A survey on histological image analysis-based assessment of three major biological factors influencing radiotherapy: proliferation, hypoxia and vasculature
暂无分享,去创建一个
[1] Thomas Gahm,et al. Automated microscopy in diagnostic histopathology: From image processing to automated reasoning , 1997 .
[2] H. Lepor,et al. Quantifying the smooth muscle content of the prostate using double-immunoenzymatic staining and color assisted image analysis. , 1992, The Journal of urology.
[3] David A. Mankoff,et al. Application of Photoshop-based Image Analysis to Quantification of Hormone Receptor Expression in Breast Cancer , 1997, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.
[4] Chul Ahn,et al. Endothelial area as a prognostic indicator for invasive breast carcinoma , 1996, Cancer.
[5] J P Rigaut,et al. Toward objective prognostic grading of prostatic carcinoma using image analysis. , 1993, Analytical and quantitative cytology and histology.
[6] F Gilles,et al. Grading of cystosarcoma phyllodes by texture analysis of tissue architecture. , 1994, Analytical and quantitative cytology and histology.
[7] R. Zhou,et al. A multiple wavelength algorithm in color image analysis and its applications in stain decomposition in microscopy images. , 1996, Medical physics.
[8] Claudio Eccher,et al. Microvessel density quantification in breast carcinomas. Assessment by light microscopy vs. a computer-aided image analysis system , 1995 .
[9] Carl G. Looney,et al. Pattern recognition using neural networks , 1997 .
[10] T K ten Kate,et al. UvA-DARE (Digital Academic Repository) A method for counting mitoses by image processing in Feulgen stained breast cancer sections , 2005 .
[11] I T Young,et al. Towards a quantitative grading of bladder tumors. , 1991, Cytometry.
[12] M. Goto,et al. Chromaticity analysis of immunostained tumor specimens. , 1992, Pathology, Research and Practice.
[13] Jim R. Parker,et al. Algorithms for image processing and computer vision , 1996 .
[14] H. Heinzl,et al. Quantitative immunohistochemistry of factor VIII-related antigen in breast carcinoma: a comparison of computer-assisted image analysis with established counting methods. , 1996, American journal of clinical pathology.
[15] R J Hodgkiss,et al. Spatial relationship between hypoxia and the (perfused) vascular network in a human glioma xenograft: a quantitative multi-parameter analysis. , 2000, International journal of radiation oncology, biology, physics.
[16] J. Bussink,et al. Multiparameter analysis of vasculature, perfusion and proliferation in human tumour xenografts. , 1998, British Journal of Cancer.
[17] P J Sjöström,et al. Artificial neural network-aided image analysis system for cell counting. , 1999, Cytometry.
[18] Jerzy Stefanowski,et al. Feature subset selection for classification of histological images , 1997, Artif. Intell. Medicine.
[19] Hiromitsu Yamada,et al. Recognition of Kidney Glomerulus by Dynamic Programming Matching Method , 1988, IEEE Trans. Pattern Anal. Mach. Intell..
[20] G Zinser,et al. Segmentation of cell nuclei in tissue section analysis. , 1983, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.
[21] Jayasooriah,et al. Image analysis of tissue sections , 1996, Comput. Biol. Medicine.
[22] R. J. Hodgkiss,et al. Vascular perfusion and hypoxic areas in RIF-1 tumours after photodynamic therapy. , 1996, British Journal of Cancer.
[23] Lawrence M. Firestone. Automated microscopy for lymph node cancer diagnosis , 1993, Photonics West - Lasers and Applications in Science and Engineering.
[24] L. Golberg,et al. Non-invasive assessment of human tumour hypoxia with 123I-iodoazomycin arabinoside: preliminary report of a clinical study. , 1992, British Journal of Cancer.
[25] R. Ornberg,et al. Analysis of Stained Objects in Histological Sections by Spectral Imaging and Differential Absorption , 1999, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.
[26] T L Phillips,et al. Oxygen in human tumors: correlations between methods of measurement and response to therapy. Summary of a workshop held November 19-20, 1992, at the National Cancer Institute, Bethesda, Maryland. , 1993, Radiation research.
