Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Nasir Rajpoot"'
Autor:
Muhammad Dawood, Quoc Dang Vu, Lawrence S. Young, Kim Branson, Louise Jones, Nasir Rajpoot, Fayyaz ul Amir Afsar Minhas
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-13 (2024)
Abstract Drug sensitivity prediction models can aid in personalising cancer therapy, biomarker discovery, and drug design. Such models require survival data from randomised controlled trials which can be time consuming and expensive. In this proof-of
Externí odkaz:
https://doaj.org/article/6768fc83a73c4f70af6501cfb444206e
Autor:
Noorul Wahab, Michael Toss, Islam M. Miligy, Mostafa Jahanifar, Nehal M. Atallah, Wenqi Lu, Simon Graham, Mohsin Bilal, Abhir Bhalerao, Ayat G. Lashen, Shorouk Makhlouf, Asmaa Y. Ibrahim, David Snead, Fayyaz Minhas, Shan E. Ahmed Raza, Emad Rakha, Nasir Rajpoot
Publikováno v:
npj Precision Oncology, Vol 7, Iss 1, Pp 1-13 (2023)
Abstract Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an ob
Externí odkaz:
https://doaj.org/article/a9e6a8e5c93b4edab4db8a7980977476
Autor:
Wenqi Lu, Ayat G Lashen, Noorul Wahab, Islam M Miligy, Mostafa Jahanifar, Michael Toss, Simon Graham, Mohsin Bilal, Abhir Bhalerao, Nehal M Atallah, Shorouk Makhlouf, Asmaa Y Ibrahim, David Snead, Fayyaz Minhas, Shan E Ahmed Raza, Emad Rakha, Nasir Rajpoot
Publikováno v:
The Journal of Pathology: Clinical Research, Vol 10, Iss 1, Pp n/a-n/a (2024)
Abstract Early‐stage estrogen receptor positive and human epidermal growth factor receptor negative (ER+/HER2−) luminal breast cancer (BC) is quite heterogeneous and accounts for about 70% of all BCs. Ki67 is a proliferation marker that has a sig
Externí odkaz:
https://doaj.org/article/6a155cf9d05147a98b8a08c72dc26ccc
Autor:
Wenqi Lu, Islam M. Miligy, Fayyaz Minhas, Young Saeng Park, David R. J. Snead, Emad A. Rakha, Clare Verrill, Nasir Rajpoot
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract Due to COVID-19 outbreaks, most school pupils have had to be home-schooled for long periods of time. Two editions of a web-based competition “Beat the Pathologists” for school age participants in the UK ran to fill up pupils’ spare tim
Externí odkaz:
https://doaj.org/article/8d49f4b7cccc472abc9731b3bada6e3b
Autor:
Noorul Wahab, Islam M Miligy, Katherine Dodd, Harvir Sahota, Michael Toss, Wenqi Lu, Mostafa Jahanifar, Mohsin Bilal, Simon Graham, Young Park, Giorgos Hadjigeorghiou, Abhir Bhalerao, Ayat G Lashen, Asmaa Y Ibrahim, Ayaka Katayama, Henry O Ebili, Matthew Parkin, Tom Sorell, Shan E Ahmed Raza, Emily Hero, Hesham Eldaly, Yee Wah Tsang, Kishore Gopalakrishnan, David Snead, Emad Rakha, Nasir Rajpoot, Fayyaz Minhas
Publikováno v:
The Journal of Pathology: Clinical Research, Vol 8, Iss 2, Pp 116-128 (2022)
Abstract Recent advances in whole‐slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence‐based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offer
Externí odkaz:
https://doaj.org/article/0ab322726d414a3280ea866dedb9d11e
Autor:
Robert Pell, Karin Oien, Max Robinson, Helen Pitman, Nasir Rajpoot, Jens Rittscher, David Snead, Clare Verrill, on behalf of the UK National Cancer Research Institute (NCRI) Cellular‐Molecular Pathology (CM‐Path) quality assurance working group
Publikováno v:
The Journal of Pathology: Clinical Research, Vol 5, Iss 2, Pp 81-90 (2019)
Abstract Digital pathology and image analysis potentially provide greater accuracy, reproducibility and standardisation of pathology‐based trial entry criteria and endpoints, alongside extracting new insights from both existing and novel features.
Externí odkaz:
https://doaj.org/article/3eac2e361f014e41ab47fe9b499162ab
Autor:
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier, Klaus Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F. Neher, Wiro Niessen, Nasir Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der Sommen, Ching-Wei Wang, Marc-André Weber, Guoyan Zheng, Pierre Jannin, Annette Kopp-Schneider
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-13 (2018)
Biomedical image analysis challenges have increased in the last ten years, but common practices have not been established yet. Here the authors analyze 150 recent challenges and demonstrate that outcome varies based on the metrics used and that limit
Externí odkaz:
https://doaj.org/article/38c338af34d545ae996e15b163f6024c
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-13 (2017)
Abstract In this paper, we present a fast method for registration of multiple large, digitised whole-slide images (WSIs) of serial histology sections. Through cross-slide WSI registration, it becomes possible to select and analyse a common visual fie
Externí odkaz:
https://doaj.org/article/24885052516e417b9215118795241687
Autor:
Quoc Dang Vu, Simon Graham, Tahsin Kurc, Minh Nguyen Nhat To, Muhammad Shaban, Talha Qaiser, Navid Alemi Koohbanani, Syed Ali Khurram, Jayashree Kalpathy-Cramer, Tianhao Zhao, Rajarsi Gupta, Jin Tae Kwak, Nasir Rajpoot, Joel Saltz, Keyvan Farahani
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 7 (2019)
High-resolution microscopy images of tissue specimens provide detailed information about the morphology of normal and diseased tissue. Image analysis of tissue morphology can help cancer researchers develop a better understanding of cancer biology. S
Externí odkaz:
https://doaj.org/article/30861e31cc3d48c1b9696006a2d27cc8
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 7 (2019)
This study applied a deep-learning cell identification algorithm to diagnostic images from the colon cancer repository at The Cancer Genome Atlas (TCGA). Within-image sampling improved performance without loss of accuracy. The features thus derived w
Externí odkaz:
https://doaj.org/article/cddb975440b04b80a6e0c218cc746a8c