Zobrazeno 1 - 10
of 23
pro vyhledávání: '"George, Thoma"'
Autor:
Sudhir Sornapudi, Jason Hagerty, R Joe Stanley, William V Stoecker, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shellaine R Frazier
Publikováno v:
Journal of Pathology Informatics, Vol 11, Iss 1, Pp 10-10 (2020)
Background: Automated pathology techniques for detecting cervical cancer at the premalignant stage have advantages for women in areas with limited medical resources. Methods: This article presents EpithNet, a deep learning approach for the critical s
Externí odkaz:
https://doaj.org/article/ccc54531b85847f9b72da2f329c298b7
Autor:
Haidar A AlMubarak, Joe Stanley, Peng Guo, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane Frazier, William Stoecker
Cervical cancer is the second most common cancer affecting women worldwide but is curable if diagnosed early. Routinely, expert pathologists visually examine histology slides for assessing cervix tissue abnormalities. A localized, fusion-based, hybri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96a7104ba54f5863bda62a08e9520164
https://doi.org/10.4018/978-1-6684-7136-4.ch003
https://doi.org/10.4018/978-1-6684-7136-4.ch003
Publikováno v:
Applied Sciences, Vol 8, Iss 10, p 1715 (2018)
Pneumonia affects 7% of the global population, resulting in 2 million pediatric deaths every year. Chest X-ray (CXR) analysis is routinely performed to diagnose the disease. Computer-aided diagnostic (CADx) tools aim to supplement decision-making. Th
Externí odkaz:
https://doaj.org/article/5d4c102918364188a71984b75e44eca7
Autor:
Sudhir Sornapudi, Ronald Joe Stanley, William V Stoecker, Haidar Almubarak, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane R Frazier
Publikováno v:
Journal of Pathology Informatics, Vol 9, Iss 1, Pp 5-5 (2018)
Background: Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) c
Externí odkaz:
https://doaj.org/article/647afa52ad904d84a85a47afbfdf9817
Autor:
Peng Guo, Haidar Almubarak, Koyel Banerjee, R Joe Stanley, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane R Frazier, Randy H Moss, William V Stoecker
Publikováno v:
Journal of Pathology Informatics, Vol 7, Iss 1, Pp 51-51 (2016)
Background: In previous research, we introduced an automated, localized, fusion-based approach for classifying uterine cervix squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on digitized
Externí odkaz:
https://doaj.org/article/f7460249af4a4659aeac1ad25c8510bd
Publikováno v:
EMBC
In this paper, we aim to extract the aortic knuckle (AK) contour in chest radiographs, an anatomical structure rarely being addressed in the literature. Since the AK structure is small and thin, simply adopting the deep network methods that are succe
Images in biomedical publications often convey important information related to an article's content. When referenced properly, these images aid in clinical decision support. Annotations such as text labels and symbols, as provided by medical experts
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7eba94a86d707e7ac675b534aa67b9fc
https://doi.org/10.4018/978-1-5225-0571-6.ch018
https://doi.org/10.4018/978-1-5225-0571-6.ch018
Autor:
James L, Littlefield, George, Thoma
Publikováno v:
Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 57(4)
Publikováno v:
Quantitative imaging in medicine and surgery. 4(6)
The U.S. National Library of Medicine has made two datasets of postero-anterior (PA) chest radiographs available to foster research in computer-aided diagnosis of pulmonary diseases with a special focus on pulmonary tuberculosis (TB). The radiographs
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium.
Medical resident physicians used MD on Tap in real time to search for MEDLINE citations relevant to clinical questions using three search engines: Essie, Entrez and Google™, in order of performance.