Artykuły w czasopismach na temat „Histopathological tumor segmentation”
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Liu, Yiqing, Qiming He, Hufei Duan, Huijuan Shi, Anjia Han i Yonghong He. "Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images". Sensors 22, nr 16 (13.08.2022): 6053. http://dx.doi.org/10.3390/s22166053.
Pełny tekst źródłavan 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 i Ronald R. de Krijger. "Automated Deep Learning-Based Classification of Wilms Tumor Histopathology". Cancers 15, nr 9 (8.05.2023): 2656. http://dx.doi.org/10.3390/cancers15092656.
Pełny tekst źródłaZadeh Shirazi, Amin, Eric Fornaciari, Mark D. McDonnell, Mahdi Yaghoobi, Yesenia Cevallos, Luis Tello-Oquendo, Deysi Inca i Guillermo A. Gomez. "The Application of Deep Convolutional Neural Networks to Brain Cancer Images: A Survey". Journal of Personalized Medicine 10, nr 4 (12.11.2020): 224. http://dx.doi.org/10.3390/jpm10040224.
Pełny tekst źródłaPark, Youngjae, Jinhee Park i Gil-Jin Jang. "Efficient Perineural Invasion Detection of Histopathological Images Using U-Net". Electronics 11, nr 10 (22.05.2022): 1649. http://dx.doi.org/10.3390/electronics11101649.
Pełny tekst źródłaAltini, Nicola, Emilia Puro, Maria Giovanna Taccogna, Francescomaria Marino, Simona De Summa, Concetta Saponaro, Eliseo Mattioli, Francesco Alfredo Zito i Vitoantonio Bevilacqua. "Tumor Cellularity Assessment of Breast Histopathological Slides via Instance Segmentation and Pathomic Features Explainability". Bioengineering 10, nr 4 (23.03.2023): 396. http://dx.doi.org/10.3390/bioengineering10040396.
Pełny tekst źródłaAlthubaity, DaifAllah D., Faisal Fahad Alotaibi, Abdalla Mohamed Ahmed Osman, Mugahed Ali Al-khadher, Yahya Hussein Ahmed Abdalla, Sadeq Abdo Alwesabi, Elsadig Eltaher Hamed Abdulrahman i 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, nr 3 (23.02.2023): 388. http://dx.doi.org/10.3390/jpm13030388.
Pełny tekst źródłaMusulin, Jelena, Daniel Štifanić, Ana Zulijani, Tomislav Ćabov, Andrea Dekanić i 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, nr 8 (8.04.2021): 1784. http://dx.doi.org/10.3390/cancers13081784.
Pełny tekst źródłaNicolás-Sáenz, Laura, Sara Guerrero-Aspizua, Javier Pascau i Arrate Muñoz-Barrutia. "Nonlinear Image Registration and Pixel Classification Pipeline for the Study of Tumor Heterogeneity Maps". Entropy 22, nr 9 (28.08.2020): 946. http://dx.doi.org/10.3390/e22090946.
Pełny tekst źródłaHuang, Zhi, Anil V. Parwani, Kun Huang i Zaibo Li. "Abstract 5436: Developing artificial intelligence algorithms to predict response to neoadjuvant chemotherapy in HER2-positive breast cancer". Cancer Research 83, nr 7_Supplement (4.04.2023): 5436. http://dx.doi.org/10.1158/1538-7445.am2023-5436.
Pełny tekst źródłaFagundes, 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 i 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, nr 2 (luty 2018): 119–26. http://dx.doi.org/10.1590/1806-9282.64.02.119.
Pełny tekst źródłaAnghel, Cristian, Mugur Cristian Grasu, Denisa Andreea Anghel, Gina-Ionela Rusu-Munteanu, Radu Lucian Dumitru i Ioana Gabriela Lupescu. "Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images". Diagnostics 14, nr 4 (16.02.2024): 438. http://dx.doi.org/10.3390/diagnostics14040438.
Pełny tekst źródłaCancian, Pierandrea, Nina Cortese, Matteo Donadon, Marco Di Maio, Cristiana Soldani, Federica Marchesi, Victor Savevski i in. "Development of a Deep-Learning Pipeline to Recognize and Characterize Macrophages in Colo-Rectal Liver Metastasis". Cancers 13, nr 13 (1.07.2021): 3313. http://dx.doi.org/10.3390/cancers13133313.
Pełny tekst źródłaMahmoudi, Keon, Daniel H. Kim, Elham Tavakkol, Shingo Kihira, Adam Bauer, Nadejda Tsankova, Fahad Khan, Adilia Hormigo, Vivek Yedavalli i Kambiz Nael. "Multiparametric Radiogenomic Model to Predict Survival in Patients with Glioblastoma". Cancers 16, nr 3 (30.01.2024): 589. http://dx.doi.org/10.3390/cancers16030589.
