Literatura académica sobre el tema "CLASSIFICATION OF BRAIN TUMOR"
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Artículos de revistas sobre el tema "CLASSIFICATION OF BRAIN TUMOR"
Manasa, P. Venkata Sai, J. Jeevitha, M. Lakshmi Chandana, M. Jeevana Sravanthi y M. Ali Shaik. "Brain Tumor Radiogenomic Classification Using Deep Learning". International Journal of Research Publication and Reviews 4, n.º 3 (17 de marzo de 2023): 1830–36. http://dx.doi.org/10.55248/gengpi.2023.4.33058.
Texto completoA, Ms Vidhya, Dr Parameswari R y Ms Sathya S. "Brain Tumor Classification Using Various Machine Learning Algorithms". International Journal of Research in Arts and Science 5, Special Issue (30 de agosto de 2019): 258–70. http://dx.doi.org/10.9756/bp2019.1002/25.
Texto completoPunam, Saudagar. "Deep Learning Approach for Brain Tumor Classification". International Journal for Research in Applied Science and Engineering Technology 9, n.º VI (30 de junio de 2021): 3094–98. http://dx.doi.org/10.22214/ijraset.2021.35648.
Texto completoPol, Jay. "Brain Tumor Image Classification using CNN". International Journal for Research in Applied Science and Engineering Technology 10, n.º 6 (30 de junio de 2022): 1934–41. http://dx.doi.org/10.22214/ijraset.2022.44191.
Texto completoDozic, Slobodan, Dubravka Cvetkovic-Dozic, Milica Skender-Gazibara y Branko Dozic. "Review of the World Health Organization classification of tumors of the nervous system". Archive of Oncology 10, n.º 3 (2002): 175–77. http://dx.doi.org/10.2298/aoo0203175d.
Texto completoNarawade, Vaibhav, Chaitali Shetty, Purva Kharsambale, Samruddhi Bhosale y Sushree Rout. "Brain Tumor Classification using Transfer Learning". Journal of Trends in Computer Science and Smart Technology 5, n.º 3 (septiembre de 2023): 223–47. http://dx.doi.org/10.36548/jtcsst.2023.3.002.
Texto completoWedad Abdul Khuder Naser *. "Brain tumor classification and diagnosis techniques". Global Journal of Engineering and Technology Advances 10, n.º 2 (28 de febrero de 2022): 071–74. http://dx.doi.org/10.30574/gjeta.2022.10.2.0036.
Texto completoKadam, Ankita. "Brain Tumor Classification using Deep Learning Algorithms". International Journal for Research in Applied Science and Engineering Technology 9, n.º 12 (31 de diciembre de 2021): 417–26. http://dx.doi.org/10.22214/ijraset.2021.39280.
Texto completoA., Afreen Habiba. "Diagnosis of Brain Tumor using Semantic Segmentation and Advance-CNN Classification". International Journal of Psychosocial Rehabilitation 24, n.º 5 (31 de marzo de 2020): 1204–24. http://dx.doi.org/10.37200/ijpr/v24i5/pr201795.
Texto completoHavaei, Mohammad, Hugo Larochelle, Philippe Poulin y Pierre-Marc Jodoin. "Within-brain classification for brain tumor segmentation". International Journal of Computer Assisted Radiology and Surgery 11, n.º 5 (3 de noviembre de 2015): 777–88. http://dx.doi.org/10.1007/s11548-015-1311-1.
Texto completoTesis sobre el tema "CLASSIFICATION OF BRAIN TUMOR"
Kalvakolanu, Anjaneya Teja Sarma. "Brain Tumor Detection and Classification from MRI Images". DigitalCommons@CalPoly, 2021. https://digitalcommons.calpoly.edu/theses/2267.
Texto completoChang, Spencer J. "Brain Tumor Classification Using Hit-or-Miss Capsule Layers". DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2006.
Texto completoKampouraki, Vasileia. "Patch-level classification of brain tumor tissue in digital histopathology slides with Deep Learning". Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177361.
Texto completoHrabovszki, Dávid. "Classification of brain tumors in weakly annotated histopathology images with deep learning". Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177271.
Texto completoKanli, Georgia. "Method for the classification of brain cancer treatment's responsiveness via physical parameters of DCE-MRI data". Thesis, Stockholms universitet, Fysikum, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-116822.
