Literatura académica sobre el tema "Tissue microarray"
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Artículos de revistas sobre el tema "Tissue microarray"
Yang, Jun, Mingjuan Zhang, Baoshan Su, XiaoLi Chen y AnJing Kang. "A novel tissue microarray instrumentation:The HT-1 tissue microarrayer". Indian Journal of Pathology and Microbiology 55, n.º 3 (2012): 314. http://dx.doi.org/10.4103/0377-4929.101736.
Texto completoBarrette, Kathleen, Joost J. van den Oord y Marjan Garmyn. "Tissue Microarray". Journal of Investigative Dermatology 134, n.º 9 (septiembre de 2014): 1–4. http://dx.doi.org/10.1038/jid.2014.277.
Texto completoRoszkowiak, Lukasz y Carlos Lopez. "PATMA: parser of archival tissue microarray". PeerJ 4 (1 de diciembre de 2016): e2741. http://dx.doi.org/10.7717/peerj.2741.
Texto completoKaur, Rashmeet, Nagaraja A, Richa Bansal, Sujata Saxena y Bhavana Rai. "Tissue microarray- A review". International Journal of Oral Health Dentistry 4, n.º 3 (15 de octubre de 2018): 152–55. http://dx.doi.org/10.18231/2395-499x.2018.0035.
Texto completoKim, Woo Ho. "High-Density Tissue Microarray". American Journal of Surgical Pathology 26, n.º 9 (septiembre de 2002): 1236–37. http://dx.doi.org/10.1097/00000478-200209000-00017.
Texto completoRubin, Mark A. y Rodney L. Dunn. "High-Density Tissue Microarray". American Journal of Surgical Pathology 26, n.º 9 (septiembre de 2002): 1237–38. http://dx.doi.org/10.1097/00000478-200209000-00018.
Texto completoPage, Robert N., Roy King y Paul B. Googe. "Tissue Microarray in Melanoma". Journal of Histotechnology 26, n.º 4 (diciembre de 2003): 271–74. http://dx.doi.org/10.1179/his.2003.26.4.271.
Texto completoPackeisen, J. "Demystified ... Tissue microarray technology". Molecular Pathology 56, n.º 4 (1 de agosto de 2003): 198–204. http://dx.doi.org/10.1136/mp.56.4.198.
Texto completoJiang, Hui-Yong, Xue-Feng Zhang, Li Liu, Hui-Ling Li y Tong Zhao. "A novel tissue array technique for high-throughput tissue microarray analysis — microarray groups". In Vitro Cellular & Developmental Biology - Animal 43, n.º 3-4 (21 de mayo de 2007): 109–12. http://dx.doi.org/10.1007/s11626-007-9019-3.
Texto completoRangel, Catherine Starrs. "The Tissue Microarray: Helpful Hints!" Journal of Histotechnology 25, n.º 2 (junio de 2002): 93–100. http://dx.doi.org/10.1179/his.2002.25.2.93.
Texto completoTesis sobre el tema "Tissue microarray"
Amaral, Telmo. "Analysis of breast tissue microarray spots". Thesis, University of Dundee, 2010. https://discovery.dundee.ac.uk/en/studentTheses/0a83915d-2f11-4b89-9c24-8dc3c15346f2.
Texto completoNguyễn, Hoài Nam. "Méthodes et algorithmes de segmentation et déconvolution d'images pour l'analyse quantitative de Tissue Microarrays". Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S104/document.
Texto completoThis thesis aims at developing dedicated methods for quantitative analysis of Tissue Microarray (TMA) images acquired by fluorescence scanners. We addressed there issues in biomedical image processing, including segmentation of objects of interest (i.e. tissue samples), correction of acquisition artifacts during scanning process and improvement of acquired image resolution while taking into account imaging modality and scanner design. The developed algorithms allow to envisage a novel automated platform for TMA analysis, which is highly required in cancer research nowadays. On a TMA slide, multiple tissue samples which are collected from different donors are assembled according to a grid structure to facilitate their identification. In order to establish the link between each sample and its corresponding clinical data, we are not only interested in the localization of these samples but also in the computation of their array (row and column) coordinates according to the design grid because the latter is often very deformed during the manufacturing of TMA slides. However, instead of directly computing array coordinates as existing approach, we proposed to reformulate this problem as the approximation of the deformation of the theoretical TMA grid using “thin plate splines” given the result of tissue sample localization. We combined a wavelet-based detection and a ellipse-based segmentation to eliminate false alarms and thus improving the localization result of tissue samples. According to the scanner design, images are acquired pixel by pixel along each line, with a change of scan direction between two subsequent lines. Such scanning system often suffers from pixel mis-positioning (jitter) due to imperfect synchronization of mechanical and electronic components. To correct these scanning artifacts, we proposed a variational method based on the estimation of pixel displacements on subsequent lines. This method, inspired from optical flow methods, consists in estimating a dense displacement field by minimizing an energy function composed of a nonconvex data fidelity term and a convex regularization term. We used half-quadratic splitting technique to decouple the original problem into two small sub-problems: one is convex and can be solved by standard optimization algorithm, the other is non-convex but can be solved by a complete search. To improve the resolution of acquired fluorescence images, we introduced a method of image deconvolution by considering a family of convex regularizers. The considered regularizers are generalized from the concept of Sparse Variation which combines the L1 norm and Total Variation (TV) to favors the co-localization of high-intensity pixels and high-magnitude gradient. The experiments showed that the proposed regularization approach produces competitive deconvolution results on fluorescence images, compared to those obtained with other approaches such as TV or the Schatten norm of Hessian matrix
Sievertzon, Maria. "Transcript profiling of small tissue samples using microarray technology". Doctoral thesis, Stockholm Department of Biotechnology, Royal Institute of Technology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-158.
