Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Joseph N. Stember"'
Publikováno v:
Journal of Digital Imaging. 36:536-546
Cancer centers have an urgent and unmet clinical and research need for AI that can guide patient management. A core component of advancing cancer treatment research is assessing response to therapy. Doing so by hand, for example, as per RECIST or RAN
Autor:
Joseph N. Stember, Hrithwik Shalu
Publikováno v:
International Symposium on Intelligent Informatics ISBN: 9789811980930
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92bb959f4353a0689f2076dc9d219916
https://doi.org/10.1007/978-981-19-8094-7_12
https://doi.org/10.1007/978-981-19-8094-7_12
Autor:
Joseph N. Stember, Hrithwik Shalu
Publikováno v:
International Symposium on Intelligent Informatics ISBN: 9789811980930
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79e5485302430a6260dc40667bb97ae0
https://doi.org/10.1007/978-981-19-8094-7_19
https://doi.org/10.1007/978-981-19-8094-7_19
Autor:
Lawrence H. Schwartz, Angela Lignelli, Sachin Jambawalikar, Bradford J. Wood, Haydar Celik, Elizabeth A. Krupinski, Gul Moonis, Joseph N. Stember, Ulas Bagci, Peter Chang, Simukayi Mutasa
Publikováno v:
Journal of Digital Imaging
Deep learning with convolutional neural networks (CNNs) has experienced tremendous growth in multiple healthcare applications and has been shown to have high accuracy in semantic segmentation of medical (e.g., radiology and pathology) images. However
Publikováno v:
J Digit Imaging
Even though teeth are often included in the field of view for a variety of medical CT studies, dental pathology is often missed by radiologists. Given the myriad morbidity and occasional mortality associated with sequelae of dental pathology, an impo
Autor:
Elizabeth A. Krupinski, Bradford J. Wood, Joseph N. Stember, Sarah Eskreis-Winkler, Nathaniel Swinburne, David A. Gutman, Haydar Celik, Sachin Jambawalikar, Peter Chang, Robert Young, Andrei I. Holodny, Ulas Bagci
Publikováno v:
Radiol Artif Intell
PURPOSE: To generate and assess an algorithm combining eye tracking and speech recognition to extract brain lesion location labels automatically for deep learning (DL). MATERIALS AND METHODS: In this retrospective study, 700 two-dimensional brain tum
Autor:
Joseph N. Stember
Publikováno v:
Journal of Digital Imaging. 31:904-911
Ultrasound is notoriously plagued by high user dependence. There is a steep drop-off in information in going from what the sonographer sees during image acquisition and what the interpreting radiologist is able to view at the reading station. One cou
Autor:
Joseph N Stember, Olaf Andersen
Publikováno v:
PLoS ONE, Vol 6, Iss 2, p e15563 (2011)
Membrane elastic properties, which are subject to alteration by compounds such as cholesterol, lipid metabolites and other amphiphiles, as well as pharmaceuticals, can have important effects on membrane proteins. A useful tool for measuring some of t
Externí odkaz:
https://doaj.org/article/2b3f7c5f1866462bb9ad9940d7c59c7a
Publikováno v:
Journal of Ultrasound in Medicine. 36:2203-2208
Objectives Early identification and quantification of bladder damage in pediatric patients with congenital anomalies of the kidney and urinary tract (CAKUT) is crucial to guiding effective treatment and may affect the eventual clinical outcome, inclu
Autor:
Joseph N. Stember, Naji Khosravan, Sachin Jambawalikar, Jonathan Shoag, Yu-Cheng Liu, Yulin Liu, Ulas Bagci
Publikováno v:
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data ISBN: 9783030333904
DART/MIL3ID@MICCAI
DART/MIL3ID@MICCAI
Creating large scale high-quality annotations is a known challenge in medical imaging. In this work, based on the CycleGAN algorithm, we propose leveraging annotations from one modality to be useful in other modalities. More specifically, the propose
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f543dfa907be46e39a91c9cd15ac1ba
https://doi.org/10.1007/978-3-030-33391-1_8
https://doi.org/10.1007/978-3-030-33391-1_8