Texto completoKirsch, Matthias, Thomas Santarius, Peter M. Black y Gabriele Schackert. "Therapeutic Anti-Angiogenesis for Malignant Brain Tumors". Karger, 2001. https://tud.qucosa.de/id/qucosa%3A27619.
Texto completoMaligne Hirntumoren, insbesondere die malignen Gliome, haben trotz multimodaler Therapieansätze eine unverändert schlechte Prognose. Diese Aggressivität korreliert mit der Tatsache, daß maligne Gliome zu den gefäßreichsten Tumoren zählen, die wir kennen. Die Quantifizierung der Gefäßdichte in diesen Tumoren erlaubte die Korrelation zur Überlebenszeit der Patienten. Da das Tumorwachstum von einer begleitenden Neovaskularisierung abhängt, wurden erste experimentelle Therapieansätze durchgeführt, um das Tumorwachstum durch Inhibierung der Neovaskularisierung zu verhindern. Inhibitoren der Angiogenese, z.B. TNP-470, Suramin und Angiostatin hemmen die Proliferation von Endothelzellen und die Ausbildung eines funktionsfähigen Gefäßbettes. Erste experimentelle Ansätze haben ihre tumorstatische Wirksamkeit in vivo bewiesen. Zur klinischen Behandlung wären diese Substanzen in Verbindung mit bestehenden Therapien einsetzbar, insbesondere für die Behandlung multipler Tumoren und zur postoperativen Therapie. Diese Übersichtsarbeit beschreibt die neuesten anti-angiogenen Therapiekonzepte besonders mit Hinblick auf Substanzen, die in ersten klinischen Studien eingesetzt werden.
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
Shen, Shan. "MRI brain tumour classification using image processing and data mining". Thesis, University of Strathclyde, 2004. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21543.
Texto completoZhang, Nan. "Feature selection based segmentation of multi-source images : application to brain tumor segmentation in multi-sequence MRI". Phd thesis, INSA de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00701545.
Texto completoVicente, Robledo Javier. "Clinical Decision Support Systems for Brain Tumour Diagnosis: Classification and Evaluation Approaches". Doctoral thesis, Editorial Universitat Politècnica de València, 2012. http://hdl.handle.net/10251/17468.
Texto completoVicente Robledo, J. (2012). Clinical Decision Support Systems for Brain Tumour Diagnosis: Classification and Evaluation Approaches [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17468
Palancia
Alberts, Esther [Verfasser], Björn [Akademischer Betreuer] Menze, Björn [Gutachter] Menze y Claus [Gutachter] Zimmer. "Multi-modal Multi-temporal Brain Tumor Segmentation, Growth Analysis and Texture-based Classification / Esther Alberts ; Gutachter: Björn Menze, Claus Zimmer ; Betreuer: Björn Menze". München : Universitätsbibliothek der TU München, 2019. http://d-nb.info/118744393X/34.
Texto completoLibros sobre el tema "CLASSIFICATION OF BRAIN TUMOR"
K, Kokula Krishna Hari, ed. An Image Segmentation and Classification for Brain Tumor Detection using Pillar K-Means Algorithm. Chennai, India: Association of Scientists, Developers and Faculties, 2016.
Buscar texto completo1913-, Fields William S., ed. Primary brain tumors: A review of histologic classification. New York: Springer-Verlag, 1989.
Buscar texto completoBuell, Duncan A. Binary quadratic forms: Classical theory and modern computations. New York: Springer-Verlag, 1989.
Buscar texto completoNagai, Masakatsu, ed. Brain Tumor. Tokyo: Springer Japan, 1996. http://dx.doi.org/10.1007/978-4-431-66887-9.
Texto completoLiau, Linda M., Donald P. Becker, Timothy F. Cloughesy y Darell D. Bigner. Brain Tumor Immunotherapy. New Jersey: Humana Press, 2000. http://dx.doi.org/10.1385/1592590357.
Texto completoGoldfarb, Ronald H., ed. Brain Tumor Invasiveness. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2622-3.
Texto completoLiau, Linda M., Donald P. Becker, Timothy F. Cloughesy y Darell D. Bigner, eds. Brain Tumor Immunotherapy. Totowa, NJ: Humana Press, 2001. http://dx.doi.org/10.1007/978-1-59259-035-3.