Texto completoCheng, Yabin. "Tissue microarray based biomarker study in human cutaneous melanoma". Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/46655.
Texto completoXie, Dan y 謝丹. "Application of high-throughput tissue microarray technology in cancer research". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30283619.
Texto completoMckenzie, Gavin Medical Sciences Faculty of Medicine UNSW. "The analysis of signalling pathways in sporadic colorectal carcinoma using tissue microarrays". Publisher:University of New South Wales. Medical Sciences, 2008. http://handle.unsw.edu.au/1959.4/43370.
Texto completoJernås, Margareta. "Microarray analysis of gene expression in human adipocytes and adipose tissue /". Göteborg : Institute of Medicine, Dept. of Molecular and Clinical Medicine, Sahlgrenska Academy, Göteborg University, 2008. http://hdl.handle.net/2077/9583.
Texto completoPANSINI, P. F. "Potencial Prognóstico da Survivina em Carcinoma Epidermóide da Cavidade Bucal". Universidade Federal do Espírito Santo, 2017. http://repositorio.ufes.br/handle/10/7104.
Texto completoO carcinoma epidermóide de cabeça e pescoço (CECP) é o sexto tipo de câncer mais comum em todo o mundo. Nos últimos anos, tem sido sugerida a participação da survivina na progressão tumoral em CECP. Este estudo teve como objetivo avaliar a survivina como potencial biomarcador de progressão tumoral em CECB. Foram utilizados no estudo dados clínicos e amostras biológicas de 115 indivíduos com carcinoma epidermóide da cavidade bucal. Lâminas contendo tecidos tumorais coradas pelo método hematoxilina e eosina foram usadas para as análises histopatológicas para avaliar o infiltrado linfocitário tumoral, padrão de invasão tumoral, gradação tumoral, invasão vascular, linfática e perineural. Tissue Microarrays foram construídos para realizar a análise imunohistoquímica da expressão da proteína survivina utilizando o anticorpo primário monoclonal de coelho anti-survivina. Para avaliar as associações entre as variáveis estudadas foram utilizados os testes Qui-Quadrado e o Exato de Fisher. A comparação das médias dos segmentos foi obtida pelo teste T de amostras independentes. As curvas de sobrevida foram calculadas pelo modelo de Kaplan-Meier e confirmadas pelo modelo multivariado de Cox. Nossos resultados mostraram existir correlação entre o infiltrado linfocitário tumoral alto, tamanho do tumor primário T1/T2 (p = 0,001) e estadiamento clínico I e II (p = 0,005). O padrão de invasão tumoral tipo IV foi correlacionado com o tamanho do tumor primário T3/T4 (p = 0,006) e estadiamento clínico avançado (estádio III e IV) (p = 0,028). Invasão perineural foi associada com o tamanho do tumor primário T1/T2 (p = 0,035). A expressão nuclear da survivina na porção mediana do tumor mostrou associação com a metástase em linfonodos regionais (p = 0,004) e o estadiamento clínico (p = 0,041). A análise regressiva multivariada confirmou que as variáveis tamanho do tumor primário (p = 0,004) e acometimento linfonodal (p= 0,06) são fatores prognósticos independentes para sobrevida global, enquanto o etilismo influencia na sobrevida livre de doença (p = 0,048). Com este estudo pode-se concluir que a elevada expressão da survivina está correlacionada com o comportamento tumoral mais agressivo, estadiamento clínico avançado, presença de mestástase linfonodal, podendo ser considerada como indicador de prognóstico em pacientes com CECB. A variável histopatológica padrão de invasão tumoral mostrou que sua correlação com tamanho do tumor primário e estadiamento clínico avançado podendo estar relacionada ao pior prognóstico dos pacientes em CECB.