[27] K. Beier,et al. Application of automatic image analysis for quantitative morphological studies of peroxisomes in rat liver in conjunction with cytochemical staining with 3‐3′‐diaminobenzidine and immunocytochemistry , 1992, Microscopy research and technique.
[28] Arthur C. Sanderson,et al. A System for Automated Liver Tissue Image Analysis: Methods and Results , 1985, IEEE Transactions on Biomedical Engineering.
[29] W Blumenfeld,et al. Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma. , 1993, The American journal of pathology.
[30] P.K Sahoo,et al. A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..
[31] Nidhi Jain,et al. Integrated neural network system for histological image understanding , 1991, Other Conferences.
[32] M Bibbo,et al. Assessment of hormone receptors in breast carcinoma by immunocytochemistry and image analysis. II. Estrogen receptors. , 1989, Analytical and quantitative cytology and histology.
[33] Allen M. Gown,et al. Complete Chromogen Separation and Analysis in Double Immunohistochemical Stains Using Photoshop-based Image Analysis , 1999, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.
[34] C MacAulay,et al. Adaptive color basis transformation. An aid in image segmentation. , 1989, Analytical and quantitative cytology and histology.
[35] J. L. Au,et al. Application of automatic thresholding in image analysis scoring of cells in human solid tumors labeled for proliferation markers. , 1997, Cytometry.
[36] J F Cornhill,et al. Automated identification of stained cells in tissue sections using digital image analysis. , 1999, Analytical and quantitative cytology and histology.
[37] Anil K. Jain,et al. Segmentation of Muscle Cell Pictures: A Preliminary Study , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] A. Heerschap,et al. In vivo (31)P magnetic resonance spectroscopy and morphometric analysis of the perfused vascular architecture of human glioma xenografts in nude mice. , 1997, British Journal of Cancer.
[39] R. Paczynski,et al. Automated measurement of infarct size with scanned images of triphenyltetrazolium chloride-stained rat brains. , 1996, Stroke.
[40] Shunzo Chiba,et al. Pulmonary response to a bronchodilator delivered by three inhalation methods on exercise-induced bronchospasm , 1990 .
[41] L. H. Gray,et al. The concentration of oxygen dissolved in tissues at the time of irradiation as a factor in radiotherapy. , 1953, The British journal of radiology.
[42] D. Weinberg,et al. Nuclear grading of breast carcinoma by image analysis. Classification by multivariate and neural network analysis. , 1991, American journal of clinical pathology.
[43] J M Lamaziere,et al. Semiquantitative study of the distribution of two cellular antigens by computer-directed color analysis. , 1993, Laboratory investigation; a journal of technical methods and pathology.
[44] U. Pal,et al. Automatic Cell Segmentation in Cyto- and Histometry Using Dominant Contour Feature Points , 1998, Analytical cellular pathology : the journal of the European Society for Analytical Cellular Pathology.
[45] B Vojnovic,et al. Measurement of oxygen tension in tumours by time-resolved fluorescence. , 1996, The British journal of cancer. Supplement.
[46] Borivoj Vojnovic,et al. An image analysis‐based approach for automated counting of cancer cell nuclei in tissue sections , 2003, Cytometry. Part A : the journal of the International Society for Analytical Cytology.
[47] L. Hibbard,et al. Multiscale detection and analysis of the senile plaques of Alzheimer's disease , 1995, IEEE Transactions on Biomedical Engineering.
[48] J. L. Au,et al. Comparative scoring by visual and image analysis of cells in human solid tumors labeled for proliferation markers. , 1997, Cytometry.
[49] Haisang Wu,et al. Optimal segmentation of cell images , 1998 .
[50] J. A. van der Laak,et al. Hue-saturation-density (HSD) model for stain recognition in digital images from transmitted light microscopy. , 2000, Cytometry.
[51] S S Cross,et al. FRACTALS IN PATHOLOGY , 1997, The Journal of pathology.
[52] P H Bartels,et al. Knowledge-guided segmentation of colorectal histopathologic imagery. , 1993, Analytical and quantitative cytology and histology.
[53] P Davaris,et al. Findings of computerised nuclear morphometry of papillary thyroid carcinoma in correlation with known prognostic factors. , 1997, Journal of experimental & clinical cancer research : CR.
