Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients

Daisuke Takenaka, Yoshiyuki Ozawa, Kaori Yamamoto, Maiko Shinohara, Masato Ikedo, Masao Yui, Yuka Oshima, Nayu Hamabuchi, Hiroyuki Nagata, Takahiro Ueda, Hirotaka Ikeda, Akiyoshi Iwase, Takeshi Yoshikawa, Hiroshi Toyama, Yoshiharu Ohno

研究成果: ジャーナルへの寄稿学術論文査読

2 被引用数 (Scopus)

フィンガープリント

「Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

Medicine and Dentistry

Agricultural and Biological Sciences

Keyphrases

Pharmacology, Toxicology and Pharmaceutical Science