Foster, Cheryl June. "Identifying a prognostic test in follicular lymphoma using a tissue microarray and immunohistochemistry". Thesis, Kingston, Ont. : [s.n.], 2008. http://hdl.handle.net/1974/1296.
Texto completoHabibi, Golareh. "Y-box binding protein-1 (YB-1) is a bio-marker of aggressiveness in breast cancer and is a potential target for therapeutic intervention". Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/911.
Texto completoLibros sobre el tema "Tissue microarray"
-S, Liu Brian C. y Ehrlich Joshua R, eds. Tissue proteomics: Pathways, biomarkers, and drug discovery. Totowa, N.J: Humana Press, 2008.
Buscar texto completoSimon, Ronald, ed. Tissue Microarrays. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-806-5.
Texto completoTissue microarrays: Methods and protocols. New York, N.Y: Humana Press, 2010.
Buscar texto completoEhrlich, Joshua R. y Brian Liu. Tissue Proteomics: Pathways, Biomarkers, and Drug Discovery. Humana Press, 2010.
Buscar texto completoTissue proteomics: Pathways, biomarkers, and drug discovery. Totowa, N.J: Humana Press, 2008.
Buscar texto completoTissue Proteomics: Pathways, Biomarkers, and Drug Discovery (Methods in Molecular Biology). Humana Press, 2008.
Buscar texto completoSimon, Ronald. Tissue Microarrays: Methods and Protocols. Humana Press, 2016.
Buscar texto completoHewitt, Stephen M. Tissue Microarrays: Methods and Applications (Methods in Molecular Biology). Humana Press, 2007.
Buscar texto completoZrazhevskiy, P. y X. Gao. Bioconjugated quantum dots for tumor molecular imaging and profiling. Editado por A. V. Narlikar y Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533060.013.17.
Texto completoCapítulos de libros sobre el tema "Tissue microarray"
Wilkerson, Myra L. y Stephen M. Hewitt. "Tissue Microarray". En Handbook of Practical Immunohistochemistry, 105–17. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-1578-1_10.
Texto completoWilkerson, Myra L. y Stephen Hewitt. "Tissue Microarray". En Handbook of Practical Immunohistochemistry, 161–72. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83328-2_11.
Texto completoWilkerson, Myra y Erin Powell. "Tissue Microarray". En Handbook of Practical Immunohistochemistry, 45–54. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8062-5_6.
Texto completoFaoro, Valentina y Anna Sapino. "Tissue Microarray (TMA)". En Guidelines for Molecular Analysis in Archive Tissues, 23–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17890-0_5.
Texto completoKoo, Matthew, Jill M. Squires, Daphne Ying y Jiaoti Huang. "Making a Tissue Microarray". En Methods in Molecular Biology, 313–23. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8935-5_27.
Texto completoKorenberg, Michael J., Pedro Farinha y Randy D. Gascoyne. "Predicting Survival in Follicular Lymphoma Using Tissue Microarrays". En Microarray Data Analysis, 255–68. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-390-5_16.
Texto completoSimon, Ronald. "Applications of Tissue Microarray Technology". En Methods in Molecular Biology, 1–16. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-806-5_1.
Texto completoGaudreau, Pierre-Olivier, Isabelle Cousineau y John Stagg. "Optimal CCN4 Immunofluorescence for Tissue Microarray". En Methods in Molecular Biology, 13–21. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2744-0_2.
Texto completoSaremi, Nassim y Alfred K. Lam. "Application of Tissue Microarray in Esophageal Adenocarcinoma". En Methods in Molecular Biology, 105–18. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7734-5_10.
Texto completoHu, Zhongting, Elbert Chang y Melissa Hodeib. "An Alternative Technology to Prepare Tissue Microarray Using Frozen Tissue Samples". En Methods in Molecular Biology, 81–91. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-806-5_9.
Texto completoActas de conferencias sobre el tema "Tissue microarray"
Can, Ali, Musodiq O. Bello y Michael J. Gerdes. "Quantification of Subcellular Molecules in Tissue Microarray". En 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.624.
Texto completoWu, Jiahua, Junyu Dong y Huiyu Zhou. "Image quantification of high-throughput tissue microarray". En Medical Imaging, editado por Armando Manduca y Amir A. Amini. SPIE, 2006. http://dx.doi.org/10.1117/12.653564.
Texto completoAmaral, T., S. McKenna, K. Robertson y A. Thompson. "Automated classification of breast tissue microarray spots." En CTRC-AACR San Antonio Breast Cancer Symposium: 2008 Abstracts. American Association for Cancer Research, 2009. http://dx.doi.org/10.1158/0008-5472.sabcs-4010.
