Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Sherine Salama"'
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-13 (2018)
Abstract Completely labeled pathology datasets are often challenging and time-consuming to obtain. Semi-supervised learning (SSL) methods are able to learn from fewer labeled data points with the help of a large number of unlabeled data points. In th
Externí odkaz:
https://doaj.org/article/792b44f9bc9942699642a822cd3b0d25
Publikováno v:
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. 7:260-265
Digital pathology has advanced substantially over the last decade with the adoption of slide scanners in pathology labs. The use of digital slides to analyse diseases at the microscopic level is both cost-effective and efficient. Identifying complex
Publikováno v:
Cytometry Part A. 91:1078-1087
Neoadjuvant treatment (NAT) of breast cancer (BCa) is an option for patients with the locally advanced disease. It has been compared with standard adjuvant therapy with the aim of improving prognosis and surgical outcome. Moreover, the response of th
Autor:
Rachel Isaksson Vogel, J. Richter, Sherine Salama, Mahmoud A. Khalifa, Boris Winterhoff, Tanya Pulver, Molly Klein, Sally A. Mullany
Publikováno v:
American Journal of Clinical Pathology. 147:322-326
Objectives Intraoperative consultation (IOC) remains an area of general practice even within subspecialized pathology departments. This study assesses the IOCs rendered in a general pathology setting where surgeons integrate these results in a well-d
Autor:
Sherine Salama, Anne L. Martel, Shazia Akbar, Mohammad Peikari, Sharon Nofech-Mozes, Azadeh Yazdan Panah
Publikováno v:
Scientific Reports
Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
AimsThe residual cancer burden index is an important quantitative measure used for assessing treatment response following neoadjuvant therapy for breast cancer. It has shown to be predictive of overall survival and is composed of two key metrics: qua
Publikováno v:
Digital Pathology ISBN: 9783030239367
ECDP
ECDP
Segmentation of ducts in whole slide images is an important step needed to analyze ductal carcinoma in-situ (DCIS), an early form of breast cancer. Here, we train several U-Net architectures – deep convolutional neural networks designed to output p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::93c81602be435f51e87526e1f63ae97b
https://doi.org/10.1007/978-3-030-23937-4_8
https://doi.org/10.1007/978-3-030-23937-4_8
Autor:
Ali Ghodsi, Anne L. Martel, Mehrdad J. Gangeh, Sharon Nofech-Mozes, Mohammad Peikari, Sherine Salama, Rene Bidart
Publikováno v:
Medical Imaging: Digital Pathology
Neoadjuvant therapy (NAT) is an option for locally advanced breast cancer patients to downsize tumour allowing for less extensive surgical operation, better cosmetic outcomes, and lesser post-operative complications. The quality of NAT is assessed by
Publikováno v:
Medical Imaging: Digital Pathology
The residual cancer burden index is a powerful prognostic factor which is used to measure neoadjuvant therapy response in invasive breast cancers. Tumor cellularity is one component of the residual cancer burden index and is currently measured manual
Publikováno v:
Scientific Reports
Scientific Reports, Vol 8, Iss 1, Pp 1-13 (2018)
Scientific Reports, Vol 8, Iss 1, Pp 1-13 (2018)
Completely labeled pathology datasets are often challenging and time-consuming to obtain. Semi-supervised learning (SSL) methods are able to learn from fewer labeled data points with the help of a large number of unlabeled data points. In this paper,
Publikováno v:
Cytometry. Part A : the journal of the International Society for Analytical Cytology. 91(11)
Neoadjuvant treatment (NAT) of breast cancer (BCa) is an option for patients with the locally advanced disease. It has been compared with standard adjuvant therapy with the aim of improving prognosis and surgical outcome. Moreover, the response of th