Zobrazeno 1 - 10
of 205
pro vyhledávání: '"Fedorov, Andrey A."'
Autor:
Murugesan, Gowtham Krishnan, McCrumb, Diana, Soni, Rahul, Kumar, Jithendra, Nuernberg, Leonard, Pei, Linmin, Wagner, Ulrike, Granger, Sutton, Fedorov, Andrey Y., Moore, Stephen, Van Oss, Jeff
AI in Medical Imaging project aims to enhance the National Cancer Institute's (NCI) Image Data Commons (IDC) by developing nnU-Net models and providing AI-assisted segmentations for cancer radiology images. We created high-quality, AI-annotated imagi
Externí odkaz:
http://arxiv.org/abs/2409.20342
Autor:
Krishnaswamy, Deepa, Thiriveedhi, Vamsi Krishna, Ciausu, Cosmin, Clunie, David, Pieper, Steve, Kikinis, Ron, Fedorov, Andrey
There is a dire need for medical imaging datasets with accompanying annotations to perform downstream patient analysis. However, it is difficult to manually generate these annotations, due to the time-consuming nature, and the variability in clinical
Externí odkaz:
http://arxiv.org/abs/2406.14486
Autor:
Krishnaswamy, Deepa, Kovács, Bálint, Denner, Stefan, Pieper, Steve, Clunie, David, Bridge, Christopher P., Kapur, Tina, Maier-Hein, Klaus H., Fedorov, Andrey
With the wealth of medical image data, efficient curation is essential. Assigning the sequence type to magnetic resonance images is necessary for scientific studies and artificial intelligence-based analysis. However, incomplete or missing metadata p
Externí odkaz:
http://arxiv.org/abs/2404.10892
Autor:
Ciausu, Cosmin, Krishnaswamy, Deepa, Billot, Benjamin, Pieper, Steve, Kikinis, Ron, Fedorov, Andrey
Deep learning has shown great promise in the ability to automatically annotate organs in magnetic resonance imaging (MRI) scans, for example, of the brain. However, despite advancements in the field, the ability to accurately segment abdominal organs
Externí odkaz:
http://arxiv.org/abs/2403.15609
Autor:
Murugesan, Gowtham Krishnan, McCrumb, Diana, Aboian, Mariam, Verma, Tej, Soni, Rahul, Memon, Fatima, Farahani, Keyvan, Pei, Linmin, Wagner, Ulrike, Fedorov, Andrey Y., Clunie, David, Moore, Stephen, Van Oss, Jeff
The National Cancer Institute (NCI) Image Data Commons (IDC) offers publicly available cancer radiology collections for cloud computing, crucial for developing advanced imaging tools and algorithms. Despite their potential, these collections are mini
Externí odkaz:
http://arxiv.org/abs/2310.14897
Autor:
Chrisochoides, Nikos, Fedorov, Andrey, Liu, Yixun, Kot, Andriy, Foteinos, Panos, Drakopoulos, Fotis, Tsolakis, Christos, Billias, Emmanuel, Clatz, Olivier, Ayache, Nicholas, Golby, Alex, Black, Peter, Kikinis, Ron
Current neurosurgical procedures utilize medical images of various modalities to enable the precise location of tumors and critical brain structures to plan accurate brain tumor resection. The difficulty of using preoperative images during the surger
Externí odkaz:
http://arxiv.org/abs/2309.03336
Autor:
Afiaz, Awan, Ivanov, Andrey, Chamberlin, John, Hanauer, David, Savonen, Candace, Goldman, Mary J, Morgan, Martin, Reich, Michael, Getka, Alexander, Holmes, Aaron, Pati, Sarthak, Knight, Dan, Boutros, Paul C., Bakas, Spyridon, Caporaso, J. Gregory, Del Fiol, Guilherme, Hochheiser, Harry, Haas, Brian, Schloss, Patrick D., Eddy, James A., Albrecht, Jake, Fedorov, Andrey, Waldron, Levi, Hoffman, Ava M., Bradshaw, Richard L., Leek, Jeffrey T., Wright, Carrie
Software is vital for the advancement of biology and medicine. Analysis of usage and impact metrics can help developers determine user and community engagement, justify additional funding, encourage additional use, identify unanticipated use cases, a
Externí odkaz:
http://arxiv.org/abs/2306.03255
Autor:
Krishnaswamy, Deepa, Bontempi, Dennis, Thiriveedhi, Vamsi, Punzo, Davide, Clunie, David, Bridge, Christopher P, Aerts, Hugo JWL, Kikinis, Ron, Fedorov, Andrey
Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating their downstream analysis. Artificial intelligence-ba
Externí odkaz:
http://arxiv.org/abs/2306.00150
Autor:
Schacherer, Daniela P., Herrmann, Markus D., Clunie, David A., Höfener, Henning, Clifford, William, Longabaugh, William J. R., Pieper, Steve, Kikinis, Ron, Fedorov, Andrey, Homeyer, André
Publikováno v:
Comput Methods Programs Biomed (2023)
Background and Objectives: Reproducibility is a major challenge in developing machine learning (ML)-based solutions in computational pathology (CompPath). The NCI Imaging Data Commons (IDC) provides >120 cancer image collections according to the FAIR
Externí odkaz:
http://arxiv.org/abs/2303.09354
Autor:
Cheverda, Vladimir, Reshetova, Galina, Kabannik, Artem, Fedorov, Andrey, Korkin, Roman, Demidov, Demid, Balalayev, Viktor
A numerical method is proposed for carrying out a full-scale simulation of the process of propagation of an acoustic signal in a cased well. The main goal is to study the interaction of the wave field with the vertical boundary of the cement filling
Externí odkaz:
http://arxiv.org/abs/2302.13907