Zobrazeno 1 - 10
of 167
pro vyhledávání: '"Kreshuk Anna"'
Publikováno v:
BIO Web of Conferences, Vol 129, p 10020 (2024)
Externí odkaz:
https://doaj.org/article/1125e0c72db54f9d948e2621d40c50b7
Autor:
Bunne, Charlotte, Roohani, Yusuf, Rosen, Yanay, Gupta, Ankit, Zhang, Xikun, Roed, Marcel, Alexandrov, Theo, AlQuraishi, Mohammed, Brennan, Patricia, Burkhardt, Daniel B., Califano, Andrea, Cool, Jonah, Dernburg, Abby F., Ewing, Kirsty, Fox, Emily B., Haury, Matthias, Herr, Amy E., Horvitz, Eric, Hsu, Patrick D., Jain, Viren, Johnson, Gregory R., Kalil, Thomas, Kelley, David R., Kelley, Shana O., Kreshuk, Anna, Mitchison, Tim, Otte, Stephani, Shendure, Jay, Sofroniew, Nicholas J., Theis, Fabian, Theodoris, Christina V., Upadhyayula, Srigokul, Valer, Marc, Wang, Bo, Xing, Eric, Yeung-Levy, Serena, Zitnik, Marinka, Karaletsos, Theofanis, Regev, Aviv, Lundberg, Emma, Leskovec, Jure, Quake, Stephen R.
The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intell
Externí odkaz:
http://arxiv.org/abs/2409.11654
Autor:
Bajcsy, Peter, Bhattiprolu, Sreenivas, Boerner, Katy, Cimini, Beth A, Collinson, Lucy, Ellenberg, Jan, Fiolka, Reto, Giger, Maryellen, Goscinski, Wojtek, Hartley, Matthew, Hotaling, Nathan, Horwitz, Rick, Jug, Florian, Kreshuk, Anna, Lundberg, Emma, Mathur, Aastha, Narayan, Kedar, Onami, Shuichi, Plant, Anne L., Prior, Fred, Swedlow, Jason, Taylor, Adam, Keppler, Antje
Coordinated collaboration is essential to realize the added value of and infrastructure requirements for global image data sharing in the life sciences. In this White Paper, we take a first step at presenting some of the most common use cases as well
Externí odkaz:
http://arxiv.org/abs/2401.13023
Autor:
Zulueta-Coarasa, Teresa, Jug, Florian, Mathur, Aastha, Moore, Josh, Muñoz-Barrutia, Arrate, Anita, Liviu, Babalola, Kola, Bankhead, Pete, Gilloteaux, Perrine, Gogoberidze, Nodar, Jones, Martin, Kleywegt, Gerard J., Korir, Paul, Kreshuk, Anna, Yoldaş, Aybüke Küpcü, Marconato, Luca, Narayan, Kedar, Norlin, Nils, Oezdemir, Bugra, Riesterer, Jessica, Rzepka, Norman, Sarkans, Ugis, Serrano, Beatriz, Tischer, Christian, Uhlmann, Virginie, Ulman, Vladimír, Hartley, Matthew
Artificial Intelligence methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new methods, but access to such data is often hindered by the lack of standards for shar
Externí odkaz:
http://arxiv.org/abs/2311.10443
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:
Maier-Hein, Lena, Reinke, Annika, Godau, Patrick, Tizabi, Minu D., Buettner, Florian, Christodoulou, Evangelia, Glocker, Ben, Isensee, Fabian, Kleesiek, Jens, Kozubek, Michal, Reyes, Mauricio, Riegler, Michael A., Wiesenfarth, Manuel, Kavur, A. Emre, Sudre, Carole H., Baumgartner, Michael, Eisenmann, Matthias, Heckmann-Nötzel, Doreen, Rädsch, Tim, Acion, Laura, Antonelli, Michela, Arbel, Tal, Bakas, Spyridon, Benis, Arriel, Blaschko, Matthew, Cardoso, M. Jorge, Cheplygina, Veronika, Cimini, Beth A., Collins, Gary S., Farahani, Keyvan, Ferrer, Luciana, Galdran, Adrian, van Ginneken, Bram, Haase, Robert, Hashimoto, Daniel A., Hoffman, Michael M., Huisman, Merel, Jannin, Pierre, Kahn, Charles E., Kainmueller, Dagmar, Kainz, Bernhard, Karargyris, Alexandros, Karthikesalingam, Alan, Kenngott, Hannes, Kofler, Florian, Kopp-Schneider, Annette, 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, Rajpoot, Nasir, 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, Jäger, Paul F.
