem, A., Hobson, P., Minchin, R.F., Lovell, B.C.,
An Automatic Image Based Single Dilution Method for End Point Titre Quantitation of Antinuclear Antibodies Tests Using HEp-2 Cells,
DICTA11(1-6).
IEEE DOI 1205
BibRef

Perner, P., Perner, H., Muller, B.,
Texture classification based on the boolean model and its application to HEP-2 cells,
ICPR02(II: 406-409).
IEEE DOI 0211
BibRef

Perner, P.[Petra],
Verification of Hypotheses Generated by Case-Based Reasoning Object Matching,
IWCIA17(66-78).
Springer DOI 1706
BibRef
Earlier:
Model Development and Incremental Learning Based on Case-Based Reasoning for Signal and Image Analysis,
CompIMAGE16(3-24).
Springer DOI 1704
BibRef
Earlier:
Case-Based Object Recognition with Application to Biological Images,
CIARP06(27-37).
Springer DOI 0611
See also Knowledge-Based Image-Inspection System for Automatic Defect Recognition, Classification, and Process Diagnosis, A. BibRef

Perner, P.[Petra],
Image Analysis and Classification of HEp-2 Cells in Fluorescent Images,
ICPR98(Vol II: 1677-1679).
IEEE DOI 9808
BibRef

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


Last update:Nov 17, 2018 at 09:12:27