Zobrazeno 1 - 10
of 516
pro vyhledávání: '"Kurc, P"'
Autor:
Huang, Wentao, Xu, Meilong, Hu, Xiaoling, Abousamra, Shahira, Ganguly, Aniruddha, Kapse, Saarthak, Yurovsky, Alisa, Prasanna, Prateek, Kurc, Tahsin, Saltz, Joel, Miller, Michael L., Chen, Chao
Spatial transcriptomics (ST) provides essential spatial context by mapping gene expression within tissue, enabling detailed study of cellular heterogeneity and tissue organization. However, aligning ST data with histology images poses challenges due
Externí odkaz:
http://arxiv.org/abs/2411.15076
Autor:
Jose L. Agraz, Carlos Agraz, Andrew A. Chen, Charles Rice, Robert S. Pozos, Sven Aelterman, Amanda Tan, Angela N. Viaene, MacLean P. Nasrallah, Parth Sharma, Caleb M. Grenko, Tahsin Kurc, Joel Saltz, Michael D. Feldman, Hamed Akbari, Russell T. Shinohara, Spyridon Bakas, Parker Wilson
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 6, Pp 35-40 (2025)
In the medical diagnostics domain, pathology and histology are pivotal for the precise identification of diseases. Digital histopathology, enhanced by automation, facilitates the efficient analysis of massive amount of biopsy images produced on a dai
Externí odkaz:
https://doaj.org/article/b030f1dc9ecb465a94aa6bee6081d1d8
Autor:
Kaczmarzyk, Jakub R., O'Callaghan, Alan, Inglis, Fiona, Kurc, Tahsin, Gupta, Rajarsi, Bremer, Erich, Bankhead, Peter, Saltz, Joel H.
The field of digital pathology has seen a proliferation of deep learning models in recent years. Despite substantial progress, it remains rare for other researchers and pathologists to be able to access models published in the literature and apply th
Externí odkaz:
http://arxiv.org/abs/2309.04631
Autor:
Yellapragada, Srikar, Graikos, Alexandros, Prasanna, Prateek, Kurc, Tahsin, Saltz, Joel, Samaras, Dimitris
To achieve high-quality results, diffusion models must be trained on large datasets. This can be notably prohibitive for models in specialized domains, such as computational pathology. Conditioning on labeled data is known to help in data-efficient m
Externí odkaz:
http://arxiv.org/abs/2309.00748
In digital pathology, the spatial context of cells is important for cell classification, cancer diagnosis and prognosis. To model such complex cell context, however, is challenging. Cells form different mixtures, lineages, clusters and holes. To mode
Externí odkaz:
http://arxiv.org/abs/2304.02255
Autor:
Reinke, Annika, Tizabi, Minu D., Baumgartner, Michael, Eisenmann, Matthias, Heckmann-Nötzel, Doreen, Kavur, A. Emre, Rädsch, Tim, Sudre, Carole H., Acion, Laura, Antonelli, Michela, Arbel, Tal, Bakas, Spyridon, Benis, Arriel, Blaschko, Matthew, Buettner, Florian, Cardoso, M. Jorge, Cheplygina, Veronika, Chen, Jianxu, Christodoulou, Evangelia, Cimini, Beth A., Collins, Gary S., Farahani, Keyvan, Ferrer, Luciana, Galdran, Adrian, van Ginneken, Bram, Glocker, Ben, Godau, Patrick, Haase, Robert, Hashimoto, Daniel A., Hoffman, Michael M., Huisman, Merel, Isensee, Fabian, Jannin, Pierre, Kahn, Charles E., Kainmueller, Dagmar, Kainz, Bernhard, Karargyris, Alexandros, Karthikesalingam, Alan, Kenngott, Hannes, Kleesiek, Jens, Kofler, Florian, Kooi, Thijs, Kopp-Schneider, Annette, Kozubek, Michal, Kreshuk, Anna, Kurc, Tahsin, Landman, Bennett