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Showing results 1 to 12 of 12

Issue DateTitle / Author(s) / CitationFileAltmetrics
2018-02
Repeat biopsy of patients with acquired resistance to EGFR TKIs: implications of biopsy-related factors on T790M mutation detection
DOI
2018-03
Improving the prediction of lung adenocarcinoma invasive component on CT: Value of a vessel removal algorithm during software segmentation of subsolid nodules

Garzelli, Lorenzo; Goo, Jin Mo; Ahn, Su Yeon; Chae, Kum Ju; Park, Chang Min; Jung, Julip; Hong, Helen

European Journal of Radiology, Vol.100, pp.58-65

DOI
2018-06
Comparison of iodine density measurement among dual-energy computed tomography scanners from 3 vendors

Kim, Hyungjin; Goo, Jin Mo; Kang, Chang Kyung; Chae, Kum Ju; Park, Chang Min

Investigative Radiology, Vol.53 No.6, pp.321-327

DOI
2018-10
Effect of CT acquisition parameters on iodine density measurement at dual-layer spectral CT

Kim, Hyungjin; Park, Chang Min; Kang, Chang Kyung; Yoon, Jinyeong; Chae, Kum Ju; Goo, Jin Mo

American Journal of Roentgenology, Vol.211 No.4, pp.748-754

DOI
2019-08
Non-diagnostic Results of Percutaneous Transthoracic Needle Biopsy: A Meta-analysis
DOI
2020-05
Quantitative CT-based structural alterations of segmental airways in cement dust-exposed subjects
view fileDOI
2020-07
Patterns of percutaneous transthoracic needle biopsy (PTNB) of the lung and risk of PTNB-related severe pneumothorax: A nationwide population-based study
DOI
2020-10
Quantitative CT-based image registration metrics provide different ventilation and lung motion patterns in prone and supine positions in healthy subjects
view fileDOI
2020-11
Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019
DOI
2021-02
2020 Clinical Practice Guideline for Percutaneous Transthoracic Needle Biopsy of Pulmonary Lesions: A Consensus Statement and Recommendations of the Korean Society of Thoracic Radiology
DOI
2022-07
A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography
DOI
2023-02
Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study
DOI
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