Zobrazeno 1 - 10
of 347
pro vyhledávání: '"Kunder, Christian A."'
Autor:
Eminaga, Okyaz, Abbas, Mahmoud, Kunder, Christian, Tolkach, Yuri, Han, Ryan, Brooks, James D., Nolley, Rosalie, Semjonow, Axel, Boegemann, Martin, West, Robert, Long, Jin, Fan, Richard, Bettendorf, Olaf
Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on
Externí odkaz:
http://arxiv.org/abs/2308.11992
Autor:
Bhattacharya, Indrani, Lim, David S., Aung, Han Lin, Liu, Xingchen, Seetharaman, Arun, Kunder, Christian A., Shao, Wei, Soerensen, Simon J. C., Fan, Richard E., Ghanouni, Pejman, To'o, Katherine J., Brooks, James D., Sonn, Geoffrey A., Rusu, Mirabela
Prostate cancer is the second deadliest cancer for American men. While Magnetic Resonance Imaging (MRI) is increasingly used to guide targeted biopsies for prostate cancer diagnosis, its utility remains limited due to high rates of false positives an
Externí odkaz:
http://arxiv.org/abs/2112.02164
Autor:
Shao, Wei, Bhattacharya, Indrani, Soerensen, Simon J. C., Kunder, Christian A., Wang, Jeffrey B., Fan, Richard E., Ghanouni, Pejman, Brooks, James D., Sonn, Geoffrey A., Rusu, Mirabela
The interpretation of prostate MRI suffers from low agreement across radiologists due to the subtle differences between cancer and normal tissue. Image registration addresses this issue by accurately mapping the ground-truth cancer labels from surgic
Externí odkaz:
http://arxiv.org/abs/2106.12526
Autor:
Shao, Wei, Vesal, Sulaiman, Soerensen, Simon J.C., Bhattacharya, Indrani, Golestani, Negar, Yamashita, Rikiya, Kunder, Christian A., Fan, Richard E., Ghanouni, Pejman, Brooks, James D., Sonn, Geoffrey A., Rusu, Mirabela
Publikováno v:
In Computers in Biology and Medicine May 2024 173
Autor:
Liu, Shiqin, Chai, Timothy, Garcia-Marques, Fernando, Yin, Qingqing, Hsu, En-Chi, Shen, Michelle, Shaw Toland, Angus Martin, Bermudez, Abel, Hartono, Alifiani B., Massey, Christopher F., Lee, Chung S., Zheng, Liwei, Baron, Maya, Denning, Caden J., Aslan, Merve, Nguyen, Holly M., Nolley, Rosalie, Zoubeidi, Amina, Das, Millie, Kunder, Christian A., Howitt, Brooke E., Soh, H. Tom, Weissman, Irving L., Liss, Michael A., Chin, Arnold I., Brooks, James D., Corey, Eva, Pitteri, Sharon J., Huang, Jiaoti, Stoyanova, Tanya
Publikováno v:
In Cell Reports Medicine 20 February 2024 5(2)
Autor:
Jun, Soyeong, Shukla, Nikhil A., Durm, Greg, Hui, Angela B., Cao, Sha, Ganti, Apar Kishor, Jabbour, Salma K., Kunder, Christian, Alizadeh, Ash A., Hanna, Nasser H., Diehn, Maximilian
Publikováno v:
In Journal of Thoracic Oncology June 2024
Autor:
Shao, Wei, Banh, Linda, Kunder, Christian A., Fan, Richard E., Soerensen, Simon J. C., Wang, Jeffrey B., Teslovich, Nikola C., Madhuripan, Nikhil, Jawahar, Anugayathri, Ghanouni, Pejman, Brooks, James D., Sonn, Geoffrey A., Rusu, Mirabela
Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and treatment of prostate cancer. However, interpretation of MRI suffers from high inter-observer variability across radiologists, thereby contributing to missed cli
Externí odkaz:
http://arxiv.org/abs/2012.00991
Autor:
Bhattacharya, Indrani, Seetharaman, Arun, Shao, Wei, Sood, Rewa, Kunder, Christian A., Fan, Richard E., Soerensen, Simon John Christoph, Wang, Jeffrey B., Ghanouni, Pejman, Teslovich, Nikola C., Brooks, James D., Sonn, Geoffrey A., Rusu, Mirabela
Magnetic Resonance Imaging (MRI) is widely used for screening and staging prostate cancer. However, many prostate cancers have subtle features which are not easily identifiable on MRI, resulting in missed diagnoses and alarming variability in radiolo
Externí odkaz:
http://arxiv.org/abs/2008.00119
Autor:
Eminaga, Okyaz, Abbas, Mahmood, Tolkach, Yuri, Nolley, Rosalie, Kunder, Christian, Semjonow, Axel, Boegemann, Martin
Histopathology is a reflection of the molecular changes and provides prognostic phenotypes representing the disease progression. In this study, we introduced feature scores generated from hematoxylin and eosin histology images based on deep learning
Externí odkaz:
http://arxiv.org/abs/1910.09100
Autor:
Eminaga, Okyaz, Tolkach, Yuri, Kunder, Christian, Abbas, Mahmood, Han, Ryan, Nolley, Rosalie, Semjonow, Axel, Boegemann, Martin, Huss, Sebastian, Loening, Andreas, West, Robert, Sonn, Geoffrey, Fan, Richard, Bettendorf, Olaf, Brook, James, Rubin, Daniel
The current study detects different morphologies related to prostate pathology using deep learning models; these models were evaluated on 2,121 hematoxylin and eosin (H&E) stain histology images captured using bright field microscopy, which spanned a
Externí odkaz:
http://arxiv.org/abs/1910.04918