A shape constrained parametric active contour model for breast contour detection. - Juhun Lee; Gautam S. Muralidhar; Gregory P. Reece; Mia K. Markey (EMBC, 2012)

A Novel Quantitative Measure of Breast Curvature Based on Catenary. - Juhun Lee; Si Chen; Gregory P. Reece; Melissa A. Crosby; Elisabeth K. Beahm; Mia K. Markey (IEEE Trans. Biomed. Eng., 2012)

Quantitative measures of facial expression for patients with head and neck cancer. - Juhun Lee; Michelle C. Fingeret; Irene Teo; Matthew M. Hanasono; Roman J. Skoracki; Mia K. Markey (EMBC, 2013)

Eigen-disfigurement model for simulating plausible facial disfigurement after reconstructive surgery. - Juhun Lee; Michelle Fingeret; Alan C. Bovik; Gregory P. Reece; Roman J. Skoracki; Matthew M. Hanasono; Mia K. Markey (BMC Medical Imaging, 2015)

Can model observers be developed to reproduce radiologists' diagnostic performances? Our study says not so fast! - Juhun Lee; Robert M. Nishikawa; Ingrid S. Reiser; John M. Boone (Image Perception, Observer Performance, and Technology Assessment, 2016)

Neutrosophic segmentation of breast lesions for dedicated breast CT. - Juhun Lee; Robert M. Nishikawa; Ingrid S. Reiser; John M. Boone (Computer-Aided Diagnosis, 2017)

Developing imaging biomarkers for mammographically-occult cancer in dense breasts using a radiologist's progress rating on cancer development: a preliminary analysis. - Juhun Lee; Sung Eun Song; Robert M. Nishikawa (IWBI, 2018)

Detecting mammographically-occult cancer in women with dense breasts using Radon Cumulative Distribution Transform: a preliminary analysis. - Juhun Lee; Robert M. Nishikawa; Gustavo K. Rohde (Computer-Aided Diagnosis, 2018)

Detecting mammographically-occult cancer in women with dense breasts using deep convolutional neural network and Radon cumulative distribution transform. - Juhun Lee; Robert M. Nishikawa (Computer-Aided Diagnosis, 2019)

Simulating breast mammogram using conditional generative adversarial network: application towards finding mammographically-occult cancer. - Juhun Lee; Robert M. Nishikawa (Computer-Aided Diagnosis, 2020)

Cross-Organ, Cross-Modality Transfer Learning: Feasibility Study for Segmentation and Classification. - Juhun Lee; Robert M. Nishikawa (IEEE Access, 2020)

Estimating near term breast cancer risk from sequential mammograms using deep learning, radon cumulative distribution transform, and a clinical risk factor: preliminary analysis. - Juhun Lee; Robert M. Nishikawa; Andriy Bandos; Margarita L. Zuley (Computer-Aided Diagnosis, 2021)

Improving lesion detection algorithm in digital breast tomosynthesis leveraging ensemble cross-validation models with multi-depth levels. - Belayat Hossain; Robert M. Nishikawa; Juhun Lee (Computer-Aided Diagnosis, 2022)

Analyzing GAN artifacts for simulating mammograms: application towards finding mammographically-occult cancer. - Juhun Lee; Robert M. Nishikawa (Computer-Aided Diagnosis, 2022)

Identifying Women With Mammographically- Occult Breast Cancer Leveraging GAN-Simulated Mammograms. - Juhun Lee; Robert M. Nishikawa (IEEE Trans. Medical Imaging, 2022)

Developing a task-oriented deep convolutional neural network application towards estimating near-term breast cancer risk: preliminary work. - Md Belayat Hossain; Juhun Lee (Computer-Aided Diagnosis, 2023)

Developing a breast lesion simulator and remover in mammograms using Cycle-GAN: focusing on its impacts on a computer aided detection algorithm. - Juhun Lee; Robert M. Nishikawa (Computer-Aided Diagnosis, 2023)

Information about immune cell proportions and tumor stage improves the prediction of recurrence in patients with colorectal cancer. - JungHo Kong; Jinho Kim; Donghyo Kim; Kwanghwan Lee; Juhun Lee; Seong Kyu Han; Inhae Kim; Seongsu Lim; Minhyuk Park; Seungho Shin; Woo Yong Lee; Seong Hyeon Yun; et al. (Patterns, 2023)

All but One: Surgical Concept Erasing with Model Preservation in Text-to-Image Diffusion Models. - Seunghoo Hong; Juhun Lee; Simon S. Woo (AAAI, 2024)

Disrupting Diffusion-based Inpainters with Semantic Digression. - Geonho Son; Juhun Lee; Simon S. Woo (IJCAI, 2024)