20.4.4 Blood Cells, Counting, Extraction, Analysis

Chapter Contents (Back)
Cells. Blood Cells. Leukocyte.

Bacus, J.W., Gose, E.E.,
Leukocyte Pattern Recognition,
SMC(2), No. 4, September 1972, pp. 513-525. BibRef 7209

Bacus, J.W.,
A whitening transformation for two-color blood cell images,
PR(8), No. 1, January 1976, pp. 53-60.
WWW Link. 0309
BibRef

Landeweerd, G.H., Gelsema, E.S.,
The Use of Nuclear Texture Parameters in the Automatic Analysis of Leukocytes,
PR(10), No. 2, 1978, pp. 57-61.
WWW Link. BibRef 7800

Norgren, P.E.[Philip E.], Kulkarni, A.V.[Ashok V.], Graham, M.D.[Marshall D.],
Leukocyte image analysis in the diff3 system,
PR(13), No. 4, 1981, pp. 299-314.
WWW Link. 0309
BibRef

Mui, J.K., and Fu, K.S.,
Automated Classification of Nuecleated Blood Cells Using a Binary Tree Classifier,
PAMI(2), No. 5, September 1980, pp. 429-443. BibRef 8009

Landeweerd, G.H., Gelsema, E.S., Brenner, J.F., Selles, W.D., Zahniser, D.J.,
Pattern Recognition of Nucleated Cells from the Peripheral Blood,
PR(16), No. 2, 1983, pp. 131-140.
WWW Link. BibRef 8300
Earlier: PR(15), No. 5, 1982, pp. 425.
WWW Link. BibRef

Landeweerd, G.H., Timmers, T., Gelsema, E.S., Bins, M., Halie, M.R.,
Classification of Normal and Abnormal Samples of Peripheral Blood by Linear Mapping of the Feature Space,
PR(16), No. 3, 1983, pp. 319-326.
WWW Link. 0309
BibRef

Landeweerd, G.H., Timmers, T., Gelsema, E.S., Bins, M., Halie, M.R.,
Binary Tree Versus Single Level Tree Classification of White Blood Cells,
PR(16), No. 6, 1983, pp. 571-577.
WWW Link. 0309
BibRef

Bronkorsta, P.J.H., Reinders, M.J.T., Hendriks, E.A., Grimbergen, J., Heethaar, R.M., Brakenhoff, G.J.,
On-line detection of red blood cell shape using deformable templates,
PRL(21), No. 5, May 2000, pp. 413-424. 0005
BibRef

Theera-Umpon, N.[Nipon], Dougherty, E.R.[Edward R.], Gader, P.D.[Paul D.],
Non-homothetic granulometric mixing theory with application to blood cell counting,
PR(34), No. 12, December 2001, pp. 2547-2560.
WWW Link. 0110
BibRef

Theera-Umpon, N., Gader, P.D.,
Training Neural Networks to Count White Blood Cells Via a Minimum Counting Error Objective Function,
ICPR00(Vol II: 299-302).
IEEE DOI 0009
BibRef

di Ruberto, C.[Cecilia], Dempster, A.[Andrew], Khan, S.[Shahid], Jarra, B.[Bill],
Analysis of infected blood cell images using morphological operators,
IVC(20), No. 2, February 2002, pp. 133-146.
WWW Link. 0202
BibRef
Earlier:
Segmentation of Blood Images Using Morphological Operators,
ICPR00(Vol III: 397-400).
IEEE DOI
IEEE DOI 0009
BibRef

di Ruberto, C., Dempster, A., Khan, S., Jarra, B.,
Automatic Thresholding of Infected Blood Images Using Granulometry and Regional Extrema,
ICPR00(Vol III: 441-444).
IEEE DOI 0009
BibRef

de Andrade Waldemarin, K.C.[Kátia Cristina], Emílio Beletti, M.[Marcelo], da Fontoura Costa, L.[Luciano],
Nuclear morphometry of neoplastic cells as a method for diagnosis of histiocytoma, mastocytoma and transmissible venereal tumor in dogs,
RealTimeImg(10), No. 4, August 2004, pp. 197-204.
WWW Link. 0410
BibRef

