Artigos de revistas sobre o tema "Whole slide images classification"
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Fell, Christina, Mahnaz Mohammadi, David Morrison, Ognjen Arandjelović, Sheeba Syed, Prakash Konanahalli, Sarah Bell, Gareth Bryson, David J. Harrison e David Harris-Birtill. "Detection of malignancy in whole slide images of endometrial cancer biopsies using artificial intelligence". PLOS ONE 18, n.º 3 (8 de março de 2023): e0282577. http://dx.doi.org/10.1371/journal.pone.0282577.
Texto completo da fonteGovind, Darshana, Brendon Lutnick, John E. Tomaszewski e Pinaki Sarder. "Automated erythrocyte detection and classification from whole slide images". Journal of Medical Imaging 5, n.º 02 (10 de abril de 2018): 1. http://dx.doi.org/10.1117/1.jmi.5.2.027501.
Texto completo da fonteNeto, Pedro C., Sara P. Oliveira, Diana Montezuma, João Fraga, Ana Monteiro, Liliana Ribeiro, Sofia Gonçalves, Isabel M. Pinto e Jaime S. Cardoso. "iMIL4PATH: A Semi-Supervised Interpretable Approach for Colorectal Whole-Slide Images". Cancers 14, n.º 10 (18 de maio de 2022): 2489. http://dx.doi.org/10.3390/cancers14102489.
Texto completo da fonteFranklin, Daniel L., Tara Pattilachan e Anthony Magliocco. "Abstract 5048: Imaging based EGFR mutation subtype classification using EfficientNet". Cancer Research 82, n.º 12_Supplement (15 de junho de 2022): 5048. http://dx.doi.org/10.1158/1538-7445.am2022-5048.
Texto completo da fonteAhmed, Shakil, Asadullah Shaikh, Hani Alshahrani, Abdullah Alghamdi, Mesfer Alrizq, Junaid Baber e Maheen Bakhtyar. "Transfer Learning Approach for Classification of Histopathology Whole Slide Images". Sensors 21, n.º 16 (9 de agosto de 2021): 5361. http://dx.doi.org/10.3390/s21165361.
Texto completo da fonteFu, Zhibing, Qingkui Chen, Mingming Wang e Chen Huang. "Whole slide images classification model based on self-learning sampling". Biomedical Signal Processing and Control 90 (abril de 2024): 105826. http://dx.doi.org/10.1016/j.bspc.2023.105826.
Texto completo da fonteFridman, M. V., A. A. Kosareva, E. V. Snezhko, P. V. Kamlach e V. A. Kovalev. "Papillary thyroid carcinoma whole-slide images as a basis for deep learning". Informatics 20, n.º 2 (29 de junho de 2023): 28–38. http://dx.doi.org/10.37661/1816-0301-2023-20-2-28-38.
Texto completo da fonteJansen, Philipp, Adelaida Creosteanu, Viktor Matyas, Amrei Dilling, Ana Pina, Andrea Saggini, Tobias Schimming et al. "Deep Learning Assisted Diagnosis of Onychomycosis on Whole-Slide Images". Journal of Fungi 8, n.º 9 (28 de agosto de 2022): 912. http://dx.doi.org/10.3390/jof8090912.
Texto completo da fonteLewis, Joshua, Xuebao Zhang, Nithya Shanmugam, Bradley Drumheller, Conrad Shebelut, Geoffrey Smith, Lee Cooper e David Jaye. "Machine Learning-Based Automated Selection of Regions for Analysis on Bone Marrow Aspirate Smears". American Journal of Clinical Pathology 156, Supplement_1 (1 de outubro de 2021): S1—S2. http://dx.doi.org/10.1093/ajcp/aqab189.001.
Texto completo da fonteEl-Hossiny, Ahmed S., Walid Al-Atabany, Osama Hassan, Ahmed M. Soliman e Sherif A. Sami. "Classification of Thyroid Carcinoma in Whole Slide Images Using Cascaded CNN". IEEE Access 9 (2021): 88429–38. http://dx.doi.org/10.1109/access.2021.3076158.
