Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Tiffany C. Kwong"'
Publikováno v:
Optical Tomography and Spectroscopy of Tissue XV.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6b1f8f2aca84da532720cf9736d8d95
https://doi.org/10.1117/12.2651104
https://doi.org/10.1117/12.2651104
Autor:
Huay-Ben Pan, Rita S. Mehta, Sou-Hsin Chien, Kai-Ting Chang, Jeon-Hor Chen, Wei-Ching Lin, Tiffany C. Kwong, Chin-Yao Lin, Min-Ying Su, Ritesh Parajuli, Yang Zhang, Siwa Chan
Publikováno v:
Journal of Digital Imaging
To develop a U-net deep learning method for breast tissue segmentation on fat-sat T1-weighted (T1W) MRI using transfer learning (TL) from a model developed for non-fat-sat images. The training dataset (N = 126) was imaged on a 1.5 T MR scanner, and t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9deb8c217afbce94450395f7cba2517a
https://doi.org/10.1007/s10278-021-00472-z
https://doi.org/10.1007/s10278-021-00472-z
Autor:
Yin Zhang, Yongrui Bai, Ning J. Yue, Hongbin Cao, Shabbar F. Danish, Zhitao Dai, Zhiyan Xiao, Tiffany C. Kwong, Joseph Weiner, Ke Nie, Yu Kuang, Xiao Wang
Publikováno v:
Journal of Neurosurgery. 132:1024-1032
OBJECTIVEThe authors sought to compare the dosimetric quality of hypofractionated stereotactic radiosurgery in treating sizeable brain tumors across the following treatment platforms: GammaKnife (GK) Icon, CyberKnife (CK) G4, volumetric modulated arc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ad2f062a53aabb8419e34f0cd12a392
https://doi.org/10.3171/2018.12.jns181578
https://doi.org/10.3171/2018.12.jns181578
Publikováno v:
Biomed Opt Express
In preclinical research, fluorescence molecular tomography (FMT) is the most sensitive imaging modality to interrogate whole-body and provide 3D distribution of fluorescent contract agents. Despite its superior sensitivity, its mediocre spatial-resol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84e28234747bec8f6f777cc6c97e60e6
https://doi.org/10.1364/boe.470723
https://doi.org/10.1364/boe.470723
Autor:
Alex Luk, Min-Ying Su, Vivian Youngjean Park, Jeon-Hor Chen, Kai Ting Chang, Yang Zhang, Daniel S. Chow, Tiffany C. Kwong, Peter Chang, Min Jung Kim, Siwa Chan
Publikováno v:
Acad Radiol
Rationale and Objectives Breast segmentation using the U-net architecture was implemented and tested in independent validation datasets to quantify fibroglandular tissue volume in breast MRI. Materials and Methods Two datasets were used. The training
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c72e013d36e3b36be896e2668eeba1a
https://doi.org/10.1016/j.acra.2019.01.012
https://doi.org/10.1016/j.acra.2019.01.012
Autor:
Ning J. Yue, Jeon-Hor Chen, Min-Ying Su, Liming Shi, Tianye Niu, Xiaonan Sun, Ke Nie, Daniel S. Chow, Tiffany C. Kwong, Peter Chang, Yang Zhang
Publikováno v:
Magn Reson Imaging
Purpose To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with locally advanced rectal cancer (LARC) using radiomics and deep learning based on pre-treatment MRI and a mid-radiation follow-up MRI taken 3–4 weeks after the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a48460cd74a4b59c710d919eae172eb9
https://doi.org/10.1016/j.mri.2019.05.003
https://doi.org/10.1016/j.mri.2019.05.003
Autor:
Rita S. Mehta, Xinxin Wang, Siwa Chan, Jeon-Hor Chen, Min-Ying Su, Jiejie Zhou, Dah-Cherng Yeh, Peter Chang, Daniel S. Chow, Tiffany C. Kwong, Meihao Wang, Ritesh Parajuli, Yang Zhang, Yezhi Lin
Publikováno v:
Eur Radiol
European radiology, vol 31, iss 4
European radiology, vol 31, iss 4
To apply deep learning algorithms using a conventional convolutional neural network (CNN) and a recurrent CNN to differentiate three breast cancer molecular subtypes on MRI. A total of 244 patients were analyzed, 99 in training dataset scanned at 1.5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fe7bbcabbd2e163331c8aa9f87276dc
https://pubmed.ncbi.nlm.nih.gov/33001309
https://pubmed.ncbi.nlm.nih.gov/33001309
Autor:
Tiffany C. Kwong, Farouk Nouizi, Uma Sampathkumaran, Hakan Erkol, M. Al-Garawi, Gultekin Gulsen, Mehrnaz Mehrabi
Publikováno v:
Optical Tomography and Spectroscopy of Tissue XIII.
High scattering in biological tissues severely degrades the spatial resolution of optical fluorescence imaging in thick tissue. As one of the most sensitive in vivo molecular imaging modalities, Fluorescence Tomography plays an essential role in prec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f3febb79cc0a1f3a2b0614560e415ac
https://doi.org/10.1117/12.2508931
https://doi.org/10.1117/12.2508931
Publikováno v:
Applied optics, vol 56, iss 28
Previously, we demonstrated that temperature-modulated fluorescence tomography (TM-FT) could provide fluorescence images with high quantitative accuracy and the spatial resolution of focused ultrasound. TM-FT is based on scanning the focused ultrasou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49afc2d56132685b864467f01f18f534
https://europepmc.org/articles/PMC6855592/
https://europepmc.org/articles/PMC6855592/
Autor:
Tiffany C. Kwong, Pei An Lo, Farouk Nouizi, Jaedu Cho, Gultekin Gulsen, Huihua Kenny Chiang, Chang-Seok Kim
Publikováno v:
SPIE Proceedings.
The strong scattering and absorption of light in biological tissue makes it challenging to model the propagation of light, especially in deep tissue. This is especially true in fluorescent tomography, which aims to recover the internal fluorescence s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45bde37bc36a717cc3d584fe75a5f35a
https://doi.org/10.1117/12.2213816
https://doi.org/10.1117/12.2213816