Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Tsang, Yee Wah"'
Autor:
Graham, Simon, Jahanifar, Mostafa, Azam, Ayesha, Nimir, Mohammed, Tsang, Yee-Wah, Dodd, Katherine, Hero, Emily, Sahota, Harvir, Tank, Atisha, Benes, Ksenija, Wahab, Noorul, Minhas, Fayyaz, Raza, Shan E Ahmed, Daly, Hesham El, Gopalakrishnan, Kishore, Snead, David, Rajpoot, Nasir
The development of deep segmentation models for computational pathology (CPath) can help foster the investigation of interpretable morphological biomarkers. Yet, there is a major bottleneck in the success of such approaches because supervised deep le
Externí odkaz:
http://arxiv.org/abs/2108.11195
Autor:
Wahab, Noorul, Miligy, Islam M, Dodd, Katherine, Sahota, Harvir, Toss, Michael, Lu, Wenqi, Jahanifar, Mostafa, Bilal, Mohsin, Graham, Simon, Park, Young, Hadjigeorghiou, Giorgos, Bhalerao, Abhir, Lashen, Ayat, Ibrahim, Asmaa, Katayama, Ayaka, Ebili, Henry O, Parkin, Matthew, Sorell, Tom, Raza, Shan E Ahmed, Hero, Emily, Eldaly, Hesham, Tsang, Yee Wah, Gopalakrishnan, Kishore, Snead, David, Rakha, Emad, Rajpoot, Nasir, Minhas, Fayyaz
Recent advances in whole slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence (AI) based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an int
Externí odkaz:
http://arxiv.org/abs/2106.13689
To train a robust deep learning model, one usually needs a balanced set of categories in the training data. The data acquired in a medical domain, however, frequently contains an abundance of healthy patients, versus a small variety of positive, abno
Externí odkaz:
http://arxiv.org/abs/2003.03109
Autor:
Bilal, Mohsin *, Tsang, Yee Wah *, Ali, Mahmoud, Graham, Simon, Hero, Emily, Wahab, Noorul, Dodd, Katherine, Sahota, Harvir, Wu, Shaobin, Lu, Wenqi, Jahanifar, Mostafa, Robinson, Andrew, Azam, Ayesha, Benes, Ksenija, Nimir, Mohammed, Hewitt, Katherine, Bhalerao, Abhir, Eldaly, Hesham, Raza, Shan E Ahmed, Gopalakrishnan, Kishore, Minhas, Fayyaz, Snead, David, Rajpoot, Nasir *
Publikováno v:
In The Lancet Digital Health November 2023 5(11):e786-e797
Autor:
Graham, Simon, Vu, Quoc Dang, Raza, Shan E Ahmed, Azam, Ayesha, Tsang, Yee Wah, Kwak, Jin Tae, Rajpoot, Nasir
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow. The development of automated methods for nuclear segmentation and classification enables th
Externí odkaz:
http://arxiv.org/abs/1812.06499
Akademický článek
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Autor:
Graham, Simon, Chen, Hao, Gamper, Jevgenij, Dou, Qi, Heng, Pheng-Ann, Snead, David, Tsang, Yee Wah, Rajpoot, Nasir
Publikováno v:
Medical Image Analysis vol. 52, pp. 199-211, Feb. 2019
The analysis of glandular morphology within colon histopathology images is an important step in determining the grade of colon cancer. Despite the importance of this task, manual segmentation is laborious, time-consuming and can suffer from subjectiv
Externí odkaz:
http://arxiv.org/abs/1806.01963
Autor:
Qaiser, Talha, Tsang, Yee-Wah, Taniyama, Daiki, Sakamoto, Naoya, Nakane, Kazuaki, Epstein, David, Rajpoot, Nasir
Tumor segmentation in whole-slide images of histology slides is an important step towards computer-assisted diagnosis. In this work, we propose a tumor segmentation framework based on the novel concept of persistent homology profiles (PHPs). For a gi
Externí odkaz:
http://arxiv.org/abs/1805.03699
Autor:
Sirinukunwattana, Korsuk, Snead, David, Epstein, David, Aftab, Zia, Mujeeb, Imaad, Tsang, Yee Wah, Cree, Ian, Rajpoot, Nasir
Distant metastasis is the major cause of death in colorectal cancer (CRC). Patients at high risk of developing distant metastasis could benefit from appropriate adjuvant and follow-up treatments if stratified accurately at an early stage of the disea
Externí odkaz:
http://arxiv.org/abs/1801.07451
Akademický článek
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