Deep learning achieves radiologist-level performance of tumor segmentation in breast MRI. - Lukas Hirsch; Yu Huang 014; Shaojun Luo; Carolina Rossi Saccarelli; Roberto Lo Gullo; Isaac Daimiel Naranjo; Almir Galvão Vieira Bitencourt; Natsuko Onishi; Eun Sook Ko; Dortis Leithner; Daly Avendano; Sarah Eskreis-Winkler; et al. (CoRR, 2020)

RadiomicsFill-Mammo: Synthetic Mammogram Mass Manipulation with Radiomics Features. - Inye Na; Jonghun Kim; Eun Sook Ko; Hyunjin Park (MICCAI (3), 2024)

Tumor Synthesis Conditioned on Radiomics. - Jonghun Kim; Inye Na; Eun Sook Ko; Hyunjin Park (WACV, 2025)

Enhancing radiomics features via a large language model for classifying benign and malignant breast tumors in mammography. - Sinyoung Ra; Jonghun Kim; Inye Na; Eun Sook Ko; Hyunjin Park (Comput. Methods Programs Biomed., 2025)