Texto completo da fonteYoshida, Hiroshi, Yoshiko Yamashita, Taichi Shimazu, Eric Cosatto, Tomoharu Kiyuna, Hirokazu Taniguchi, Shigeki Sekine e Atsushi Ochiai. "Automated histological classification of whole slide images of colorectal biopsy specimens". Oncotarget 8, n.º 53 (12 de outubro de 2017): 90719–29. http://dx.doi.org/10.18632/oncotarget.21819.
Texto completo da fonteXu, Hongming, Sunho Park e Tae Hyun Hwang. "Computerized Classification of Prostate Cancer Gleason Scores from Whole Slide Images". IEEE/ACM Transactions on Computational Biology and Bioinformatics 17, n.º 6 (1 de novembro de 2020): 1871–82. http://dx.doi.org/10.1109/tcbb.2019.2941195.
Texto completo da fonteHassanpour, Saeed, Bruno Korbar, AndreaM Olofson, AllenP Miraflor, CatherineM Nicka, MatthewA Suriawinata, Lorenzo Torresani e AriefA Suriawinata. "Deep learning for classification of colorectal polyps on whole-slide images". Journal of Pathology Informatics 8, n.º 1 (2017): 30. http://dx.doi.org/10.4103/jpi.jpi_34_17.
Texto completo da fonteSoldatov, Sergey A., Danil M. Pashkov, Sergey A. Guda, Nikolay S. Karnaukhov, Alexander A. Guda e Alexander V. Soldatov. "Deep Learning Classification of Colorectal Lesions Based on Whole Slide Images". Algorithms 15, n.º 11 (27 de outubro de 2022): 398. http://dx.doi.org/10.3390/a15110398.
Texto completo da fonteYoshida, Hiroshi, Taichi Shimazu, Tomoharu Kiyuna, Atsushi Marugame, Yoshiko Yamashita, Eric Cosatto, Hirokazu Taniguchi, Shigeki Sekine e Atsushi Ochiai. "Automated histological classification of whole-slide images of gastric biopsy specimens". Gastric Cancer 21, n.º 2 (2 de junho de 2017): 249–57. http://dx.doi.org/10.1007/s10120-017-0731-8.
Texto completo da fonteTourniaire, Paul, Marius Ilie, Paul Hofman, Nicholas Ayache e Hervé Delingette. "Abstract 461: Mixed supervision to improve the classification and localization: Coherence of tumors in histological slides". Cancer Research 82, n.º 12_Supplement (15 de junho de 2022): 461. http://dx.doi.org/10.1158/1538-7445.am2022-461.
Texto completo da fonteMa, Yingfan, Xiaoyuan Luo, Kexue Fu e Manning Wang. "Transformer-Based Video-Structure Multi-Instance Learning for Whole Slide Image Classification". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 13 (24 de março de 2024): 14263–71. http://dx.doi.org/10.1609/aaai.v38i13.29338.
Texto completo da fonteAmgad, Mohamed, Habiba Elfandy, Hagar Hussein, Lamees A. Atteya, Mai A. T. Elsebaie, Lamia S. Abo Elnasr, Rokia A. Sakr et al. "Structured crowdsourcing enables convolutional segmentation of histology images". Bioinformatics 35, n.º 18 (6 de fevereiro de 2019): 3461–67. http://dx.doi.org/10.1093/bioinformatics/btz083.
Texto completo da fonteKallipolitis, Athanasios, Kyriakos Revelos e Ilias Maglogiannis. "Ensembling EfficientNets for the Classification and Interpretation of Histopathology Images". Algorithms 14, n.º 10 (26 de setembro de 2021): 278. http://dx.doi.org/10.3390/a14100278.
Texto completo da fonteMahmood, F., C. J. Robbins, S. Perincheri e R. Torres. "Applying Deep Learning Cancer Subtyping Algorithms Trained on Physical Slides to Multiphoton Imaging of Unembedded Samples". American Journal of Clinical Pathology 158, Supplement_1 (1 de novembro de 2022): S117. http://dx.doi.org/10.1093/ajcp/aqac126.248.