Pełny tekst źródłaZováthi, Bendegúz H., Réka Mohácsi, Attila Marcell Szász i György Cserey. "Breast Tumor Tissue Segmentation with Area-Based Annotation Using Convolutional Neural Network". Diagnostics 12, nr 9 (6.09.2022): 2161. http://dx.doi.org/10.3390/diagnostics12092161.
Pełny tekst źródłaZhang, Xiaoxuan, Xiongfeng Zhu, Kai Tang, Yinghua Zhao, Zixiao Lu i 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 (maj 2022): 102415. http://dx.doi.org/10.1016/j.media.2022.102415.
Pełny tekst źródłaHosainey, Sayied Abdol Mohieb, David Bouget, Ingerid Reinertsen, Lisa Millgård Sagberg, Sverre Helge Torp, Asgeir Store Jakola i Ole Solheim. "Are there predilection sites for intracranial meningioma? A population-based atlas". Neurosurgical Review 45, nr 2 (21.10.2021): 1543–52. http://dx.doi.org/10.1007/s10143-021-01652-9.
Pełny tekst źródłaBundschuh, Lena, Vesna Prokic, Matthias Guckenberger, Stephanie Tanadini-Lang, Markus Essler i 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, nr 3 (23.02.2022): 576. http://dx.doi.org/10.3390/diagnostics12030576.
Pełny tekst źródłaZhou, Wentong, Ziheng Deng, Yong Liu, Hui Shen, Hongwen Deng i 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, nr 18 (15.09.2022): 11597. http://dx.doi.org/10.3390/ijerph191811597.
Pełny tekst źródłaJaber, Mustafa I., Christopher W. Szeto, Bing Song, Liudmila Beziaeva, Stephen C. Benz, Patrick Soon-Shiong i Shahrooz Rabizadeh. "Pathology image-based lung cancer subtyping using deeplearning features and cell-density maps". Electronic Imaging 2020, nr 10 (26.01.2020): 64–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.10.ipas-064.
Pełny tekst źródłaKurczyk, Agata, Marta Gawin, Piotr Paul, Ewa Chmielik, Tomasz Rutkowski, Monika Pietrowska i Piotr Widłak. "Prognostic Value of Molecular Intratumor Heterogeneity in Primary Oral Cancer and Its Lymph Node Metastases Assessed by Mass Spectrometry Imaging". Molecules 27, nr 17 (25.08.2022): 5458. http://dx.doi.org/10.3390/molecules27175458.
Pełny tekst źródłaEminaga, Okyaz, Mahmoud Abbas, Axel Semjonow, James D. Brooks i Daniel Rubin. "Determination of biologic and prognostic feature scores from whole slide histology images using deep learning." Journal of Clinical Oncology 38, nr 15_suppl (20.05.2020): e17527-e17527. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e17527.
Pełny tekst źródłaJung, Jiyoon, Eunsu Kim, Hyeseong Lee, Sung Hak Lee i Sangjeong Ahn. "Automated Hybrid Model for Detecting Perineural Invasion in the Histology of Colorectal Cancer". Applied Sciences 12, nr 18 (13.09.2022): 9159. http://dx.doi.org/10.3390/app12189159.
Pełny tekst źródłaLiu, Yan, Fadila Zerka, Sylvain Bodard, Mehdi Felfli, Charles Voyton, Alexandre Thinnes, Sebastien Jacques i Antoine Iannessi. "CT based radiomics signature for phenotyping histopathological subtype in patients with non-small cell lung cancer." Journal of Clinical Oncology 41, nr 16_suppl (1.06.2023): e20599-e20599. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.e20599.
Pełny tekst źródłaTalwar, Vineet, Kundan Singh Chufal i Srujana Joga. "Artificial Intelligence: A New Tool in Oncologist's Armamentarium". Indian Journal of Medical and Paediatric Oncology 42, nr 06 (grudzień 2021): 511–17. http://dx.doi.org/10.1055/s-0041-1735577.
Pełny tekst źródłaKhalil, Muhammad-Adil, Yu-Ching Lee, Huang-Chun Lien, Yung-Ming Jeng i Ching-Wei Wang. "Fast Segmentation of Metastatic Foci in H&E Whole-Slide Images for Breast Cancer Diagnosis". Diagnostics 12, nr 4 (14.04.2022): 990. http://dx.doi.org/10.3390/diagnostics12040990.
Pełny tekst źródłaGrewal, Mahip, Taha Ahmed i Ammar Asrar Javed. "Current state of radiomics in hepatobiliary and pancreatic malignancies". Artificial Intelligence Surgery 3, nr 4 (28.11.2023): 217–32. http://dx.doi.org/10.20517/ais.2023.28.
