Littérature scientifique sur le sujet « Histopathologie – Innovation »
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Articles de revues sur le sujet "Histopathologie – Innovation"
Danks, Janine A., Roula Papadopoulos et Nicholas J. Vardaxis. « Innovation in Histopathology Teaching ». Journal of Histotechnology 32, no 3 (septembre 2009) : 119–21. http://dx.doi.org/10.1179/his.2009.32.3.119.
Texte intégralTacha, David E., Linda C. Bloom et Ball Lauren R. « Histopathology Instrumentation : Innovations in the 1980s ». Laboratory Medicine 18, no 8 (1 août 1987) : 519–23. http://dx.doi.org/10.1093/labmed/18.8.519.
Texte intégralNaik, Paras, Jem Rashbass, Mark Bennett, Sue Cossins et Nick R. Griffin. « IT innovation in histopathology recruitment, training and research ». British Journal of Hospital Medicine 66, no 10 (octobre 2005) : 563–65. http://dx.doi.org/10.12968/hmed.2005.66.10.19893.
Texte intégralBardhan, Neelkanth M., Vivek Rastogi, Rebecca L. Stone et Angela M. Belcher. « Abstract 6166 : A whole-organ ex vivo optical imaging technique for non-destructive, more precise identification of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes ». Cancer Research 84, no 6_Supplement (22 mars 2024) : 6166. http://dx.doi.org/10.1158/1538-7445.am2024-6166.
Texte intégralKarthikeyan Ramalingam,. « Innovations in Oral Pathology Laboratory - A Mini Review ». International Journal of Head and Neck Pathology 6, no 2 (13 octobre 2023) : 1–5. http://dx.doi.org/10.56501/intjheadneckpathol.v6i1.914.
Texte intégralAhmed, Shakil, Asadullah Shaikh, Hani Alshahrani, Abdullah Alghamdi, Mesfer Alrizq, Junaid Baber et Maheen Bakhtyar. « Transfer Learning Approach for Classification of Histopathology Whole Slide Images ». Sensors 21, no 16 (9 août 2021) : 5361. http://dx.doi.org/10.3390/s21165361.
Texte intégralHegde, Sankalp, et Bhavadharini RM. « LuCoNet : A Convolutional Neural Network Model for Lung Cancer and Colon Cancer Prediction Using Histopathological Images ». International Research Journal of Multidisciplinary Scope 05, no 03 (2024) : 407–19. http://dx.doi.org/10.47857/irjms.2024.v05i03.0766.
Texte intégralHabawel, Candice Mabette, Listya Purnamasari, Joseph Peñano Olarve et Joseph Flores dela Cruz. « Comparative Efficacy of Different Fixed Drug Combination on Clinical Signs of Respiratory Disease in Starter Pigs ». Jurnal Veteriner 23, no 3 (30 septembre 2022) : 297–305. http://dx.doi.org/10.19087/jveteriner.2022.23.3.297.
Texte intégralMurthy, M. S. N., M. G. Jones, J. D. Davies, P. C. Jackson, J. Kulka, P. N. T. Wells, M. Halliwell et D. R. Bull. « Scanning confocal near-infra-red microscopy : a new microscopy technique for three-dimensional histopathology ». Engineering Science & ; Education Journal 4, no 5 (1 octobre 1995) : 223–30. http://dx.doi.org/10.1049/esej:19950509.
Texte intégralKirchhof, Nicole. « What Is “Preclinical Device Pathology” : An Introduction of the Unfamiliar ». Toxicologic Pathology 47, no 3 (5 février 2019) : 205–12. http://dx.doi.org/10.1177/0192623319827502.
Texte intégralThèses sur le sujet "Histopathologie – Innovation"
Habis, Antoine Aurélien. « Developing interactive artificial intelligence tools to assist pathologists with histology annotation ». Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT022.
Texte intégralHistopathology on Whole Slide Images (WSI) represents a very valuable field of medicine since the study of biopsies with microscopes can reveal several diseases that are sometimes difficult or impossible to diagnose with the naked eye or other imaging techniques. With the advent of deep learning, which requires a large number of annotated images to be effective, the need to obtain quickly high-quality annotations became clear. The purpose of this thesis is to develop artificial intelligence algorithms for fast interactive annotations and corrections to facilitate user supervision in histopathology image segmentation. This thesis presents our contributions using three different interaction strategies and underlying deep-learning mathematical formalisms. Together, our contributions cover a wide range of use cases:(1) The first tool is completely supervised and tackles the task of correcting nuclei segmentation. Nuclei are biological structures that can be observed distinctly at ×40 magnification and which are essential for several diagnosis tasks. In fact, markers such as the density of nuclei or the ratio between the area of the nucleusand that of the cytoplasm are indicative of certain conditions. The proposed tool proposes a Click and Refine pipeline, exploiting novel metrics on patch similarities and novel architecture training designs to refine four types of segmentation errors, specific to nuclei.(2) The second tool consists of a weakly supervised segmentation method tested on tumoral regions in lymph node metastatic breast cancer. These tumoral regions are biological structures clearly visible at low magnification(×5 or × 10). The first part of our algorithm provides an initial coarse segmentation of the entire WSI based on scribbles, which can then be corrected using fast interactive and non-local segmentation correction inputs.(3) Finally, the third tool proposes a completely unsupervised segmentation tool and a one-shot variant to segment complex heterogeneous biological structures on whole WSIs. The One-Shot learning version is evaluated on a dataset of kidney-dilated tubules. Dilated tubules are medium-sized biological structures that can be observed at an average magnification of ×10-20. They are indicative of some diseases such as urinary tract obstruction. The underlying proposed Deep ContourFlow method translates concepts of active contours into differentiable loss functions exploited in deep-learning architectures
Chapitres de livres sur le sujet "Histopathologie – Innovation"
Singh, Pushap Deep, Arnav Bhavsar et K. K. Harinarayanan. « Histopathology Whole Slide Image Analysis for Breast Cancer Detection ». Dans EAI/Springer Innovations in Communication and Computing, 31–56. Cham : Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15816-2_2.
