Artigos de revistas sobre o tema "Histopathological tumor segmentation"
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Liu, Yiqing, Qiming He, Hufei Duan, Huijuan Shi, Anjia Han e Yonghong He. "Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images". Sensors 22, n.º 16 (13 de agosto de 2022): 6053. http://dx.doi.org/10.3390/s22166053.
Texto completo da fontevan der Kamp, Ananda, Thomas de Bel, Ludo van Alst, Jikke Rutgers, Marry M. van den Heuvel-Eibrink, Annelies M. C. Mavinkurve-Groothuis, Jeroen van der Laak e Ronald R. de Krijger. "Automated Deep Learning-Based Classification of Wilms Tumor Histopathology". Cancers 15, n.º 9 (8 de maio de 2023): 2656. http://dx.doi.org/10.3390/cancers15092656.
Texto completo da fonteZadeh Shirazi, Amin, Eric Fornaciari, Mark D. McDonnell, Mahdi Yaghoobi, Yesenia Cevallos, Luis Tello-Oquendo, Deysi Inca e Guillermo A. Gomez. "The Application of Deep Convolutional Neural Networks to Brain Cancer Images: A Survey". Journal of Personalized Medicine 10, n.º 4 (12 de novembro de 2020): 224. http://dx.doi.org/10.3390/jpm10040224.
Texto completo da fontePark, Youngjae, Jinhee Park e Gil-Jin Jang. "Efficient Perineural Invasion Detection of Histopathological Images Using U-Net". Electronics 11, n.º 10 (22 de maio de 2022): 1649. http://dx.doi.org/10.3390/electronics11101649.
Texto completo da fonteAltini, Nicola, Emilia Puro, Maria Giovanna Taccogna, Francescomaria Marino, Simona De Summa, Concetta Saponaro, Eliseo Mattioli, Francesco Alfredo Zito e Vitoantonio Bevilacqua. "Tumor Cellularity Assessment of Breast Histopathological Slides via Instance Segmentation and Pathomic Features Explainability". Bioengineering 10, n.º 4 (23 de março de 2023): 396. http://dx.doi.org/10.3390/bioengineering10040396.
Texto completo da fonteAlthubaity, DaifAllah D., Faisal Fahad Alotaibi, Abdalla Mohamed Ahmed Osman, Mugahed Ali Al-khadher, Yahya Hussein Ahmed Abdalla, Sadeq Abdo Alwesabi, Elsadig Eltaher Hamed Abdulrahman e Maram Abdulkhalek Alhemairy. "Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis". Journal of Personalized Medicine 13, n.º 3 (23 de fevereiro de 2023): 388. http://dx.doi.org/10.3390/jpm13030388.
Texto completo da fonteMusulin, Jelena, Daniel Štifanić, Ana Zulijani, Tomislav Ćabov, Andrea Dekanić e Zlatan Car. "An Enhanced Histopathology Analysis: An AI-Based System for Multiclass Grading of Oral Squamous Cell Carcinoma and Segmenting of Epithelial and Stromal Tissue". Cancers 13, n.º 8 (8 de abril de 2021): 1784. http://dx.doi.org/10.3390/cancers13081784.
Texto completo da fonteNicolás-Sáenz, Laura, Sara Guerrero-Aspizua, Javier Pascau e Arrate Muñoz-Barrutia. "Nonlinear Image Registration and Pixel Classification Pipeline for the Study of Tumor Heterogeneity Maps". Entropy 22, n.º 9 (28 de agosto de 2020): 946. http://dx.doi.org/10.3390/e22090946.
Texto completo da fonteHuang, Zhi, Anil V. Parwani, Kun Huang e Zaibo Li. "Abstract 5436: Developing artificial intelligence algorithms to predict response to neoadjuvant chemotherapy in HER2-positive breast cancer". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 5436. http://dx.doi.org/10.1158/1538-7445.am2023-5436.
Texto completo da fonteFagundes, Theara C., Arnoldo Mafra, Rodrigo G. Silva, Ana C. G. Castro, Luciana C. Silva, Priscilla T. Aguiar, Josiane A. Silva, Eduardo P. Junior, Alexei M. Machado e Marcelo Mamede. "Individualized threshold for tumor segmentation in 18F-FDG PET/CT imaging: The key for response evaluation of neoadjuvant chemoradiation therapy in patients with rectal cancer?" Revista da Associação Médica Brasileira 64, n.º 2 (fevereiro de 2018): 119–26. http://dx.doi.org/10.1590/1806-9282.64.02.119.