Texto completo da fonteGupta, Pushpanjali, Yenlin Huang, Prasan Kumar Sahoo, Jeng-Fu You, Sum-Fu Chiang, Djeane Debora Onthoni, Yih-Jong Chern et al. "Colon Tissues Classification and Localization in Whole Slide Images Using Deep Learning". Diagnostics 11, n.º 8 (2 de agosto de 2021): 1398. http://dx.doi.org/10.3390/diagnostics11081398.
Texto completo da fonteXu, Hongming, Cheng Lu, Richard Berendt, Naresh Jha e Mrinal Mandal. "Automated analysis and classification of melanocytic tumor on skin whole slide images". Computerized Medical Imaging and Graphics 66 (junho de 2018): 124–34. http://dx.doi.org/10.1016/j.compmedimag.2018.01.008.
Texto completo da fonteTsuneki, Masayuki, e Fahdi Kanavati. "Weakly supervised learning for multi-organ adenocarcinoma classification in whole slide images". PLOS ONE 17, n.º 11 (23 de novembro de 2022): e0275378. http://dx.doi.org/10.1371/journal.pone.0275378.
Texto completo da fonteZhao, Boxuan, Jun Zhang, Deheng Ye, Jian Cao, Xiao Han, Qiang Fu e Wei Yang. "RLogist: Fast Observation Strategy on Whole-Slide Images with Deep Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 3 (26 de junho de 2023): 3570–78. http://dx.doi.org/10.1609/aaai.v37i3.25467.
Texto completo da fonteAftab, Rukhma, Yan Qiang e Zhao Juanjuan. "Contrastive Learning for Whole Slide Image Representation: A Self-Supervised Approach in Digital Pathology". European Journal of Applied Science, Engineering and Technology 2, n.º 2 (1 de março de 2024): 175–85. http://dx.doi.org/10.59324/ejaset.2024.2(2).12.
Texto completo da fonteSong, JaeYen, Soyoung Im, Sung Hak Lee e Hyun-Jong Jang. "Deep Learning-Based Classification of Uterine Cervical and Endometrial Cancer Subtypes from Whole-Slide Histopathology Images". Diagnostics 12, n.º 11 (28 de outubro de 2022): 2623. http://dx.doi.org/10.3390/diagnostics12112623.
Texto completo da fonteZarella, Mark D., Matthew R. Quaschnick;, David E. Breen e Fernando U. Garcia. "Estimation of Fine-Scale Histologic Features at Low Magnification". Archives of Pathology & Laboratory Medicine 142, n.º 11 (18 de junho de 2018): 1394–402. http://dx.doi.org/10.5858/arpa.2017-0380-oa.
Texto completo da fonteTavolara, Thomas E., Metin N. Gurcan e M. Khalid Khan Niazi. "Contrastive Multiple Instance Learning: An Unsupervised Framework for Learning Slide-Level Representations of Whole Slide Histopathology Images without Labels". Cancers 14, n.º 23 (24 de novembro de 2022): 5778. http://dx.doi.org/10.3390/cancers14235778.
Texto completo da fonteFeng, Ming, Kele Xu, Nanhui Wu, Weiquan Huang, Yan Bai, Yin Wang, Changjian Wang e Huaimin Wang. "Trusted multi-scale classification framework for whole slide image". Biomedical Signal Processing and Control 89 (março de 2024): 105790. http://dx.doi.org/10.1016/j.bspc.2023.105790.
Texto completo da fontePirovano, Antoine, Hippolyte Heuberger, Sylvain Berlemont, SaÏd Ladjal e Isabelle Bloch. "Automatic Feature Selection for Improved Interpretability on Whole Slide Imaging". Machine Learning and Knowledge Extraction 3, n.º 1 (22 de fevereiro de 2021): 243–62. http://dx.doi.org/10.3390/make3010012.
