Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Ralph Bernstein"'
Publikováno v:
Scientific American. 277:50-55
Autor:
Ralph, Bernstein
Publikováno v:
Revenue-cycle strategist. 8(6)
Autor:
Ralph, Bernstein
Publikováno v:
Revenue-cycle strategist. 8(1)
Publikováno v:
IBM Journal of Research and Development. 35:78-87
Autor:
Václav Kubeček, Patrick K. Rambo, Ralph Bernstein, Jens Schwarz, Luca Giuggioli, Jean-Claude Diels, Jens Biegert
Publikováno v:
SPIE Proceedings.
Pulses of 500 fs or greater duration and several tens of millijoules at 248 nm are used to trigger discharges in air. We will discuss the influence of beam geometry, the minimum field strength that can be triggered, and the electrical discharge guidi
Publikováno v:
SPIE Proceedings.
This paper describes techniques to visualize aneurysms in three dimensions from Magnetic Resonance Angiographic data sets to aid surgeons and radiologists in surgical planning and treatment of cerebrovascular (brain) aneurysms. Maximum Intensity Proj
Autor:
Ralph Bernstein
Publikováno v:
Clinical Gastroenterology and Hepatology. 7:1138
Publikováno v:
Medical Informatics Europe 1991 ISBN: 9783540543923
MIE
MIE
Magnetic Resonance Imaging (MRI) plays a relevant role in the design of systems for computer assisted diagnosis. MR-images are multi-dimensional in nature; physicians have to combine several perceptual information images to perform the tissue classif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a7983161949372b679b3cc133b64b16
https://doi.org/10.1007/978-3-642-93503-9_94
https://doi.org/10.1007/978-3-642-93503-9_94
Publikováno v:
SPIE Proceedings.
We describe the application of statistical clustering algorithms (approximate fuzzy C-means (AFCM) and ISODATA) and a Bayesian/maximum likelihood (BfML) classifier for data dimension reduction and information extraction with MRI. Analyses were perfor
Publikováno v:
SPIE Proceedings.
Supercomputer facilities have been applied to a problem in numerically intensive medical image processing. Magnetic Resonance Imaging (MRI) data was converted into a useful information product. The motivation for this work is the "information overloa