Texto completo da fonteAnghel, Cristian, Mugur Cristian Grasu, Denisa Andreea Anghel, Gina-Ionela Rusu-Munteanu, Radu Lucian Dumitru e Ioana Gabriela Lupescu. "Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images". Diagnostics 14, n.º 4 (16 de fevereiro de 2024): 438. http://dx.doi.org/10.3390/diagnostics14040438.
Texto completo da fonteCancian, Pierandrea, Nina Cortese, Matteo Donadon, Marco Di Maio, Cristiana Soldani, Federica Marchesi, Victor Savevski et al. "Development of a Deep-Learning Pipeline to Recognize and Characterize Macrophages in Colo-Rectal Liver Metastasis". Cancers 13, n.º 13 (1 de julho de 2021): 3313. http://dx.doi.org/10.3390/cancers13133313.
Texto completo da fonteMahmoudi, Keon, Daniel H. Kim, Elham Tavakkol, Shingo Kihira, Adam Bauer, Nadejda Tsankova, Fahad Khan, Adilia Hormigo, Vivek Yedavalli e Kambiz Nael. "Multiparametric Radiogenomic Model to Predict Survival in Patients with Glioblastoma". Cancers 16, n.º 3 (30 de janeiro de 2024): 589. http://dx.doi.org/10.3390/cancers16030589.
Texto completo da fonteZováthi, Bendegúz H., Réka Mohácsi, Attila Marcell Szász e György Cserey. "Breast Tumor Tissue Segmentation with Area-Based Annotation Using Convolutional Neural Network". Diagnostics 12, n.º 9 (6 de setembro de 2022): 2161. http://dx.doi.org/10.3390/diagnostics12092161.
Texto completo da fonteZhang, Xiaoxuan, Xiongfeng Zhu, Kai Tang, Yinghua Zhao, Zixiao Lu e Qianjin Feng. "DDTNet: A dense dual-task network for tumor-infiltrating lymphocyte detection and segmentation in histopathological images of breast cancer". Medical Image Analysis 78 (maio de 2022): 102415. http://dx.doi.org/10.1016/j.media.2022.102415.
Texto completo da fonteHosainey, Sayied Abdol Mohieb, David Bouget, Ingerid Reinertsen, Lisa Millgård Sagberg, Sverre Helge Torp, Asgeir Store Jakola e Ole Solheim. "Are there predilection sites for intracranial meningioma? A population-based atlas". Neurosurgical Review 45, n.º 2 (21 de outubro de 2021): 1543–52. http://dx.doi.org/10.1007/s10143-021-01652-9.
Texto completo da fonteBundschuh, Lena, Vesna Prokic, Matthias Guckenberger, Stephanie Tanadini-Lang, Markus Essler e Ralph A. Bundschuh. "A Novel Radiomics-Based Tumor Volume Segmentation Algorithm for Lung Tumors in FDG-PET/CT after 3D Motion Correction—A Technical Feasibility and Stability Study". Diagnostics 12, n.º 3 (23 de fevereiro de 2022): 576. http://dx.doi.org/10.3390/diagnostics12030576.
Texto completo da fonteZhou, Wentong, Ziheng Deng, Yong Liu, Hui Shen, Hongwen Deng e Hongmei Xiao. "Global Research Trends of Artificial Intelligence on Histopathological Images: A 20-Year Bibliometric Analysis". International Journal of Environmental Research and Public Health 19, n.º 18 (15 de setembro de 2022): 11597. http://dx.doi.org/10.3390/ijerph191811597.
Texto completo da fonteJaber, Mustafa I., Christopher W. Szeto, Bing Song, Liudmila Beziaeva, Stephen C. Benz, Patrick Soon-Shiong e Shahrooz Rabizadeh. "Pathology image-based lung cancer subtyping using deeplearning features and cell-density maps". Electronic Imaging 2020, n.º 10 (26 de janeiro de 2020): 64–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.10.ipas-064.
Texto completo da fonteKurczyk, Agata, Marta Gawin, Piotr Paul, Ewa Chmielik, Tomasz Rutkowski, Monika Pietrowska e Piotr Widłak. "Prognostic Value of Molecular Intratumor Heterogeneity in Primary Oral Cancer and Its Lymph Node Metastases Assessed by Mass Spectrometry Imaging". Molecules 27, n.º 17 (25 de agosto de 2022): 5458. http://dx.doi.org/10.3390/molecules27175458.