[54] S. Cross,et al. Fractal geometric analysis of material from molar and non‐molar pregnancies , 1994, The Journal of pathology.
[55] P H Bartels,et al. Expert systems in histopathology. IV. The management of uncertainty. , 1992, Analytical and quantitative cytology and histology.
[56] A. Harris,et al. Quantitation and prognostic value of breast cancer angiogenesis: Comparison of microvessel density, Chalkley count, and computer image analysis , 1995, The Journal of pathology.
[57] F Gilles,et al. Use of texture parameters in the classification of soft tissue tumors. , 1994, Analytical and quantitative cytology and histology.
[58] M Klencki,et al. Multifarious system for quantitative analysis of histologic compartments. , 1997, Computers and biomedical research, an international journal.
[59] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.
[60] Bidyut Baran Chaudhuri,et al. Region based techniques for segmentation of volumetric histo-pathological images , 2000, Comput. Methods Programs Biomed..
[61] K. Haustermans,et al. Diffusion limited hypoxia estimated by vascular image analysis: comparison with pimonidazole staining in human tumors. , 2000, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[62] E H Hammond,et al. Quantitative peroxidase-antiperoxidase complex-substrate mass determination in tissue sections by a dual wavelength method. , 1992, Analytical and quantitative cytology and histology.
[63] P H Bartels,et al. Expert systems in histopathology. V. DS theory, certainty factors and possibility theory. , 1992, Analytical and quantitative cytology and histology.
[64] Lawrence O'Gorman,et al. The Wedge Filter Technique for Convex Boundary Estimation , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[65] Bayan S. Sharif,et al. Microscopic image analysis for quantitative measurement and feature identification of normal and cancerous colonic mucosa , 1998, IEEE Transactions on Information Technology in Biomedicine.
[66] J. Uitto,et al. Elastic fibers in human skin: quantitation of elastic fibers by computerized digital image analyses and determination of elastin by radioimmunoassay of desmosine. , 1983, Laboratory investigation; a journal of technical methods and pathology.
[67] Constantinos G. Loukas,et al. Image-analysis-based assessment of hypoxia and vasculature in bladder tumors , 2001, International Symposium on Multispectral Image Processing and Pattern Recognition.
[68] Rafael C. González,et al. Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[69] Borivoj Vojnovic,et al. Tumor Hypoxia and Blood Vessel Detection , 2002, Annals of the New York Academy of Sciences.
[70] D Gibson,et al. Definition and application of a fourier domain texture measure: applications to histological image segmentation. , 1995, Computers in biology and medicine.
[71] M H Deverell,et al. Comparison of stains for image segmentation and measurement of nuclear parameters by computerised image analysis using IBAS 2000. , 1989, Pathology, research and practice.
[72] G L Wied,et al. Artificial neural networks and their use in quantitative pathology. , 1990, Analytical and quantitative cytology and histology.
[73] P Vaupel,et al. Oxygenation of human tumors: evaluation of tissue oxygen distribution in breast cancers by computerized O2 tension measurements. , 1991, Cancer research.
[74] W Abmayr,et al. Segmentation of scenes in tissue sections. , 1987, Analytical and quantitative cytology and histology.
[75] A. J. van der Kogel,et al. Application of an image analysis system to the quantitation of tumor perfusion and vascularity in human glioma xenografts. , 1995, Microvascular research.
[76] J. M. Taylor,et al. The hazard of accelerated tumor clonogen repopulation during radiotherapy. , 1988, Acta oncologica.
[77] L Piana,et al. CD31 quantitative immunocytochemical assays in breast carcinomas. Correlation with current prognostic factors. , 1995, American journal of clinical pathology.
[78] S. Soltani,et al. SURVEY A Survey of Thresholding Techniques , 1988 .
[79] Sim Heng Ong,et al. Adaptive window-based tracking for the detection of membrane structures in kidney electron micrographs , 2005, Machine Vision and Applications.
[80] Roland T. Chin,et al. Automated analysis of nerve-cell images using active contour models , 1996, IEEE Trans. Medical Imaging.
[81] Bidyut Baran Chaudhuri,et al. Semi-automatic segmentation of tissue cells from confocal microscope images , 1996, Proceedings of 13th International Conference on Pattern Recognition.