Publikováno v:
Nature methods, 1-18 (2024)
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus fa
Externí odkaz:
http://arxiv.org/abs/2206.01653
Autor:
Hilt, Paul, Zarvandi, Maedeh, Kaziakhmedov, Edgar, Bhide, Sourabh, Leptin, Maria, Pape, Constantin, Kreshuk, Anna
Instance segmentation is an important computer vision problem which remains challenging despite impressive recent advances due to deep learning-based methods. Given sufficient training data, fully supervised methods can yield excellent performance, b
Externí odkaz:
http://arxiv.org/abs/2107.02600
Autor:
Reinke, Annika, Tizabi, Minu D., Sudre, Carole H., Eisenmann, Matthias, Rädsch, Tim, Baumgartner, Michael, Acion, Laura, Antonelli, Michela, Arbel, Tal, Bakas, Spyridon, Bankhead, Peter, Benis, Arriel, Blaschko, Matthew, Buettner, Florian, Cardoso, M. Jorge, Chen, Jianxu, Cheplygina, Veronika, Christodoulou, Evangelia, Cimini, Beth, Collins, Gary S., Engelhardt, Sandy, Farahani, Keyvan, Ferrer, Luciana, Galdran, Adrian, van Ginneken, Bram, Glocker, Ben, Godau, Patrick, Haase, Robert, Hamprecht, Fred, Hashimoto, Daniel A., Heckmann-Nötzel, Doreen, Hirsch, Peter, Hoffman, Michael M., Huisman, Merel, Isensee, Fabian, Jannin, Pierre, Kahn, Charles E., Kainmueller, Dagmar, Kainz, Bernhard, Karargyris, Alexandros, Karthikesalingam, Alan, Kavur, A. Emre, Kenngott, Hannes, Kleesiek, Jens, Kleppe, Andreas, Kohler, Sven, Kofler, Florian, Kopp-Schneider, Annette, Kooi, Thijs, 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, Moher, David, Moons, Karel G. M., Müller, Henning, Nichyporuk, Brennan, Nickel, Felix, Noyan, M. Alican, Petersen, Jens, Polat, Gorkem, Rafelski, Susanne M., Rajpoot, Nasir, Reyes, Mauricio, Rieke, Nicola, Riegler, Michael, Rivaz, Hassan, Saez-Rodriguez, Julio, Sánchez, Clara I., Schroeter, Julien, Saha, Anindo, Selver, M. Alper, Sharan, Lalith, Shetty, Shravya, van Smeden, Maarten, Stieltjes, Bram, Summers, Ronald M., Taha, Abdel A., Tiulpin, Aleksei, Tsaftaris, Sotirios A., Van Calster, Ben, Varoquaux, Gaël, Wiesenfarth, Manuel, Yaniv, Ziv R., Jäger, Paul, Maier-Hein, Lena
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performan
Externí odkaz:
http://arxiv.org/abs/2104.05642
Most state-of-the-art instance segmentation methods have to be trained on densely annotated images. While difficult in general, this requirement is especially daunting for biomedical images, where domain expertise is often required for annotation and
Externí odkaz:
http://arxiv.org/abs/2103.14572
This work introduces a new proposal-free instance segmentation method that builds on single-instance segmentation masks predicted across the entire image in a sliding window style. In contrast to related approaches, our method concurrently predicts a
Externí odkaz:
http://arxiv.org/abs/2009.04998