Texto completo da fonteEminaga, Okyaz, Mahmoud Abbas, Axel Semjonow, James D. Brooks e Daniel Rubin. "Determination of biologic and prognostic feature scores from whole slide histology images using deep learning." Journal of Clinical Oncology 38, n.º 15_suppl (20 de maio de 2020): e17527-e17527. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e17527.
Texto completo da fonteJung, Jiyoon, Eunsu Kim, Hyeseong Lee, Sung Hak Lee e Sangjeong Ahn. "Automated Hybrid Model for Detecting Perineural Invasion in the Histology of Colorectal Cancer". Applied Sciences 12, n.º 18 (13 de setembro de 2022): 9159. http://dx.doi.org/10.3390/app12189159.
Texto completo da fonteLiu, Yan, Fadila Zerka, Sylvain Bodard, Mehdi Felfli, Charles Voyton, Alexandre Thinnes, Sebastien Jacques e Antoine Iannessi. "CT based radiomics signature for phenotyping histopathological subtype in patients with non-small cell lung cancer." Journal of Clinical Oncology 41, n.º 16_suppl (1 de junho de 2023): e20599-e20599. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.e20599.
Texto completo da fonteTalwar, Vineet, Kundan Singh Chufal e Srujana Joga. "Artificial Intelligence: A New Tool in Oncologist's Armamentarium". Indian Journal of Medical and Paediatric Oncology 42, n.º 06 (dezembro de 2021): 511–17. http://dx.doi.org/10.1055/s-0041-1735577.
Texto completo da fonteKhalil, Muhammad-Adil, Yu-Ching Lee, Huang-Chun Lien, Yung-Ming Jeng e Ching-Wei Wang. "Fast Segmentation of Metastatic Foci in H&E Whole-Slide Images for Breast Cancer Diagnosis". Diagnostics 12, n.º 4 (14 de abril de 2022): 990. http://dx.doi.org/10.3390/diagnostics12040990.
Texto completo da fonteGrewal, Mahip, Taha Ahmed e Ammar Asrar Javed. "Current state of radiomics in hepatobiliary and pancreatic malignancies". Artificial Intelligence Surgery 3, n.º 4 (28 de novembro de 2023): 217–32. http://dx.doi.org/10.20517/ais.2023.28.
Texto completo da fonteRigamonti, Alessandra, Marika Viatore, Rebecca Polidori, Marco Erreni, Maria Fumagalli, Daoud Rahal, Massimo Locati, Alberto Mantovani e Federica Marchesi. "Abstract 5783: Integration of AI-powered digital pathology and imaging mass cytometry to identify relevant features of the tumor microenvironment". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 5783. http://dx.doi.org/10.1158/1538-7445.am2023-5783.
Texto completo da fonteWu, Wei, Lauren Cech, Victor Olivas, Aubhishek Zaman, Daniel Lucas Kerr e Trever G. Bivona. "Deep learning-based characterization of the drug tolerant persister cell state in lung cancer." JCO Global Oncology 9, Supplement_1 (agosto de 2023): 141. http://dx.doi.org/10.1200/go.2023.9.supplement_1.141.
Texto completo da fonteDi Dio, Michele, Simona Barbuto, Claudio Bisegna, Andrea Bellin, Mario Boccia, Daniele Amparore, Paolo Verri et al. "Artificial Intelligence-Based Hyper Accuracy Three-Dimensional (HA3D®) Models in Surgical Planning of Challenging Robotic Nephron-Sparing Surgery: A Case Report and Snapshot of the State-of-the-Art with Possible Future Implications". Diagnostics 13, n.º 14 (10 de julho de 2023): 2320. http://dx.doi.org/10.3390/diagnostics13142320.
Texto completo da fontePasello, Giulia, Alessandra Ferro, Elena Scagliori, Gisella Gennaro, Matilde Costa, Matteo Sepulcri, Marco Schiavon et al. "Exploratory radiomic analysis of stage III non-small cell lung cancer CT images: Correlation with clinical-pathological characteristics." Journal of Clinical Oncology 40, n.º 16_suppl (1 de junho de 2022): e20574-e20574. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e20574.
