| dc.contributor | 應物所 | |
| dc.creator (作者) | 蔡尚岳 | |
| dc.creator (作者) | Tsai, Shang-Yueh;Huang, Yu-Long;Lin, Yi-Ru | |
| dc.date (日期) | 2024-07 | |
| dc.date.accessioned | 28-十月-2024 13:15:36 (UTC+8) | - |
| dc.date.available | 28-十月-2024 13:15:36 (UTC+8) | - |
| dc.date.issued (上傳時間) | 28-十月-2024 13:15:36 (UTC+8) | - |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/154141 | - |
| dc.description.abstract (摘要) | Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have found a variety of applications on the process of MRS data. A quantification strategy compatible to DL base MRS spectral processing method is, therefore, useful. | |
| dc.format.extent | 106 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Magnetic Resonance Materials in Physics, Biology and Medicine: Official Journal of the European Society for Magnetic Resonance in Medicine and Biology, Vol.37, pp.477-489 | |
| dc.subject (關鍵詞) | Convolutional neural network; Magnetic resonance spectroscopy; Metabolite concentrations | |
| dc.title (題名) | Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1007/s10334-023-01120-z | |
| dc.doi.uri (DOI) | https://doi.org/10.1007/s10334-023-01120-z | |