Texto completoHattingen, Elke y Ulrich Pilatus, eds. Brain Tumor Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-642-45040-2.
Texto completoH, Goldfarb Ronald, ed. Brain tumor invasiveness. Dordrecht: Kluwer Academic, 1994.
Buscar texto completoSingh, Sheila K. y Chitra Venugopal, eds. Brain Tumor Stem Cells. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-8805-1.
Texto completoCapítulos de libros sobre el tema "CLASSIFICATION OF BRAIN TUMOR"
Wechsler, Wolfgang y Guido Reifenberger. "Histopathological Classification of Brain Tumors According to the Revised WHO Classification: Current State and Perspectives". En Brain Tumor, 3–20. Tokyo: Springer Japan, 1996. http://dx.doi.org/10.1007/978-4-431-66887-9_1.
Texto completoLerousseau, Marvin, Eric Deutsch y Nikos Paragios. "Multimodal Brain Tumor Classification". En Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 475–86. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72087-2_42.
Texto completoKathawala, Fatema, Ami Shah, Jugal Shah, Shranik Vora y Sonali Patil. "Brain Tumor Detection and Classification". En Advances in Computing and Intelligent Systems, 547–56. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0222-4_52.
Texto completoWechsler, W. y G. Reifenberger. "Immunohistochemistry in Brain Tumor Classification". En Neuro-Oncology, 11–19. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3152-0_2.
Texto completoTeoh, Teik Toe. "CNN for Brain Tumor Classification". En Convolutional Neural Networks for Medical Applications, 19–34. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8814-1_2.
Texto completoPatil, Saraswati, Sangita Jaybhaye, Sanjyot Kotgire, Shravan Raina, Somanshu Bhat y Saksham Sharma. "Brain Tumor Detection and Classification". En IOT with Smart Systems, 379–91. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3761-5_35.
Texto completoPfister, Stefan M., David Capper y David T. W. Jones. "Modern Principles of CNS Tumor Classification". En Brain Tumors in Children, 117–29. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-43205-2_6.
Texto completoWaghmare, Vishal K. y Maheshkumar H. Kolekar. "Brain Tumor Classification Using Deep Learning". En Studies in Big Data, 155–75. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4112-4_8.
Texto completoMeena, S. Divya, Srirama V. S. S. Bulusu, V. Sai Siddharth, S. Prathik Reddy y J. Sheela. "Brain Tumor Classification Using Transfer Learning". En Machine Learning and Artificial Intelligence in Healthcare Systems, 191–209. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003265436-9.
Texto completoBahuguna, Aman, Azhar Ashraf, Kavita, Sahil Verma y Poonam Negi. "Brain Tumor Classification from MRI Scans". En International Conference on Innovative Computing and Communications, 713–25. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3010-4_57.
Texto completoActas de conferencias sobre el tema "CLASSIFICATION OF BRAIN TUMOR"
Amin, Javeria, Muhammad Sharif, Mudassar Raza, Tanzila Saba y Amjad Rehman. "Brain Tumor Classification: Feature Fusion". En 2019 International Conference on Computer and Information Sciences (ICCIS). IEEE, 2019. http://dx.doi.org/10.1109/iccisci.2019.8716449.
Texto completoJairam, S. J. A., D. Lokeshwar, B. Divya y P. Mohamed Fathimal. "Brain Tumor Detection Using Deep Learning". En International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-5d1g8v.
Texto completoPaul, Justin S., Andrew J. Plassard, Bennett A. Landman y Daniel Fabbri. "Deep learning for brain tumor classification". En SPIE Medical Imaging, editado por Andrzej Krol y Barjor Gimi. SPIE, 2017. http://dx.doi.org/10.1117/12.2254195.
Texto completoSaleh, Ahmad, Rozana Sukaik y Samy S. Abu-Naser. "Brain Tumor Classification Using Deep Learning". En 2020 International Conference on Assistive and Rehabilitation Technologies (iCareTech). IEEE, 2020. http://dx.doi.org/10.1109/icaretech49914.2020.00032.
Texto completoChaitanya, Koganti, Kolisetty Sai Saran, Inapanurthi Swarupa y G. Jaya Lakshmi. "Brain Tumor Classification using DeepResidual Learning". En 2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2022. http://dx.doi.org/10.1109/iciccs53718.2022.9787993.