Texto completo da fontePasello, Giulia, Alessandra Ferro, Elena Scagliori, Gisella Gennaro, Matilde Costa, Matteo Sepulcri, Marco Schiavon et al. "Exploratory radiomic analysis of stage III non-small cell lung cancer CT images: Correlation with clinical-pathological characteristics." Journal of Clinical Oncology 40, n.º 16_suppl (1 de junho de 2022): e20574-e20574. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e20574.
Texto completo da fonteCanola, Julio Carlos, e Fabrício Singaretti de Oliveira. "Three-dimensional magnetic resonance reconstruction images before and after surgical therapy of spontaneous canine brain tumors". Ciência Rural 37, n.º 4 (agosto de 2007): 1174–77. http://dx.doi.org/10.1590/s0103-84782007000400044.
Texto completo da fonteDionisio, Fernando Carrasco Ferreira, Larissa Santos Oliveira, Mateus de Andrade Hernandes, Edgard Eduard Engel, Paulo Mazzoncini de Azevedo-Marques e Marcello Henrique Nogueira-Barbosa. "Manual versus semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging: evaluation of similarity and comparison of segmentation times". Radiologia Brasileira 54, n.º 3 (junho de 2021): 155–64. http://dx.doi.org/10.1590/0100-3984.2020.0028.
Texto completo da fonteAlvarsson, Alexandra, Carl Storey, Brandy Olin Pope, Caleb Stoltzfus, Robert Vierkant, Jessica Tufariello, Aaron Bungum et al. "Abstract 6624: 3D assessment of the lung cancer microenvironment using multi-resolution open-top light-sheet microscopy". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 6624. http://dx.doi.org/10.1158/1538-7445.am2023-6624.
Texto completo da fonteHempel, Johann-Martin, Cornelia Brendle, Sasan Darius Adib, Felix Behling, Ghazaleh Tabatabai, Salvador Castaneda Vega, Jens Schittenhelm, Ulrike Ernemann e Uwe Klose. "Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging". Journal of Clinical Medicine 10, n.º 11 (26 de maio de 2021): 2325. http://dx.doi.org/10.3390/jcm10112325.
Texto completo da fontede Matos, Jonathan, Steve Ataky, Alceu de Souza Britto, Luiz Soares de Oliveira e Alessandro Lameiras Koerich. "Machine Learning Methods for Histopathological Image Analysis: A Review". Electronics 10, n.º 5 (27 de fevereiro de 2021): 562. http://dx.doi.org/10.3390/electronics10050562.
Texto completo da fonteWarman, Pranav, Syed M. Adil, Andreas Seas, Daniel Sexton, Evan Calabrese, Nandan P. Lad, Brad Kolls et al. "381 Glioma Three-Dimensional Shape Predicts Underlying Genetic Mutations". Neurosurgery 70, Supplement_1 (abril de 2024): 115. http://dx.doi.org/10.1227/neu.0000000000002809_381.
Texto completo da fonteHulahan, Taylor S., Elizabeth N. Wallace, Siri H. Strand, Graham A. Colditz, E. Shelley Hwang, Robert West, Laura Spruill, Jeffrey Marks, Richard R. Drake e Peggi M. Angel. "Abstract P2-21-03: Unique Collagen Peptide Signatures between Ductal Carcinoma in Situ and Invasive Breast Cancer by Mass Spectrometry Tissue Imaging". Cancer Research 83, n.º 5_Supplement (1 de março de 2023): P2–21–03—P2–21–03. http://dx.doi.org/10.1158/1538-7445.sabcs22-p2-21-03.
Texto completo da fonteHulahan, Taylor S., Elizabeth N. Wallace, Siri H. Strand, Robert Michael Angelo, Graham Colditz, Eun-Sil Shelley Hwang, Robert West et al. "Abstract B019: Discrete regulation of the collagen proteome among pathological features in DCIS and invasive breast cancer by mass spectrometry tissue imaging". Cancer Prevention Research 15, n.º 12_Supplement_1 (1 de dezembro de 2022): B019. http://dx.doi.org/10.1158/1940-6215.dcis22-b019.
Texto completo da fonteXu, Rui, Zhizhen Wang, Zhenbing Liu, Chu Han, Lixu Yan, Huan Lin, Zeyan Xu et al. "Histopathological Tissue Segmentation of Lung Cancer with Bilinear CNN and Soft Attention". BioMed Research International 2022 (7 de julho de 2022): 1–10. http://dx.doi.org/10.1155/2022/7966553.
