Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data. - Tran Minh Quan; David Grant Colburn Hildebrand; Kanggeun Lee; Logan A. Thomas; Aaron T. Kuan; Wei-Chung Allen Lee 001; Won-Ki Jeong (ICCV Workshops, 2019)

Neuron Segmentation using Incomplete and Noisy Labels via Adaptive Learning with Structure Priors. - Chanmin Park; Kanggeun Lee; Suyeon Kim; Fatma Sema Canbakis Cecen; Seok-Kyu Kwon; Won-Ki Jeong (ISBI, 2021)

Improving the Accuracy of Intrahepatic Cholangiocarcinoma Subtype Classification by Hidden Class Detection via Label Smoothing. - Jing Wei Tan; Kanggeun Lee; Kyoungbun Lee; Won-Ki Jeong (ISBI, 2021)

PAIP 2019: Liver cancer segmentation challenge. - Yoo Jung Kim; Hyungjoon Jang; Kyoungbun Lee; Seongkeun Park; Sung-Gyu Min; Choyeon Hong; Jeong Hwan Park; Kanggeun Lee; Jisoo Kim; Wonjae Hong; Hyun Jung; Yanling Liu; et al. (Medical Image Anal., 2021)

ISCL: Interdependent Self-Cooperative Learning for Unpaired Image Denoising. - Kanggeun Lee; Won-Ki Jeong (IEEE Trans. Medical Imaging, 2021)

Scribble-Supervised Cell Segmentation Using Multiscale Contrastive Regularization. - Hyun-Jic Oh; Kanggeun Lee; Won-Ki Jeong (ISBI, 2022)

Noise2Kernel: Adaptive Self-Supervised Blind Denoising Using a Dilated Convolutional Kernel Architecture. - Kanggeun Lee; Won-Ki Jeong (Sensors, 2022)

Undersampled MRI Reconstruction Using Switchable Interdependent Self-Cooperative Learning Without Paired Training Data. - Suemin Jeon; Kanggeun Lee; Won-Ki Jeong (ISBI, 2023)

I2V: Towards Texture-Aware Self-Supervised Blind Denoising using Self-Residual Learning for Real-World Images. - Kanggeun Lee; Kyungryun Lee; Won-Ki Jeong (CoRR, 2023)

RAMP: response-aware multi-task learning with contrastive regularization for cancer drug response prediction. - Kanggeun Lee; Dongbin Cho; Jinho Jang; Kang Choi; Hyoung-oh Jeong; Jiwon Seo 002; Won-Ki Jeong; Semin Lee (Briefings Bioinform., 2023)