Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Gordon S. Okimoto"'
Publikováno v:
CDC
In this work, we developed an algorithm for the integrated analysis of multiple high-dimensional data matrices based on sparse rank-one matrix approximations. The algorithm approximates multiple data matrices with rank one outer products composed of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d818870f6571cbba1e8e55d63ca9a001
https://doi.org/10.1109/cdc.2015.7402818
https://doi.org/10.1109/cdc.2015.7402818
Publikováno v:
American journal of nuclear medicine and molecular imaging. 6(1)
PET using fluorine-18 fluorocholine ((18)F-fluorocholine) may detect malignancies that involve altered choline metabolism. While (18)F-fluorocholine PET/CT has shown greater sensitivity for detecting hepatocellular carcinoma (HCC) than (18)F-fluoro-D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::0a8c91a46ff0a973cebd5f7ce32811ab
https://pubmed.ncbi.nlm.nih.gov/27069767
https://pubmed.ncbi.nlm.nih.gov/27069767
Autor:
Gordon S. Okimoto, Steven J. Saggese, Gregory C. Mooradian, Kunio Miyazawa, Dennis M. O'Connor, Mary F. Parker
Publikováno v:
American Journal of Obstetrics and Gynecology. 187:398-402
Objective: The aim of this study was to initiate neural net construction for the detection of cervical intraepithelial neoplasia by fluorescence imaging. Study Design: Thirty-three women with abnormal Papanicolaou smears underwent fluorescence imagin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::383144d66b53469db1ad5baf00973ddc
https://doi.org/10.1067/mob.2002.123940
https://doi.org/10.1067/mob.2002.123940
Autor:
Gordon S. Okimoto
Publikováno v:
Systems Biology and Synthetic Biology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54aac91bf7e86ba4130c652f514e9cc1
https://doi.org/10.1002/9780470437988.ch4
https://doi.org/10.1002/9780470437988.ch4
Autor:
Gordon S, Okimoto
Publikováno v:
Hawaii medical journal. 66(1)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::0d3fa5bfe1a8917e5f6f23d083d00b4a
https://pubmed.ncbi.nlm.nih.gov/17381038
https://pubmed.ncbi.nlm.nih.gov/17381038
Autor:
Mary F. Parker, Gordon S. Okimoto, Gregory C. Mooradian, Kunio Miyazawa, Dennis M. O'Connor, Steven J. Saggese, Ames A. Grisanti
Publikováno v:
Clinical Diagnostic Systems.
Principal component analysis (PCA) in the wavelet domain provides powerful new features for the non-invasive detection of cervical intraepithelial neoplasia (CIN) using fluorescence imaging spectroscopy. These features are known as principal wavelet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82b88d08019e5553bac8bc30710eadb8
https://doi.org/10.1117/12.426747
https://doi.org/10.1117/12.426747
Autor:
David W. Lemonds, Gordon S. Okimoto
Publikováno v:
SPIE Proceedings.
Principal component analysis (PCA) in the wavelet domain provides powerful features for underwater object recognition applications. The multiresolution analysis of the Morlet wavelet transform (MWT) is used to pre-process echo returns from targets en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e46ff544cb1c917af212e4dc20e8d388
https://doi.org/10.1117/12.357091
https://doi.org/10.1117/12.357091
Publikováno v:
SPIE Proceedings.
Signal features based on multiresolution short-time Fourier transforms (STFT) and the Morlet wavelet transform (MWT) have been developed to classify echo returns from targets ensonified by simulated dolphin echolocation clicks. Spectrogram features a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9aa8c49a346625601b5a1a8192e175c4
https://doi.org/10.1117/12.324204
https://doi.org/10.1117/12.324204