Texte intégralTayel, Mazhar B., Mohamed-Amr A. Mokhtar et Ahmed F. Kishk. « Breast Cancer Diagnosis Using Histopathology and Convolution Neural Network CNN Method ». Dans International Conference on Innovative Computing and Communications, 585–600. Singapore : Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2821-5_49.
Texte intégralFridrihsone, Ilze, Ilze Strumfa, Boriss Strumfs, Andrejs Vanags, Dainis Balodis, Arvids Jakovlevs, Arnis Abolins et Janis Gardovskis. « Thyroid Nodules in Diagnostic Pathology : From Classic Concepts to Innovations ». Dans Histopathology - An Update. InTech, 2018. http://dx.doi.org/10.5772/intechopen.77117.
Texte intégralBrosnan, Bríd, Inna Skarga-Bandurova, Tetiana Biloborodova et Illia Skarha-Bandurov. « An Integrated Approach to Automated Diagnosis of Cervical Intraepithelial Neoplasia in Digital Histology Images ». Dans Caring is Sharing – Exploiting the Value in Data for Health and Innovation. IOS Press, 2023. http://dx.doi.org/10.3233/shti230220.
Texte intégralActes de conférences sur le sujet "Histopathologie – Innovation"
Bhatt, Chandradeep, Vaibhav Kumar Kapriyal, Yash Kharola, Rama Koranga, Ishita Chhetri et Teekam Singh. « Advanced Automation for Colorectal Tissue Classification in Histopathology ». Dans 2024 Asia Pacific Conference on Innovation in Technology (APCIT), 1–9. IEEE, 2024. http://dx.doi.org/10.1109/apcit62007.2024.10673436.
Texte intégralT, Soumya. « Detection and Differentiation of blood cancer cells using Edge Detection method ». Dans The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/zbua6077/ngcesi23p138.
Texte intégralKonstantinov, Andrei, et Lev Utkin. « Multiple Instance Learning through Explanation by Using a Histopathology Example ». Dans 2022 31st Conference of Open Innovations Association (FRUCT). IEEE, 2022. http://dx.doi.org/10.23919/fruct54823.2022.9770901.
Texte intégralGopalan, Vinod, Erick Chan, Debbie Ho et Alfred Lam. « EXPLORING MEDICAL STUDENT ENGAGEMENT, PERCEPTION AND COMPETENCY IN CLINICALLY INTEGRATED HISTOPATHOLOGY ». Dans 10th annual International Conference of Education, Research and Innovation. IATED, 2017. http://dx.doi.org/10.21125/iceri.2017.2204.
Texte intégralM. D, Tharun Kumar, Soniya Priyatharsini G. et Geetha S. « Breast Cancer Detection Using Machine Learning Classifier ». Dans The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/ovzf8018/ngcesi23p140.
Texte intégralKoyun, Onur Can, et Tulay Yildirim. « Adversarial Nuclei Segmentation on H&E Stained Histopathology Images ». Dans 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA). IEEE, 2019. http://dx.doi.org/10.1109/inista.2019.8778369.
Texte intégralNawandhar, Archana, Navin Kumar et Lakshmi Yamujala. « Performance Analysis of Neighborhood Component Feature Selection for Oral Histopathology Images ». Dans 2019 PhD Colloquium on Ethically Driven Innovation and Technology for Society (PhD EDITS). IEEE, 2019. http://dx.doi.org/10.1109/phdedits47523.2019.8986921.
Texte intégralLaxmisagar, H. S., et M. C. Hanumantharaju. « A Survey on Automated Detection of Breast Cancer based Histopathology Images ». Dans 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). IEEE, 2020. http://dx.doi.org/10.1109/icimia48430.2020.9074915.
Texte intégralFadhlia, Fadhlia, et Elvita Nora Susana. « Unilateral Benign Thyroid Lesion Management with Histopathology Results Following Surgery Was a Malignancy ». Dans 2nd Global Health and Innovation in conjunction with 6th ORL Head and Neck Oncology Conference (ORLHN 2021). Paris, France : Atlantis Press, 2021. http://dx.doi.org/10.2991/ahsr.k.220206.042.
Texte intégralSukweenadhi, Johan, Risma Ikawaty, Yohanes Bosko Anne Marie, Farizky Martriano Humardani, Lisa Thalia Mulyanata, Lady Theresa Adeodata Tanaya et Sulistyo Emantoko Dwi Putra. « Changes of histopathology and PPAR-ɣ gene expression in hyperglycaemia-mice ». Dans 12TH INTERNATIONAL SEMINAR ON NEW PARADIGM AND INNOVATION ON NATURAL SCIENCES AND ITS APPLICATIONS (12TH ISNPINSA) : Contribution of Science and Technology in the Changing World. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0218053.
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