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pro vyhledávání: '"Becker, Anton S."'
Autor:
Campanella, Gabriele, Ho, David, Häggström, Ida, Becker, Anton S, Chang, Jason, Vanderbilt, Chad, Fuchs, Thomas J
Lung cancer is the leading cause of cancer death worldwide, with lung adenocarcinoma being the most prevalent form of lung cancer. EGFR positive lung adenocarcinomas have been shown to have high response rates to TKI therapy, underlying the essential
Externí odkaz:
http://arxiv.org/abs/2206.10573
Autor:
Becker, Anton S., Woo, Sungmin, Leithner, Doris, Tong, Angela, Mayerhoefer, Marius E., Vargas, H. Alberto
Publikováno v:
In European Journal of Radiology October 2024 179
Autor:
Becker, Anton S., Das, Jeeban P., Woo, Sungmin, Vilela de Oliveira, Camila, Charbel, Charlotte, Perez-Johnston, Rocio, Vargas, Hebert Alberto
Publikováno v:
In European Journal of Radiology April 2024 173
We analyze the effect of using a screening CT-scan for evaluation of potential COVID-19 infections in order to isolate and perform contact tracing based upon a viral pneumonia diagnosis. RT-PCR is then used for continued isolation based upon a COVID
Externí odkaz:
http://arxiv.org/abs/2006.02140
Autor:
Baumgartner, Christian F., Tezcan, Kerem C., Chaitanya, Krishna, Hötker, Andreas M., Muehlematter, Urs J., Schawkat, Khoschy, Becker, Anton S., Donati, Olivio, Konukoglu, Ender
Segmentation of anatomical structures and pathologies is inherently ambiguous. For instance, structure borders may not be clearly visible or different experts may have different styles of annotating. The majority of current state-of-the-art methods d
Externí odkaz:
http://arxiv.org/abs/1906.04045
Supervised deep learning relies on the assumption that enough training data is available, which presents a problem for its application to several fields, like medical imaging. On the example of a binary image classification task (breast cancer recogn
Externí odkaz:
http://arxiv.org/abs/1902.07762
Autor:
Becker, Anton S., Giganti, Francesco, Purysko, Andrei, Fainberg, Jonathan, Alberto Vargas, Hebert, Woo, Sungmin
Publikováno v:
In European Journal of Radiology June 2023
Akademický článek
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Autor:
Becker, Anton S., Jendele, Lukas, Skopek, Ondrej, Berger, Nicole, Ghafoor, Soleen, Marcon, Magda, Konukoglu, Ender
$\textbf{Purpose}$ To train a cycle-consistent generative adversarial network (CycleGAN) on mammographic data to inject or remove features of malignancy, and to determine whether these AI-mediated attacks can be detected by radiologists. $\textbf{Mat
Externí odkaz:
http://arxiv.org/abs/1811.07767
Autor:
Woo, Sungmin, Freedman, Daniel, Becker, Anton S., Leithner, Doris, Mayerhoefer, Marius E., Friedman, Kent P., Arita, Yuki, Han, Sangwon, Burger, Irene A., Taneja, Samir S., Wise, David R., Zelefsky, Michael J., Vargas, Hebert A.
Publikováno v:
Clinical & Translational Imaging; Oct2024, Vol. 12 Issue 5, p485-500, 16p