Pełny tekst źródłaRigamonti, Alessandra, Marika Viatore, Rebecca Polidori, Marco Erreni, Maria Fumagalli, Daoud Rahal, Massimo Locati, Alberto Mantovani i 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, nr 7_Supplement (4.04.2023): 5783. http://dx.doi.org/10.1158/1538-7445.am2023-5783.
Pełny tekst źródłaWu, Wei, Lauren Cech, Victor Olivas, Aubhishek Zaman, Daniel Lucas Kerr i Trever G. Bivona. "Deep learning-based characterization of the drug tolerant persister cell state in lung cancer." JCO Global Oncology 9, Supplement_1 (sierpień 2023): 141. http://dx.doi.org/10.1200/go.2023.9.supplement_1.141.
Pełny tekst źródłaDi Dio, Michele, Simona Barbuto, Claudio Bisegna, Andrea Bellin, Mario Boccia, Daniele Amparore, Paolo Verri i in. "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, nr 14 (10.07.2023): 2320. http://dx.doi.org/10.3390/diagnostics13142320.
Pełny tekst źródłaPasello, Giulia, Alessandra Ferro, Elena Scagliori, Gisella Gennaro, Matilde Costa, Matteo Sepulcri, Marco Schiavon i in. "Exploratory radiomic analysis of stage III non-small cell lung cancer CT images: Correlation with clinical-pathological characteristics." Journal of Clinical Oncology 40, nr 16_suppl (1.06.2022): e20574-e20574. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e20574.
Pełny tekst źródłaPasello, Giulia, Alessandra Ferro, Elena Scagliori, Gisella Gennaro, Matilde Costa, Matteo Sepulcri, Marco Schiavon i in. "Exploratory radiomic analysis of stage III non-small cell lung cancer CT images: Correlation with clinical-pathological characteristics." Journal of Clinical Oncology 40, nr 16_suppl (1.06.2022): e20574-e20574. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.e20574.
Pełny tekst źródłaCanola, Julio Carlos, i Fabrício Singaretti de Oliveira. "Three-dimensional magnetic resonance reconstruction images before and after surgical therapy of spontaneous canine brain tumors". Ciência Rural 37, nr 4 (sierpień 2007): 1174–77. http://dx.doi.org/10.1590/s0103-84782007000400044.
Pełny tekst źródłaDionisio, Fernando Carrasco Ferreira, Larissa Santos Oliveira, Mateus de Andrade Hernandes, Edgard Eduard Engel, Paulo Mazzoncini de Azevedo-Marques i 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, nr 3 (czerwiec 2021): 155–64. http://dx.doi.org/10.1590/0100-3984.2020.0028.
Pełny tekst źródłaAlvarsson, Alexandra, Carl Storey, Brandy Olin Pope, Caleb Stoltzfus, Robert Vierkant, Jessica Tufariello, Aaron Bungum i in. "Abstract 6624: 3D assessment of the lung cancer microenvironment using multi-resolution open-top light-sheet microscopy". Cancer Research 83, nr 7_Supplement (4.04.2023): 6624. http://dx.doi.org/10.1158/1538-7445.am2023-6624.
Pełny tekst źródłaHempel, Johann-Martin, Cornelia Brendle, Sasan Darius Adib, Felix Behling, Ghazaleh Tabatabai, Salvador Castaneda Vega, Jens Schittenhelm, Ulrike Ernemann i Uwe Klose. "Glioma-Specific Diffusion Signature in Diffusion Kurtosis Imaging". Journal of Clinical Medicine 10, nr 11 (26.05.2021): 2325. http://dx.doi.org/10.3390/jcm10112325.
Pełny tekst źródłade Matos, Jonathan, Steve Ataky, Alceu de Souza Britto, Luiz Soares de Oliveira i Alessandro Lameiras Koerich. "Machine Learning Methods for Histopathological Image Analysis: A Review". Electronics 10, nr 5 (27.02.2021): 562. http://dx.doi.org/10.3390/electronics10050562.
Pełny tekst źródłaWarman, Pranav, Syed M. Adil, Andreas Seas, Daniel Sexton, Evan Calabrese, Nandan P. Lad, Brad Kolls i in. "381 Glioma Three-Dimensional Shape Predicts Underlying Genetic Mutations". Neurosurgery 70, Supplement_1 (kwiecień 2024): 115. http://dx.doi.org/10.1227/neu.0000000000002809_381.
