Publications by authors named "Sewoo Kim"
Article Synopsis
- A study was conducted to assess the effectiveness of deep learning techniques in reconstructing virtual monoenergetic images (VMIs) from dual-energy CT scans of the liver, focusing on hypervascular lesions.
- The research included 109 patients and compared the image quality of VMIs reconstructed using both adaptive statistical iterative reconstruction (ASiR-V) and a deep learning method (ClariCT.AI) at different energy levels (40 keV and 70 keV).
- Results showed that the deep learning reconstructed images at 40 keV had significantly improved image quality, including lower noise, better sharpness, and higher diagnostic acceptability compared to traditional methods, making it more effective for evaluating liver lesions.
Introduction: Differentiating between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) is critical for developing a therapeutic strategy to treat multiple lung cancers with multiple pulmonary sites of involvement.
Methods: We retrospectively included 252 lesions (126 pairs) from 126 patients with surgically resected multiple lung adenocarcinomas. Each pair was classified as MPLC or IPM based on histopathologic findings as the reference standard.