Texto completo da fonteWang, Ching-Wei, Sheng-Chuan Huang, Yu-Ching Lee, Yu-Jie Shen, Shwu-Ing Meng e Jeff L. Gaol. "Deep learning for bone marrow cell detection and classification on whole-slide images". Medical Image Analysis 75 (janeiro de 2022): 102270. http://dx.doi.org/10.1016/j.media.2021.102270.
Texto completo da fonteMorkūnas, Mindaugas, Povilas Treigys, Jolita Bernatavičienė, Arvydas Laurinavičius e Gražina Korvel. "Machine Learning Based Classification of Colorectal Cancer Tumour Tissue in Whole-Slide Images". Informatica 29, n.º 1 (1 de janeiro de 2018): 75–90. http://dx.doi.org/10.15388/informatica.2018.158.
Texto completo da fonteCho, Kyung-Ok, Sung Hak Lee e Hyun-Jong Jang. "Feasibility of fully automated classification of whole slide images based on deep learning". Korean Journal of Physiology & Pharmacology 24, n.º 1 (2020): 89. http://dx.doi.org/10.4196/kjpp.2020.24.1.89.
Texto completo da fonteSertel, O., J. Kong, H. Shimada, U. V. Catalyurek, J. H. Saltz e M. N. Gurcan. "Computer-aided prognosis of neuroblastoma on whole-slide images: Classification of stromal development". Pattern Recognition 42, n.º 6 (junho de 2009): 1093–103. http://dx.doi.org/10.1016/j.patcog.2008.08.027.
Texto completo da fonteYingli, Zhao, Ding Weilong, You Qinghua, Zhu Fenglong, Zhu Xiaojie, Zheng Kui e Liu Dandan. "Classification of whole slide images of breast histopathology based on spatial correlation characteristics". Journal of Image and Graphics 28, n.º 4 (2023): 1134–45. http://dx.doi.org/10.11834/jig.211133.
Texto completo da fonteShakarami, Ashkan, Lorenzo Nicolè, Matteo Terreran, Angelo Paolo Dei Tos e Stefano Ghidoni. "TCNN: A Transformer Convolutional Neural Network for artifact classification in whole slide images". Biomedical Signal Processing and Control 84 (julho de 2023): 104812. http://dx.doi.org/10.1016/j.bspc.2023.104812.
Texto completo da fonteFu, Yan, Fanlin Zhou, Xu Shi, Long Wang, Yu Li, Jian Wu e Hong Huang. "Classification of adenoid cystic carcinoma in whole slide images by using deep learning". Biomedical Signal Processing and Control 84 (julho de 2023): 104789. http://dx.doi.org/10.1016/j.bspc.2023.104789.
Texto completo da fonteSun, Shenghuan, Jacob Cleave, Linlin Wang, Fabienne Lucas, Laura Brown, Jacob Spector, Leonardo Boiocchi et al. "Deep Learning for Morphology-Based, Bone Marrow Cell Classification". Blood 142, Supplement 1 (28 de novembro de 2023): 2841. http://dx.doi.org/10.1182/blood-2023-172654.
Texto completo da fonteJayaratne, N., A. Sasikumar, S. Subasinghe, A. Borkowski, S. Mastorides, L. Thomas, E. Mastorides e L. DeLand. "Using Deep Learning for Whole Slide Image Prostate Cancer Diagnosis and Grading in South Florida Veteran Population". American Journal of Clinical Pathology 156, Supplement_1 (1 de outubro de 2021): S141. http://dx.doi.org/10.1093/ajcp/aqab191.301.
Texto completo da fonteHuang, Jin, Liye Mei, Mengping Long, Yiqiang Liu, Wei Sun, Xiaoxiao Li, Hui Shen et al. "BM-Net: CNN-Based MobileNet-V3 and Bilinear Structure for Breast Cancer Detection in Whole Slide Images". Bioengineering 9, n.º 6 (20 de junho de 2022): 261. http://dx.doi.org/10.3390/bioengineering9060261.