Sabino, D.M.U.[Daniela Mayumi Ushizima], da Fontoura Costa, L.[Luciano], Rizzatti, E.G.[Edgar Gil], Zago, M.A.[Marco Antonio],
A texture approach to leukocyte recognition,
RealTimeImg(10), No. 4, August 2004, pp. 205-216.
WWW Link. 0410
BibRef

Ray, N., Acton, S.T., Ley, K.,
Tracking leukocytes in vivo with shape and size constrained active contours,
MedImg(21), No. 10, October 2002, pp. 1222-1235.
IEEE Top Reference. 0301
BibRef

Ray, N.[Nilanjan], Acton, S.T.[Scott T.],
Motion gradient vector flow: an external force for tracking rolling leukocytes with shape and size constrained active contours,
MedImg(23), No. 12, December 2004, pp. 1466-1478.
IEEE Abstract. 0412
BibRef
Earlier:
Tracking fast-rolling leukocytes in vivo with active contours,
ICIP02(III: 165-168).
IEEE DOI 0210
BibRef

Cui, J.[Jing], Ray, N., Acton, S.T., Lin, Z.[Zongli],
Application of the Affine Transform Invariant Model to Cell Tracking,
Southwest06(56-60).
IEEE DOI 0603
BibRef

Acton, S.T.[Scott T.], Ray, N.[Nilanjan],
Biomedical Image Analysis: Tracking,
Morgan Claypool2006. Synthesis Lectures on Image, Video, and Multimedia Processing
WWW Link. BibRef 0600

Ray, N., Acton, S.T.,
Active contours for cell tracking,
Southwest02(274-278).
IEEE Top Reference. 0208
BibRef

Acton, S.T.,
Biomedical Image Analysis at the Cellular Level,
IMVIP08(27-27).
IEEE DOI 0809
BibRef

Mukherjee, D.P., Ray, N., Acton, S.T.,
Level Set Analysis for Leukocyte Detection and Tracking,
IP(13), No. 4, April 2004, pp. 562-572.
IEEE DOI 0404
BibRef

Dong, G.[Gang], Acton, S.T.,
A variational method for leukocyte detection,
ICIP03(II: 161-164).
IEEE DOI 0312
BibRef

Dong, G.[Gang], Ray, N., Acton, S.T.,
Intravital leukocyte detection using the gradient inverse coefficient of variation,
MedImg(24), No. 7, July 2005, pp. 910-924.
IEEE DOI 0508
BibRef

Zhang, X.W.[Xi-Wen], Song, J.Q.A.[Ji-Qi-Ang], Lyu, M.R.[Michael R.], Cai, S.J.[Shi-Jie],
Extraction of karyocytes and their components from microscopic bone marrow images based on regional color features,
PR(37), No. 2, February 2004, pp. 351-361.
WWW Link. 0311
BibRef

Ahammer, H., Kropfl, J.M., Hackl, C., Sedivy, R.,
Image statistics and data mining of anal intraepithelial neoplasia,
PRL(29), No. 16, 1 December 2008, pp. 2189-2196.
WWW Link. 0811
Image statistics; Data mining; Classification; Neoplasia; HIV BibRef

Tek, F.B.[F. Boray], Dempster, A.G.[Andrew G.], Kale, I.[Izzet],
Computer vision for microscopy diagnosis of malaria,
Malaria Journal(8), No. 153, 2009.
DOI Link BibRef 0900
Earlier:
Malaria Parasite Detection in Peripheral Blood Images,
BMVC06(I:347).
PDF File. 0609
Application of image analysis and computer vision to malaria screening. BibRef

Tek, F.B.[F. Boray], Dempster, A.G.[Andrew G.], Kale, I.[Izzet],
Parasite detection and identification for automated thin blood film malaria diagnosis,
CVIU(114), No. 1, January 2010, pp. 21-32.
Elsevier DOI 1001
Malaria diagnosis; Microscope image analysis; Blood cell image; Parasitemia; K nearest neighbour rule; Imbalanced learning; Area granulometry BibRef

Tek, F.B.[F. Boray], Dempster, A.G.[Andrew G.], Kale, I.[Izzet],
Blood Cell Segmentation Using Minimum Area Watershed and Circle Radon Transformations,
MM40Yrs05(441-454)
Springer DOI 0907
BibRef

