Zobrazeno 1 - 10
of 241
pro vyhledávání: '"Rajpoot, Nasir M"'
Autor:
Shephard, Adam J, Jahanifar, Mostafa, Wang, Ruoyu, Dawood, Muhammad, Graham, Simon, Sidlauskas, Kastytis, Khurram, Syed Ali, Rajpoot, Nasir M, Raza, Shan E Ahmed
Tumour-infiltrating lymphocytes (TILs) are considered as a valuable prognostic markers in both triple-negative and human epidermal growth factor receptor 2 (HER2) positive breast cancer. In this study, we introduce an innovative deep learning pipelin
Externí odkaz:
http://arxiv.org/abs/2311.06185
Autor:
Shephard, Adam J, Mahmood, Hanya, Raza, Shan E Ahmed, Araujo, Anna Luiza Damaceno, Santos-Silva, Alan Roger, Lopes, Marcio Ajudarte, Vargas, Pablo Agustin, McCombe, Kris, Craig, Stephanie, James, Jacqueline, Brooks, Jill, Nankivell, Paul, Mehanna, Hisham, Khurram, Syed Ali, Rajpoot, Nasir M
Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. OED grading is subject to large inter/intra-rater variability, resulting in the under/over-treatment of patients. We developed a new Tr
Externí odkaz:
http://arxiv.org/abs/2311.05452
Autor:
Shephard, Adam J, Bashir, Raja Muhammad Saad, Mahmood, Hanya, Jahanifar, Mostafa, Minhas, Fayyaz, Raza, Shan E Ahmed, McCombe, Kris D, Craig, Stephanie G, James, Jacqueline, Brooks, Jill, Nankivell, Paul, Mehanna, Hisham, Khurram, Syed Ali, Rajpoot, Nasir M
Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. Its grading suffers from significant inter-/intra- observer variability, and does not reliably predict malignancy progression, potentia
Externí odkaz:
http://arxiv.org/abs/2307.03757
Autor:
Graham, Simon, Vu, Quoc Dang, Jahanifar, Mostafa, Weigert, Martin, Schmidt, Uwe, Zhang, Wenhua, Zhang, Jun, Yang, Sen, Xiang, Jinxi, Wang, Xiyue, Rumberger, Josef Lorenz, Baumann, Elias, Hirsch, Peter, Liu, Lihao, Hong, Chenyang, Aviles-Rivero, Angelica I., Jain, Ayushi, Ahn, Heeyoung, Hong, Yiyu, Azzuni, Hussam, Xu, Min, Yaqub, Mohammad, Blache, Marie-Claire, Piégu, Benoît, Vernay, Bertrand, Scherr, Tim, Böhland, Moritz, Löffler, Katharina, Li, Jiachen, Ying, Weiqin, Wang, Chixin, Kainmueller, Dagmar, Schönlieb, Carola-Bibiane, Liu, Shuolin, Talsania, Dhairya, Meda, Yughender, Mishra, Prakash, Ridzuan, Muhammad, Neumann, Oliver, Schilling, Marcel P., Reischl, Markus, Mikut, Ralf, Huang, Banban, Chien, Hsiang-Chin, Wang, Ching-Ping, Lee, Chia-Yen, Lin, Hong-Kun, Liu, Zaiyi, Pan, Xipeng, Han, Chu, Cheng, Jijun, Dawood, Muhammad, Deshpande, Srijay, Bashir, Raja Muhammad Saad, Shephard, Adam, Costa, Pedro, Nunes, João D., Campilho, Aurélio, Cardoso, Jaime S., S, Hrishikesh P, Puthussery, Densen, G, Devika R, C V, Jiji, Zhang, Ye, Fang, Zijie, Lin, Zhifan, Zhang, Yongbing, Lin, Chunhui, Zhang, Liukun, Mao, Lijian, Wu, Min, Vo, Vi Thi-Tuong, Kim, Soo-Hyung, Lee, Taebum, Kondo, Satoshi, Kasai, Satoshi, Dumbhare, Pranay, Phuse, Vedant, Dubey, Yash, Jamthikar, Ankush, Vuong, Trinh Thi Le, Kwak, Jin Tae, Ziaei, Dorsa, Jung, Hyun, Miao, Tianyi, Snead, David, Raza, Shan E Ahmed, Minhas, Fayyaz, Rajpoot, Nasir M.
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest
Externí odkaz:
http://arxiv.org/abs/2303.06274
Some major challenges associated with the automated processing of whole slide images (WSIs) includes their sheer size, different magnification levels and high resolution. Utilizing these images directly in AI frameworks is computationally expensive d
Externí odkaz:
http://arxiv.org/abs/2302.09682
Semantic segmentation of various tissue and nuclei types in histology images is fundamental to many downstream tasks in the area of computational pathology (CPath). In recent years, Deep Learning (DL) methods have been shown to perform well on segmen
Externí odkaz:
http://arxiv.org/abs/2301.13141
Federated learning (FL) enables collaborative learning of a deep learning model without sharing the data of participating sites. FL in medical image analysis tasks is relatively new and open for enhancements. In this study, we propose FedDropoutAvg,
Externí odkaz:
http://arxiv.org/abs/2111.13230
Autor:
Shephard, Adam J., Graham, Simon, Bashir, R. M. Saad, Jahanifar, Mostafa, Mahmood, Hanya, Khurram, Syed Ali, Rajpoot, Nasir M.
Oral epithelial dysplasia (OED) is a pre-malignant histopathological diagnosis given to lesions of the oral cavity. Predicting OED grade or whether a case will transition to malignancy is critical for early detection and appropriate treatment. OED ty
Externí odkaz:
http://arxiv.org/abs/2108.13904
"Is it possible to predict expression levels of different genes at a given spatial location in the routine histology image of a tumor section by modeling its stain absorption characteristics?" In this work, we propose a "stain-aware" machine learning
Externí odkaz:
http://arxiv.org/abs/2108.10446
Can we predict if an early stage cancer patient is at high risk of developing distant metastasis and what clinicopathological factors are associated with such a risk? In this paper, we propose a ranking based censoring-aware machine learning model fo
Externí odkaz:
http://arxiv.org/abs/2108.10365