Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Eliot, Siegel"'
Autor:
Binit Vasant Gajera, Siddhant Raj Kapil, Dorsa Ziaei, Jayalakshmi Mangalagiri, Eliot Siegel, David Chapman
Publikováno v:
IEEE Access, Vol 9, Pp 84093-84109 (2021)
We propose a Generative Adversarial Network (GAN) optimized for noise reduction in CT-scans. The objective of CT scan denoising is to obtain higher quality imagery using a lower radiation exposure to the patient. Recent work in computer vision has sh
Externí odkaz:
https://doaj.org/article/b2d7b3aeabef466cbe77631a33f2a79a
Publikováno v:
Academic Radiology. 30:971-974
With a track record of innovation and unique access to digital data, radiologists are distinctly positioned to usher in a new medical era of artificial intelligence (AI).In this Perspective piece, we summarize AI initiatives that academic radiology d
Autor:
Babak, Saboury, Tyler, Bradshaw, Ronald, Boellaard, Irène, Buvat, Joyita, Dutta, Mathieu, Hatt, Abhinav K, Jha, Quanzheng, Li, Chi, Liu, Helena, McMeekin, Michael A, Morris, Neeta, Pandit-Taskar, Peter J H, Scott, Eliot, Siegel, John J, Sunderland, Richard L, Wahl, Sven, Zuehlsdorff, Arman, Rahmim
Publikováno v:
Saboury, B, Bradshaw, T, Boellaard, R, Buvat, I, Dutta, J, Hatt, M, Jha, A K, Li, Q, Liu, C, McMeekin, H, Morris, M A, Scott, P J H, Siegel, E, Sunderland, J J, Pandit-Taskar, N, Wahl, R L, Zuehlsdorff, S & Rahmim, A 2023, ' Artificial Intelligence in Nuclear Medicine : Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem ', Journal of nuclear medicine : official publication, Society of Nuclear Medicine, vol. 64, no. 2, pp. 188-196 . https://doi.org/10.2967/jnumed.121.263703
Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 64(2), 188-196
Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 64(2), 188-196
Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of healthcare. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We
Publikováno v:
Journal of the American College of Radiology. 19:192-200
Data sets with demographic imbalances can introduce bias in deep learning models and potentially amplify existing health disparities. We evaluated the reporting of demographics and potential biases in publicly available chest radiograph (CXR) data se
Autor:
Eliot Siegel
Publikováno v:
Applied Radiology. :27-30
Autor:
Dorsa Ziaei, Siddhant Raj Kapil, David Chapman, Binit Vasant Gajera, Jayalakshmi Mangalagiri, Eliot Siegel
Publikováno v:
IEEE Access, Vol 9, Pp 84093-84109 (2021)
We propose a Generative Adversarial Network (GAN) optimized for noise reduction in CT-scans. The objective of CT scan denoising is to obtain higher quality imagery using a lower radiation exposure to the patient. Recent work in computer vision has sh
Publikováno v:
Annual review of biomedical engineering. 24
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to health-care organizations worldwide. To combat the global crisis, the use of thoracic imaging has played a major role in the diagnosis, prediction, and management of
Autor:
Melissa Treviño, George Birdsong, Ann Carrigan, Peter Choyke, Trafton Drew, Miguel Eckstein, Anna Fernandez, Brandon D Gallas, Maryellen Giger, Stephen M Hewitt, Todd S Horowitz, Yuhong V Jiang, Bonnie Kudrick, Susana Martinez-Conde, Stephen Mitroff, Linda Nebeling, Joseph Saltz, Frank Samuelson, Steven E Seltzer, Behrouz Shabestari, Lalitha Shankar, Eliot Siegel, Mike Tilkin, Jennifer S Trueblood, Alison L Van Dyke, Aradhana M Venkatesan, David Whitney, Jeremy M Wolfe
Publikováno v:
JNCI Cancer Spectr
Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8e5b37a9279e26c833fb800f147417f
https://europepmc.org/articles/PMC8826981/
https://europepmc.org/articles/PMC8826981/
Publikováno v:
PET Clin
Artificial intelligence (AI) can enhance the efficiency of medical imaging quality control and clinical documentation, provide clinical decision support, and increase image acquisition and processing quality. A clear understanding of the basic tenets
Publikováno v:
PET Clinics. 17:i