Nalee Kim
Samsung Medical Center
49 Papers
78 Citations
Nalee Kim is an academic researcher from Samsung Medical Center. The author has contributed to research in topics: Medicine & Radiation therapy. The author has an hindex of 10, co-authored 49 publications. Previous affiliations of Nalee Kim include Yonsei University & University Health System.
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Papers
Stereotactic body radiation therapy vs. radiofrequency ablation in Asian patients with hepatocellular carcinoma.
Nalee Kim,Jason Chia-Hsien Cheng,Inkyung Jung,Ja-Der Liang,Yu-Lueng Shih,Wen Yen Huang,Tomoki Kimura,Victor Ho-Fun Lee,Zhao Chong Zeng,Ren Zhenggan,Chul Seung Kay,Seok-Jae Heo,J. Won,Jinsil Seong +13 more
TL;DR: SBRT could be an effective alternative to RFA for unresectable HCC when considering tumor size and subphrenic region, and particularly for those tumors that progress after transarterial chemoembolization.
155
Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer.
Min Seo Choi,Byeong Su Choi,Seung Yeun Chung,Nalee Kim,Jaehee Chun,Yong Bae Kim,Jee Suk Chang,Jin Sung Kim +7 more
TL;DR: Deep learning-based auto-segmentation (DLBAS) was more consistent and robust in its performance than ABAS across the majority of structures when examining both CTVs and normal organs and has great potential to aid a key process in the radiation therapy workflow.
86
Proton beam therapy reduces the risk of severe radiation-induced lymphopenia during chemoradiotherapy for locally advanced non-small cell lung cancer: A comparative analysis of proton versus photon therapy.
TL;DR: In this article, the authors investigated differences in severe radiation-induced lymphopenia (SRL) after pencil beam scanning proton therapy (PBSPT) or intensity-modulated (photon) radiotherapy (IMRT) for patients with locally advanced non-small cell lung cancer.
47
Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers.
TL;DR: ABAS could help physicians to delineate the CTV and organs-at-risk (e.g., femurs) in IMRT planning considering its consistency, efficacy, and accuracy.
Clinical Evaluation of Commercial Atlas-Based Auto-Segmentation in the Head and Neck Region.
Hyothaek Lee,Eungman Lee,Nalee Kim,Joo Ho Kim,Kwangwoo Park,Ho Lee,Jaehee Chun,J. I. Shin,Jee Suk Chang,Jin Sung Kim +9 more
TL;DR: The performance of AS AC generally increased as the population of the atlas library increased, however, the performance does not drastically vary in the larger atlas libraries in contrast to the logic that bigger atlas Library should lead to better results.