Texto completoRochmawati, Naim, Hanik Badriyah Hidayati, Yuni Yamasari, Wiyli Yustanti, I. Made Suartana, Agus Prihanto y Aditya Prapanca. "Brain Tumor Classification Using Transfer Learning". En 2022 Fifth International Conference on Vocational Education and Electrical Engineering (ICVEE). IEEE, 2022. http://dx.doi.org/10.1109/icvee57061.2022.9930403.
Texto completoSimon, Eliott y Alexia Briassouli. "Vision Transformers for Brain Tumor Classification". En 9th International Conference on Bioimaging. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0010834300003123.
Texto completoVenkata Subbarao, M., G. Challa Ram, D. Girish Kumar y Sudheer Kumar Terlapu. "Brain Tumor Classification using Ensemble Classifiers". En 2022 International Conference on Electronics and Renewable Systems (ICEARS). IEEE, 2022. http://dx.doi.org/10.1109/icears53579.2022.9752177.
Texto completoSorte, Ashish, Ruchita Sathe, Shubham Yadav y Chitra Bhole. "Brain Tumor Classification using Deep Learning". En 2022 5th International Conference on Advances in Science and Technology (ICAST). IEEE, 2022. http://dx.doi.org/10.1109/icast55766.2022.10039550.
Texto completoShaji, Thejus, K. Ravi, E. Vignesh y A. Sinduja. "Brain Tumor Segmentation Using Modified Double U-Net Architecture". En International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-52096g.
Texto completoInformes sobre el tema "CLASSIFICATION OF BRAIN TUMOR"
Hedyehzadeh, Mohammadreza, Shadi Yoosefian, Dezfuli Nezhad y Naser Safdarian. Evaluation of Conventional Machine Learning Methods for Brain Tumour Type Classification. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, junio de 2020. http://dx.doi.org/10.7546/crabs.2020.06.14.
Texto completoAnantharajan, Shenbagarajan y Shenbagalakshmi Gunasekaran. Detection and Classification of MRI Brain Tumour Using GLCM and Enhanced K-NN. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, febrero de 2021. http://dx.doi.org/10.7546/crabs.2021.02.13.
Texto completoArun, Ramaiah y Shanmugasundaram Singaravelan. Classification of Brain Tumour in Magnetic Resonance Images Using Hybrid Kernel Based Support Vector Machine. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, octubre de 2019. http://dx.doi.org/10.7546/crabs.2019.10.12.
Texto completoLaramore, G. E., B. R. Griffin y A. Spence. American brain tumor patients treated with BNCT in Japan. Office of Scientific and Technical Information (OSTI), noviembre de 1995. http://dx.doi.org/10.2172/421335.
Texto completoLojzim, Joshua Michael y Marcus Fries. Brain Tumor Segmentation Using Morphological Processing and the Discrete Wavelet Transform. Journal of Young Investigators, agosto de 2017. http://dx.doi.org/10.22186/jyi.33.3.55-62.
Texto completoMajewska, Anna y Edward B. Brown. The Influence of Neuronal Activity on Breast Tumor Metastasis to the Brain. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 2008. http://dx.doi.org/10.21236/ada502596.
Texto completoMajewska, Anna K. y Edward B. Brown. The Influence of Neuronal Activity on Breast Tumor Metastasis to the Brain. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 2009. http://dx.doi.org/10.21236/ada513293.
Texto completoLi, Xiao-Nan. Harnessing Autopsied DIPG Tumor Tissues for Orthotopic Xenograft Model Development in the Brain Stems of SCID Mice. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 2012. http://dx.doi.org/10.21236/ada568355.
Texto completoPhillips, Peter C. Early Detection of NF1 Brain Tumor Growth and Treatment Response by MRI, MRS and PET in a Trial of Novel Antitumor Drugs. Fort Belvoir, VA: Defense Technical Information Center, octubre de 1997. http://dx.doi.org/10.21236/ada376214.
Texto completoTian, Cong, Jianlong Shu, Wenhui Shao, Zhengxin Zhou, Huayang Guo y Jingang Wang. The efficacy and safety of IL Inhibitors, TNF-α Inhibitors, and JAK Inhibitor on ankylosing spondylitis: A Bayesian network meta-analysis of a “randomized, double-blind, placebo-controlled” trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, septiembre de 2022. http://dx.doi.org/10.37766/inplasy2022.9.0117.
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