[82] Piero Mussio,et al. Automatic cell count in digital images of liver tissue sections , 1991, [1991] Computer-Based Medical Systems@m_Proceedings of the Fourth Annual IEEE Symposium.
[83] M. Janicek,et al. Tumor angiogenesis as a prognostic factor in ovarian carcinoma , 1997, Cancer.
[84] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[85] Demetri Terzopoulos,et al. Snakes: Active contour models , 2004, International Journal of Computer Vision.
[86] M Bibbo,et al. Quantitation of estrogen receptor content and Ki-67 staining in breast carcinoma by the microTICAS image analysis system. , 1987, Analytical and quantitative cytology and histology.
[87] Ruifrok Ac. QUANTIFICATION OF IMMUNOHISTOCHEMICAL STAINING BY COLOR TRANSLATION AND AUTOMATED THRESHOLDING , 1997 .
[88] A. Pouliakis,et al. A comparative study of three variations of the learning vector quantizer in the discrimination of benign from malignant gastric cells , 1998, Cytopathology : official journal of the British Society for Clinical Cytology.
[89] F. K. Lam,et al. Image analysis system for assessment of immunohistochemically stained proliferative marker (MIB-1) in oesophageal squamous cell carcinoma , 2003, Comput. Methods Programs Biomed..
[90] U. Luthra,et al. Manual versus image analysis estimation of PCNA in breast carcinoma. , 2000, Analytical and quantitative cytology and histology.
[91] J. Lakowicz,et al. Texture analysis of fluorescence lifetime images of nuclear DNA with effect of fluorescence resonance energy transfer. , 2001, Cytometry.
[92] C Garbay,et al. Application of colored image analysis to bone marrow cell recognition. , 1981, Analytical and quantitative cytology.
[93] J Smolle,et al. Optimization of linear image combination for segmentation in red-green-blue images. , 1996, Analytical and quantitative cytology and histology.
[94] S. Cross,et al. Fractal geometric analysis of colorectal polyps , 1994, The Journal of pathology.
[95] P H Bartels,et al. Image segmentation of cribriform gland tissue. , 1995, Analytical and quantitative cytology and histology.
[96] J. Brown,et al. Exploiting the hypoxic cancer cell: mechanisms and therapeutic strategies. , 2000, Molecular medicine today.
[97] A. Van Daele,et al. Quantification and prognostic relevance of angiogenic parameters in invasive cervical cancer. , 1998, British Journal of Cancer.
[98] G. Steel,et al. Basic Clinical Radiobiology , 1997 .
[99] L. H. Gray,et al. The Histological Structure of Some Human Lung Cancers and the Possible Implications for Radiotherapy , 1955, British Journal of Cancer.
[100] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[101] C Decaestecker,et al. Discrimination between dysplastic and malignant epithelium of the ampulla of vater based on quantitative image cytometric data. , 2000, Analytical and quantitative cytology and histology.
[102] T. W. Ridler,et al. Picture thresholding using an iterative selection method. , 1978 .
[103] N. Fusenig,et al. Angiogenic switch occurs late in squamous cell carcinomas of human skin , 2000, British Journal of Cancer.
[104] David Pycock,et al. Robust statistical models for cell image interpretation , 1997, Image Vis. Comput..
[105] K Wenzelides,et al. The PARTICLE expert system for tumor grading by automated image analysis. , 1989, Analytical and quantitative cytology and histology.
[106] J. Bussink,et al. Vascular architecture and hypoxic profiles in human head and neck squamous cell carcinomas , 2000, British Journal of Cancer.
[107] Stephen J. Roberts,et al. Robust cell nuclei segmentation using statistical modelling , 1998 .
[108] Ela Claridge,et al. Low-level grouping mechanisms for contour completion , 2000, Inf. Sci..
[109] Deborah B. Thompson,et al. AUTOMATED LOCATION OF DYSPLASTIC FIELDS IN COLORECTAL HISTOLOGY USING IMAGE TEXTURE ANALYSIS , 1997, The Journal of pathology.
[110] Constantinos Loukas,et al. Automated segmentation of cancer cell nuclei in complex tissue sections , 2001, European Conference on Biomedical Optics.