Pełny tekst źródłaHulahan, Taylor S., Elizabeth N. Wallace, Siri H. Strand, Graham A. Colditz, E. Shelley Hwang, Robert West, Laura Spruill, Jeffrey Marks, Richard R. Drake i 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, nr 5_Supplement (1.03.2023): P2–21–03—P2–21–03. http://dx.doi.org/10.1158/1538-7445.sabcs22-p2-21-03.
Pełny tekst źródłaHulahan, Taylor S., Elizabeth N. Wallace, Siri H. Strand, Robert Michael Angelo, Graham Colditz, Eun-Sil Shelley Hwang, Robert West i in. "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, nr 12_Supplement_1 (1.12.2022): B019. http://dx.doi.org/10.1158/1940-6215.dcis22-b019.
Pełny tekst źródłaXu, Rui, Zhizhen Wang, Zhenbing Liu, Chu Han, Lixu Yan, Huan Lin, Zeyan Xu i in. "Histopathological Tissue Segmentation of Lung Cancer with Bilinear CNN and Soft Attention". BioMed Research International 2022 (7.07.2022): 1–10. http://dx.doi.org/10.1155/2022/7966553.
Pełny tekst źródłaZadeh Shirazi, Amin, Mark D. McDonnell, Eric Fornaciari, Narjes Sadat Bagherian, Kaitlin G. Scheer, Michael S. Samuel, Mahdi Yaghoobi i in. "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, nr 3 (29.04.2021): 337–50. http://dx.doi.org/10.1038/s41416-021-01394-x.
Pełny tekst źródłaAlGhamdi, Rayed. "Mitotic Nuclei Segmentation and Classification Using Chaotic Butterfly Optimization Algorithm with Deep Learning on Histopathology Images". Biomimetics 8, nr 6 (5.10.2023): 474. http://dx.doi.org/10.3390/biomimetics8060474.
Pełny tekst źródłaJakola, Asgeir S., David Bouget, Ingerid Reinertsen, Anne J. Skjulsvik, Lisa Millgård Sagberg, Hans Kristian Bø, Sasha Gulati, Kristin Sjåvik i Ole Solheim. "Spatial distribution of malignant transformation in patients with low-grade glioma". Journal of Neuro-Oncology 146, nr 2 (styczeń 2020): 373–80. http://dx.doi.org/10.1007/s11060-020-03391-1.
Pełny tekst źródłaWang, Edmond. "Glioblastoma Synthesis and Segmentation with 3D Multi-Modal MRI: A Study using Generative Adversarial Networks". International Journal on Computational Science & Applications 11, nr 6 (31.12.2021): 1–14. http://dx.doi.org/10.5121/ijcsa.2021.11601.
Pełny tekst źródłaVerghese, Gregory, Mengyuan Li, Amit Lohan, Nikhil Cherian, Swapnil Rane, Fangfang Liu, Aekta Shah i in. "Abstract 6233: A deep learning pipeline to capture the prognostic immune responses in lymph nodes of breast cancer patients". Cancer Research 82, nr 12_Supplement (15.06.2022): 6233. http://dx.doi.org/10.1158/1538-7445.am2022-6233.
Pełny tekst źródłaHeiland, Dieter, Robin Ohle, Simon Behringer, Juergen Beck i Oliver Schnell. "NIMG-63. LONGITUDINAL ANALYSIS OF OLIGODENDROGLIOMA GROWTH PATTERN REVEALED SPATIAL HETEROGENEITY AND DIVERSE TREATMENT RESPONSE". Neuro-Oncology 21, Supplement_6 (listopad 2019): vi175. http://dx.doi.org/10.1093/neuonc/noz175.732.
Pełny tekst źródłaWach, Johannes, Claudia Goetz, Kasra Shareghi, Torben Scholz, Volker Heßelmann, Ann-Kathrin Mager, Joachim Gottschalk, Hartmut Vatter i 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, nr 06 (4.07.2019): 413–22. http://dx.doi.org/10.1055/s-0039-1692975.
Pełny tekst źródłaWalkowski, Slawomir, i Janusz Szymas. "Histopathologic Patterns of Nervous System Tumors Based on Computer Vision Methods and Whole Slide Imaging (WSI)". Analytical Cellular Pathology 35, nr 2 (2012): 117–22. http://dx.doi.org/10.1155/2012/483525.
Pełny tekst źródłaKanta Maitra, Indra, i Samir Kumar Bandyopadhyay. "CAD Based Method for Detection of Breast Cancer". Oriental journal of computer science and technology 11, nr 3 (10.09.2018): 154–68. http://dx.doi.org/10.13005/ojcst11.03.04.
Pełny tekst źródłaGui, Chloe, Jonathan C. Lau i 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 (czerwiec 2018): S6. http://dx.doi.org/10.1017/cjn.2018.274.
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