Kumarasamy, S.K.[Saravana Kumar], Ong, S.H., Tan, K.S.W.,
Robust contour reconstruction of red blood cells and parasites in the automated identification of the stages of malarial infection,
MVA(22), No. 3, May 2011, pp. 461-469.
WWW Link. 1104
BibRef

Liu, R.[Ran], Dey, D.K.[Dipak K.], Boss, D.[Daniel], Marquet, P.[Pierre], Javidi, B.[Bahram],
Recognition and classification of red blood cells using digital holographic microscopy and data clustering with discriminant analysis,
JOSA-A(28), No. 6, June 2011, pp. 1204-1210.
WWW Link. 1101
BibRef

Chen, H.M.[Hung-Ming], Tsao, Y.T.[Ya-Ting], Tsai, S.N.[Shin-Ni],
Automatic image segmentation and classification based on direction texton technique for hemolytic anemia in thin blood smears,
MVA(25), No. 2, February 2014, pp. 501-510.
WWW Link. 1402
BibRef

Xia, W.[Wenfei], Ma, X.P.[Xiao-Peng], Li, X.[Xingrui], Lu, C.[Chao], Yang, X.W.[Xiao-Wei], Zhu, Z.[Zhi], Yi, J.L.[Ji-Lin],
Reversal effect of low-intensity ultrasound on adriamycin-resistant human hepatoma cells in vitro and in vivo,
IJIST(24), No. 1, 2014, pp. 23-28.
DOI Link 1403
ultrasound, adriamycin-resistant, MDR, hepatoma, HepG2 BibRef

Lee, H.[Howard], Chen, Y.P.P.[Yi-Ping Phoebe],
Cell morphology based classification for red cells in blood smear images,
PRL(49), No. 1, 2014, pp. 155-161.
Elsevier DOI 1410
BibRef

Di Ruberto, C.[Cecilia], Loddo, A.[Andrea], Putzu, L.[Lorenzo],
A leucocytes count system from blood smear images,
MVA(27), No. 8, November 2016, pp. 1151-1160.
Springer DOI 1612
BibRef
Earlier:
A Multiple Classifier Learning by Sampling System for White Blood Cells Segmentation,
CAIP15(II:415-425).
Springer DOI 1511
BibRef
And:
Learning by Sampling for White Blood Cells Segmentation,
CIAP15(I:557-567).
Springer DOI 1511
BibRef


Razzak, M.I., Naz, S.,
Microscopic Blood Smear Segmentation and Classification Using Deep Contour Aware CNN and Extreme Machine Learning,
Microscopy17(801-807)
IEEE DOI 1709
Blood, Diseases, Feature extraction, Image color analysis, Image segmentation, Microscopy, Shape, Blood Sample Analysis, ELM, KWFLICM, RBC, cell morphology, image, analysis BibRef

Carvajal, J., Smith, D.F., Zhao, K., Wiliem, A., Finucane, P., Hobson, P., Jennings, A., McDougall, R., Lovell, B.,
An Early Experience Toward Developing Computer Aided Diagnosis for Gram-Stained Smears Images,
Microscopy17(814-820)
IEEE DOI 1709
Blood, Computer vision, Data mining, Feature extraction, Microorganisms, Microscopy, Pathology BibRef

Dong, Y.F.[Yue-Fang], Fu, W.W.[Wei-Wei], Zhou, Z.[Zhe], Chen, N.[Nian], Liu, M.[Min], Chen, S.[Shi],
ABO blood group detection based on image processing technology,
ICIVC17(655-659)
IEEE DOI 1708
Filling, Image recognition, Image segmentation, ABO blood image, agglutination/no agglutination, blood analysis, standard deviation, threshold, segmentation BibRef

Li, X.[Xiang], Li, W., Xu, X.D.[Xiao-Dong], Hu, W.[Wei],
Cell classification using convolutional neural networks in medical hyperspectral imagery,
ICIVC17(501-504)
IEEE DOI 1708
Blood, Computer architecture, Hyperspectral imaging, Medical diagnostic imaging, Microprocessors, Support vector machines, blood cell classification, convolutional neural network, deep learning, medical, hyperspectral, imagery BibRef