Texto completo da fonteSchmitt, Max, Roman Christoph Maron, Achim Hekler, Albrecht Stenzinger, Axel Hauschild, Michael Weichenthal, Markus Tiemann et al. "Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study". Journal of Medical Internet Research 23, n.º 2 (2 de fevereiro de 2021): e23436. http://dx.doi.org/10.2196/23436.
Texto completo da fonteDimitriou, Neofytos, Ognjen Arandjelović e David J. Harrison. "Magnifying Networks for Histopathological Images with Billions of Pixels". Diagnostics 14, n.º 5 (1 de março de 2024): 524. http://dx.doi.org/10.3390/diagnostics14050524.
Texto completo da fonteAhmad Fauzi, Mohammad Faizal, Wan Siti Halimatul Munirah Wan Ahmad, Mohammad Fareed Jamaluddin, Jenny Tung Hiong Lee, See Yee Khor, Lai Meng Looi, Fazly Salleh Abas e Nouar Aldahoul. "Allred Scoring of ER-IHC Stained Whole-Slide Images for Hormone Receptor Status in Breast Carcinoma". Diagnostics 12, n.º 12 (8 de dezembro de 2022): 3093. http://dx.doi.org/10.3390/diagnostics12123093.
Texto completo da fonteChe, Yuxuan, Fei Ren, Xueyuan Zhang, Li Cui, Huanwen Wu e Ze Zhao. "Immunohistochemical HER2 Recognition and Analysis of Breast Cancer Based on Deep Learning". Diagnostics 13, n.º 2 (10 de janeiro de 2023): 263. http://dx.doi.org/10.3390/diagnostics13020263.
Texto completo da fonteBhatt, Anant R., Amit Ganatra e Ketan Kotecha. "Cervical cancer detection in pap smear whole slide images using convNet with transfer learning and progressive resizing". PeerJ Computer Science 7 (18 de fevereiro de 2021): e348. http://dx.doi.org/10.7717/peerj-cs.348.
Texto completo da fonteCho, Joonyoung, Tae-Yeong Kwak, Sun Woo Kim e Hyeyoon Chang. "Abstract 5056: Automated Gleason grading of digitized frozen section prostate tissue slide images". Cancer Research 82, n.º 12_Supplement (15 de junho de 2022): 5056. http://dx.doi.org/10.1158/1538-7445.am2022-5056.
Texto completo da fonteWang, Pin, Pufei Li, Yongming Li, Jin Xu e Mingfeng Jiang. "Classification of histopathological whole slide images based on multiple weighted semi-supervised domain adaptation". Biomedical Signal Processing and Control 73 (março de 2022): 103400. http://dx.doi.org/10.1016/j.bspc.2021.103400.
Texto completo da fonteKanavati, Fahdi, Shin Ichihara, Michael Rambeau, Osamu Iizuka, Koji Arihiro e Masayuki Tsuneki. "Deep Learning Models for Gastric Signet Ring Cell Carcinoma Classification in Whole Slide Images". Technology in Cancer Research & Treatment 20 (1 de janeiro de 2021): 153303382110279. http://dx.doi.org/10.1177/15330338211027901.
Texto completo da fonteHart, StevenN, William Flotte, AndrewP Norgan, KabeerK Shah, ZacharyR Buchan, Taofic Mounajjed e ThomasJ Flotte. "Classification of melanocytic lesions in selected and whole-slide images via convolutional neural networks". Journal of Pathology Informatics 10, n.º 1 (2019): 5. http://dx.doi.org/10.4103/jpi.jpi_32_18.
Texto completo da fonteMukashyaka, Patience, Todd B. Sheridan, Ali Foroughi pour e Jeffrey H. Chuang. "Abstract B039: SAMPLER: Unsupervised representations of whole slide images for tumor phenotype prediction". Cancer Research 84, n.º 3_Supplement_2 (1 de fevereiro de 2024): B039. http://dx.doi.org/10.1158/1538-7445.canevol23-b039.
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