A., Litjens, Geert, Madani, Amin, Maier-Hein, Klaus, Martel, Anne L., Mattson, Peter, Meijering, Erik, Menze, Bjoern, Moons, Karel G. M., Müller, Henning, Nichyporuk, Brennan, Nickel, Felix, Petersen, Jens, Rafelski, Susanne M., Rajpoot, Nasir, Reyes, Mauricio, Riegler, Michael A., Rieke, Nicola, Saez-Rodriguez, Julio, Sánchez, Clara I., Shetty, Shravya, van Smeden, Maarten, Summers, Ronald M., Taha, Abdel A., Tiulpin, Aleksei, Tsaftaris, Sotirios A., Van Calster, Ben, Varoquaux, Gaël, Wiesenfarth, Manuel, Yaniv, Ziv R., Jäger, Paul F., Maier-Hein, Lena
Publikováno v:
Nature methods, 1-13 (2024)
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in im
Externí odkaz:
http://arxiv.org/abs/2302.01790
Autor:
Lyanne Delgado-Coka, Michael Horowitz, Mariana Torrente-Goncalves, Lucia Roa-Peña, Cindy V. Leiton, Mahmudul Hasan, Sruthi Babu, Danielle Fassler, Jaymie Oentoro, Ji-Dong K Bai, Emanuel F. Petricoin, Lynn M. Matrisian, Edik Matthew Blais, Natalia Marchenko, Felicia D. Allard, Wei Jiang, Brent Larson, Andrew Hendifar, Chao Chen, Shahira Abousamra, Dimitris Samaras, Tahsin Kurc, Joel Saltz, Luisa F. Escobar-Hoyos, Kenneth R. Shroyer
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-16 (2024)
Abstract Background The immune microenvironment impacts tumor growth, invasion, metastasis, and patient survival and may provide opportunities for therapeutic intervention in pancreatic ductal adenocarcinoma (PDAC). Although never studied as a potent
Externí odkaz:
https://doaj.org/article/d0bfc3b841b643c9bb6db994b3bb87d5
Autor:
Ema Kantorová, Marianna Vítková, Martina Martiníková, Andrea Cimprichová, Miriam Fedicˇová, Slavomíra Kovácˇová, Miroslav Mako, Juraj Cisár, Viera Hancˇinová, Jarmila Szilasiová, Peter Koleda, Jana RoháIˇová, Jana Polóniová, Martin Karlík, Darina Slezáková, Eleonóra Klímová, Matúš Maciak, Egon Kurcˇa, Petra Hnilicová
Publikováno v:
Therapeutic Advances in Neurological Disorders, Vol 17 (2024)
Background: Alemtuzumab (ALEM) is a humanised monoclonal antibody that depletes circulating lymphocytes by selectively targeting CD52, which is expressed in high levels on T- and B-lymphocytes. This depletion is followed by lymphocyte repopulation an
Externí odkaz:
https://doaj.org/article/2a1d7ef584194f8c9b83c37de0ea4bad
Autor:
Gupta, Saumya, Hu, Xiaoling, Kaan, James, Jin, Michael, Mpoy, Mutshipay, Chung, Katherine, Singh, Gagandeep, Saltz, Mary, Kurc, Tahsin, Saltz, Joel, Tassiopoulos, Apostolos, Prasanna, Prateek, Chen, Chao
Deep learning methods have achieved impressive performance for multi-class medical image segmentation. However, they are limited in their ability to encode topological interactions among different classes (e.g., containment and exclusion). These cons
Externí odkaz:
http://arxiv.org/abs/2207.09654
The combination of data analysis methods, increasing computing capacity, and improved sensors enable quantitative granular, multi-scale, cell-based analyses. We describe the rich set of application challenges related to tissue interpretation and surv
Externí odkaz:
http://arxiv.org/abs/2206.07573