Kossowski, T., Stasinski, R.,
Multi-wavelength analysis of substances levels in human blood,
WSSIP17(1-4)
IEEE DOI 1707
Absorption, Blood, Compounds, Ethanol, Spectroscopy, Sugar, Wavelength measurement, ethanol, glucose, multi-wavelength, non-invasive, prediction BibRef

Arvind, B.C., Nagaraj, S.K., Seelamantula, C.S., Gorthi, S.S.,
Active-disc-based Kalman filter technique for tracking of blood cells in microfluidic channels,
ICIP16(3394-3398)
IEEE DOI 1610
Blood BibRef

Lotfi, M., Nazari, B., Sadri, S., Sichani, N.K.,
The detection of Dacrocyte, Schistocyte and Elliptocyte cells in Iron Deficiency Anemia,
IPRIA15(1-5)
IEEE DOI 1603
cellular biophysics BibRef

Maji, P., Mandal, A., Ganguly, M., Saha, S.,
An automated method for counting and characterizing red blood cells using mathematical morphology,
ICAPR15(1-6)
IEEE DOI 1511
blood BibRef

Rawat, J.[Jyoti], Bhadauria, H.S., Singh, A.[Annapurna], Virmani, J.[Jitendra],
Review of Leukocyte Classification Techniques for Microscopic Blood Images,
ICCSGD15(1948-1954). 1506
BibRef

Henning, R., Rivas-Perea, P., Shaw, B., Hamerly, G.,
A Convolutional Neural Network approach for classifying leukocoria,
Southwest14(9-12)
IEEE DOI 1406
cancer BibRef

Sheeba, F.[Feminna], Thamburaj, R.[Robinson], Mammen, J.J.[Joy John], Nagar, A.K.[Atulya K.],
Splitting of Overlapping Cells in Peripheral Blood Smear Images by Concavity Analysis,
IWCIA14(238-249).
Springer DOI 1405
BibRef

Habibzadeh, M.[Mehdi], Krzyz.ak, A.[Adam], Fevens, T.[Thomas],
Analysis of White Blood Cell Differential Counts Using Dual-Tree Complex Wavelet Transform and Support Vector Machine Classifier,
ICCVG12(414-422).
Springer DOI 1210
BibRef

Mohapatra, S.[Subrajeet], Patra, D.[Dipti], Kumar, K.[Kundan],
Blood microscopic image segmentation using rough sets,
ICIIP11(1-6).
IEEE DOI 1112
BibRef

Makkapati, V.V.[Vishnu V.], Naik, S.K.[Sarif K.],
Clump splitting based on detection of dominant points from contours,
CASE09(197-201).
WWW Link. 0908
BibRef

Makkapati, V.V.[Vishnu V.], Rao, R.M.,
Ontology-based Malaria Parasite Stage and Species Identification from Peripheral Blood Smear Images,
EMBC11(6138-6141).
IEEE DOI BibRef 1100
And:
Segmentation of Malaria Parasites in Peripheral Blood Smear Images,
ICASSP09(1361-1364).
IEEE DOI BibRef

Bradhurst, C.J.[Christopher J.], Boles, W.[Wageeh], Xiao, Y.[Yin],
Segmentation of bone marrow stromal cells in phase contrast microscopy images,
IVCNZ08(1-6).
IEEE DOI 0811
BibRef

Ray, N.[Nilanjan],
A concave cost formulation for parametric curve fitting: Detection of leukocytes from intravital microscopy images,
ICIP10(53-56).
IEEE DOI 1009
BibRef

Falcón-Ruiz, A.[Alexander], Paz-Viera, J.[Juan], Taboada-Crispí, A.[Alberto], Sahli, H.[Hichem],
A Quality Analysis on JPEG 2000 Compressed Leukocyte Images by Means of Segmentation Algorithms,
CIARP10(161-168).
Springer DOI 1011
BibRef

Rezatofighi, S.H.[Seyed Hamid], Khaksari, K.[Kosar], Soltanian-Zadeh, H.[Hamid],
Automatic Recognition of Five Types of White Blood Cells in Peripheral Blood,
ICIAR10(II: 161-172).
Springer DOI 1006
BibRef