Texto completo da fonteZadeh Shirazi, Amin, Mark D. McDonnell, Eric Fornaciari, Narjes Sadat Bagherian, Kaitlin G. Scheer, Michael S. Samuel, Mahdi Yaghoobi et al. "A deep convolutional neural network for segmentation of whole-slide pathology images identifies novel tumour cell-perivascular niche interactions that are associated with poor survival in glioblastoma". British Journal of Cancer 125, n.º 3 (29 de abril de 2021): 337–50. http://dx.doi.org/10.1038/s41416-021-01394-x.
Texto completo da fonteAlGhamdi, Rayed. "Mitotic Nuclei Segmentation and Classification Using Chaotic Butterfly Optimization Algorithm with Deep Learning on Histopathology Images". Biomimetics 8, n.º 6 (5 de outubro de 2023): 474. http://dx.doi.org/10.3390/biomimetics8060474.
Texto completo da fonteJakola, Asgeir S., David Bouget, Ingerid Reinertsen, Anne J. Skjulsvik, Lisa Millgård Sagberg, Hans Kristian Bø, Sasha Gulati, Kristin Sjåvik e Ole Solheim. "Spatial distribution of malignant transformation in patients with low-grade glioma". Journal of Neuro-Oncology 146, n.º 2 (janeiro de 2020): 373–80. http://dx.doi.org/10.1007/s11060-020-03391-1.
Texto completo da fonteWang, Edmond. "Glioblastoma Synthesis and Segmentation with 3D Multi-Modal MRI: A Study using Generative Adversarial Networks". International Journal on Computational Science & Applications 11, n.º 6 (31 de dezembro de 2021): 1–14. http://dx.doi.org/10.5121/ijcsa.2021.11601.
Texto completo da fonteVerghese, Gregory, Mengyuan Li, Amit Lohan, Nikhil Cherian, Swapnil Rane, Fangfang Liu, Aekta Shah et al. "Abstract 6233: A deep learning pipeline to capture the prognostic immune responses in lymph nodes of breast cancer patients". Cancer Research 82, n.º 12_Supplement (15 de junho de 2022): 6233. http://dx.doi.org/10.1158/1538-7445.am2022-6233.
Texto completo da fonteHeiland, Dieter, Robin Ohle, Simon Behringer, Juergen Beck e Oliver Schnell. "NIMG-63. LONGITUDINAL ANALYSIS OF OLIGODENDROGLIOMA GROWTH PATTERN REVEALED SPATIAL HETEROGENEITY AND DIVERSE TREATMENT RESPONSE". Neuro-Oncology 21, Supplement_6 (novembro de 2019): vi175. http://dx.doi.org/10.1093/neuonc/noz175.732.
Texto completo da fonteWach, Johannes, Claudia Goetz, Kasra Shareghi, Torben Scholz, Volker Heßelmann, Ann-Kathrin Mager, Joachim Gottschalk, Hartmut Vatter e Paul Kremer. "Dual-Use Intraoperative MRI in Glioblastoma Surgery: Results of Resection, Histopathologic Assessment, and Surgical Site Infections". Journal of Neurological Surgery Part A: Central European Neurosurgery 80, n.º 06 (4 de julho de 2019): 413–22. http://dx.doi.org/10.1055/s-0039-1692975.
Texto completo da fonteWalkowski, Slawomir, e Janusz Szymas. "Histopathologic Patterns of Nervous System Tumors Based on Computer Vision Methods and Whole Slide Imaging (WSI)". Analytical Cellular Pathology 35, n.º 2 (2012): 117–22. http://dx.doi.org/10.1155/2012/483525.
Texto completo da fonteKanta Maitra, Indra, e Samir Kumar Bandyopadhyay. "CAD Based Method for Detection of Breast Cancer". Oriental journal of computer science and technology 11, n.º 3 (10 de setembro de 2018): 154–68. http://dx.doi.org/10.13005/ojcst11.03.04.
Texto completo da fonteGui, Chloe, Jonathan C. Lau e Joseph F. Megyesi. "30 Perceived versus quantified growth trajectory of serially-imaged low-grade gliomas". Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 45, S3 (junho de 2018): S6. http://dx.doi.org/10.1017/cjn.2018.274.
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