Texto completoXing, Fuyong, Baiyang Liu, Xin Qi, David J. Foran y Lin Yang. "Digitized tissue microarray classification using sparse reconstruction". En SPIE Medical Imaging, editado por David R. Haynor y Sébastien Ourselin. SPIE, 2012. http://dx.doi.org/10.1117/12.911900.
Texto completoCline, Harvey E., Ali Can y Dirk Padfield. "Segmentation of prostate cancer tissue microarray images". En Biomedical Optics 2006, editado por Daniel L. Farkas, Dan V. Nicolau y Robert C. Leif. SPIE, 2006. http://dx.doi.org/10.1117/12.643180.
Texto completoGalizia, Antonella, Federica Viti, Alessandro Orro, Daniele D'Agostino, Ivan Merelli, Luciano Milanesi y Andrea Clematis. "TMAinspect, an EGEE Framework for Tissue MicroArray Image Handling". En 2008 8th IEEE International Symposium on Cluster Computing and the Grid (CCGrid). IEEE, 2008. http://dx.doi.org/10.1109/ccgrid.2008.100.
Texto completo"SCORING OF BREAST TISSUE MICROARRAY SPOTS THROUGH ORDINAL REGRESSION". En International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0001808202430248.
Texto completoZhou, A., Z. Zhou y P. Chen. "Microarray Analysis of Noncoding RNA in Lung Tissue of COPD Patients". En American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a5381.
Texto completoNguyen, Hoai-Nam, Charles Kervrann, Cyril Cauchois y Vincent Paveau. "Automatic core segmentation and registration for fast tissue microarray de-arraying". En 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015). IEEE, 2015. http://dx.doi.org/10.1109/isbi.2015.7164147.
Texto completoAmaral, Telmo, Stephen McKenna, Katherine Robertson y Alastair Thompson. "Classification of breast-tissue microarray spots using colour and local invariants". En 2008 5th IEEE International Symposium on Biomedical Imaging (ISBI 2008). IEEE, 2008. http://dx.doi.org/10.1109/isbi.2008.4541167.
Texto completoInformes sobre el tema "Tissue microarray"
Dolled-Filhart, Marisa. Tissue Microarray Based Investigation of Stat3 Signaling Pathway in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, mayo de 2004. http://dx.doi.org/10.21236/ada425703.
Texto completoMehra, Rohit. Tissue Microarray Assessment of Novel Prostate Cancer Biomarkers AMACR and EZH2 and Immunologic Response to Them in African-American and Caucasian Men. Fort Belvoir, VA: Defense Technical Information Center, abril de 2007. http://dx.doi.org/10.21236/ada470995.
Texto completoMeir, Shimon, Michael S. Reid, Cai-Zhong Jiang, Amnon Lers y Sonia Philosoph-Hadas. Molecular Studies of Postharvest Leaf and Flower Senescence. United States Department of Agriculture, enero de 2011. http://dx.doi.org/10.32747/2011.7592657.bard.
Texto completoRimm, David L. Spectral Analysis of Breast Cancer on Tissue Microarrays: Seeing Beyond Morphology. Fort Belvoir, VA: Defense Technical Information Center, mayo de 2003. http://dx.doi.org/10.21236/ada417663.
Texto completoRimm, David L. Outcome Based Screening for Prognostic Phospho-RTK (Receptor Tyrosine Kinase) Antibodies Using Tissue Microarrays. Fort Belvoir, VA: Defense Technical Information Center, agosto de 2002. http://dx.doi.org/10.21236/ada410085.
Texto completoRimm, David. Outcome Based Screening for Prognostic Phospho-RTK (Receptor Tyrosine Kinase) Antibodies Using Tissue Microarrays). Fort Belvoir, VA: Defense Technical Information Center, agosto de 2004. http://dx.doi.org/10.21236/ada430123.
Texto completoRimm, David L. Outcome Based Screening for Prognostic Phospho-RTK (Receptor Tyrosine Kinase) Antibodies Using Tissue Microarrays. Fort Belvoir, VA: Defense Technical Information Center, agosto de 2003. http://dx.doi.org/10.21236/ada420064.
Texto completoGinzberg, Idit y Walter De Jong. Molecular genetic and anatomical characterization of potato tuber skin appearance. United States Department of Agriculture, septiembre de 2008. http://dx.doi.org/10.32747/2008.7587733.bard.
Texto completoDroby, Samir, Michael Wisniewski, Ron Porat y Dumitru Macarisin. Role of Reactive Oxygen Species (ROS) in Tritrophic Interactions in Postharvest Biocontrol Systems. United States Department of Agriculture, diciembre de 2012. http://dx.doi.org/10.32747/2012.7594390.bard.
Texto completoHeifetz, Yael y Michael Bender. Success and failure in insect fertilization and reproduction - the role of the female accessory glands. United States Department of Agriculture, diciembre de 2006. http://dx.doi.org/10.32747/2006.7695586.bard.
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