Landau, M.[Michael], Koltsova, E.[Ekaterina], Ley, K.[Klaus], Acton, S.T.[Scott T.],
Multi-cell 3D tracking with adaptive acceptance gates,
Southwest10(49-52).
IEEE DOI 1005
Track dendritic and T cells. BibRef

Vromen, J., McCane, B.,
Red blood cell segmentation from SEM images,
IVCNZ09(44-49).
IEEE DOI 0911
BibRef

Martinez, L.,
A non-invasive spectral reflectance method for mapping blood oxygen saturation in wounds,
AIPR02(112-116).
IEEE DOI 0210
BibRef

Beach, J.,
Spectral reflectance technique for retinal blood oxygen evaluation in humans,
AIPR02(117-123).
IEEE DOI 0210
BibRef

Xiong, W., Ong, S.H., Lim, J.H., Tung, N.N., Liu, J., Racoceanu, D., Tan, K., Chong, A., Foong, K.,
Automatic working area classification in peripheral blood smears using spatial distribution features across scales,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Seepuri, S.I.[Sun-Il], Rodriguez, J.J.[Jeffrey J.], Elliott, D.A.[David A.],
Automated 3-D Segmentation of Internal Hemoglobin in TEM Images,
Southwest08(117-120).
IEEE DOI 0803
BibRef

Díaz, G.[Gloria], Gonzalez, F.A.[Fabio A.], Romero, E.[Eduardo],
Automatic Clump Splitting for Cell Quantification in Microscopical Images,
CIARP07(763-772).
Springer DOI 0711
BibRef
And:
Infected Cell Identification in Thin Blood Images Based on Color Pixel Classification: Comparison and Analysis,
CIARP07(812-821).
Springer DOI 0711
BibRef

Halim, S., Bretschneider, T.R., Li, Y.K.[Yi-Kun], Preiser, P.R., Kuss, C.,
Estimating Malaria Parasitaemia from Blood Smear Images,
ICARCV06(1-6).
IEEE DOI 0612
BibRef

Lee, L.[Lim], Bretschneider, T.R., Preiser, P.R.,
Automatic Analysis of Cos-7 Binding Assay Imagery for Malaria Vaccination Experiments,
ICARCV06(1-6).
IEEE DOI 0612
BibRef

Eom, S.[Seongeun], Kim, S.J.[Seung-Jun], Shin, V.[Vladimir], Ahn, B.[Byungha],
Leukocyte Segmentation in Blood Smear Images Using Region-Based Active Contours,
ACIVS06(867-876).
Springer DOI 0609
BibRef

Kasson, P.M., Huppa, J.B., Davis, M.M., Brunger, A.T.,
Quantitative analysis of lymphocyte membrane protein redistribution from fluorescence microscopy,
ICIP04(V: 2933-2936).
IEEE DOI 0505
BibRef

Nilsson, B., Heyden, A.,
Model-based segmentation of leukocytes clusters,
ICPR02(I: 727-730).
IEEE DOI 0211
BibRef

di Ruberto, C.[Cecilia], Dempster, A.[Andrew], Khan, S.[Shahid], Jarra, B.[Bill],
Morphological Image Processing for Evaluating Malaria Disease,
VF01(739 ff.).
Springer DOI 0209
BibRef

Nilsson, B., Heyden, A.,
Segmentation of Dense Leukocyte Clusters,
MMBIA01(xx-yy). 0110
BibRef

Ferri, M., Lombardini, S., Pallotti, C.,
Leukocyte classifications by size functions,
WACV94(223-229).
IEEE Abstract. 0403
BibRef

Kovalev, V.A., Grigoriev, A.Y., Ahn, H.S.[Hyo-Sok],
Robust recognition of white blood cell images,
ICPR96(IV: 371-375).
IEEE DOI 0509
BibRef

Cseke, I.,
A fast segmentation scheme for white blood cell images,
ICPR92(III:530-533).
IEEE DOI 9208
BibRef

Bartfeld, E., Zajicek, G., Kenet, G., Schwartz-Arad, D.,
Measuring hepatocytes reaction to dimethylnitrosamine using computerized microscope,
ICPR88(I: 465-467).
IEEE DOI 8811
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Blood Cell Cancers, Lymphoma, Leukemia .


Last update:Nov 11, 2017 at 13:31:57