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Jaehee Chun

Showing results (21-30 of 31) with videos related to

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Medical Physics|July 17, 2019
MRI super-resolution reconstruction for MRI-guided adaptive radiotherapy using cascaded deep learning: In the presence of limited training data and unknown translation modelJaehee Chun, Hao Zhang, H Michael Gach, et al.
Radiation Oncology (London, England)|February 26, 2021
Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgerySeung Yeun Chung, Jee Suk Chang, Min Seo Choi, et al.
ACS Applied Materials & Interfaces|June 2, 2015
High-Performing Thin-Film Transistors in Large Spherulites of Conjugated Polymer Formed by Epitaxial Growth on Removable Organic Crystalline TemplatesJae Yoon Kim, Da Seul Yang, Jicheol Shin, et al.
Medical Physics|July 17, 2019
Synthetic CT reconstruction using a deep spatial pyramid convolutional framework for MR-only breast radiotherapySven Olberg, Hao Zhang, William R Kennedy, et al.
Radiation Oncology (London, England)|October 15, 2021
Evaluation of deep learning-based autosegmentation in breast cancer radiotherapyHwa Kyung Byun, Jee Suk Chang, Min Seo Choi, et al.
Radiation Oncology (London, England)|April 23, 2022
Synthetic contrast-enhanced computed tomography generation using a deep convolutional neural network for cardiac substructure delineation in breast cancer radiation therapy: a feasibility studyJaehee Chun, Jee Suk Chang, Caleb Oh, et al.
Medical Physics|December 21, 2025
Uncertainty-guided test-time optimization for personalizing segmentation models in longitudinal medical imagingJaehee Chun, Austin Castelo, McKell Woodland, et al.
Medical Image Analysis|January 5, 2025
SegRap2023: A benchmark of organs-at-risk and gross tumor volume Segmentation for Radiotherapy Planning of Nasopharyngeal CarcinomaXiangde Luo, Jia Fu, Yunxin Zhong, et al.
Breast (Edinburgh, Scotland)|December 31, 2023
Corrigendum to 'Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study' [The Breast 73 (2024) 103599]Min Seo Choi, Jee Suk Chang, Kyubo Kim, et al.
Breast (Edinburgh, Scotland)|November 22, 2023
Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional studyMin Seo Choi, Jee Suk Chang, Kyubo Kim, et al.
Pageof 4

Showing results (21-30 of 31) with videos related to

Sort By:
Pageof 4
Medical Physics|July 17, 2019
MRI super-resolution reconstruction for MRI-guided adaptive radiotherapy using cascaded deep learning: In the presence of limited training data and unknown translation modelJaehee Chun, Hao Zhang, H Michael Gach, et al.
Radiation Oncology (London, England)|February 26, 2021
Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgerySeung Yeun Chung, Jee Suk Chang, Min Seo Choi, et al.
ACS Applied Materials & Interfaces|June 2, 2015
High-Performing Thin-Film Transistors in Large Spherulites of Conjugated Polymer Formed by Epitaxial Growth on Removable Organic Crystalline TemplatesJae Yoon Kim, Da Seul Yang, Jicheol Shin, et al.
Medical Physics|July 17, 2019
Synthetic CT reconstruction using a deep spatial pyramid convolutional framework for MR-only breast radiotherapySven Olberg, Hao Zhang, William R Kennedy, et al.
Radiation Oncology (London, England)|October 15, 2021
Evaluation of deep learning-based autosegmentation in breast cancer radiotherapyHwa Kyung Byun, Jee Suk Chang, Min Seo Choi, et al.
Radiation Oncology (London, England)|April 23, 2022
Synthetic contrast-enhanced computed tomography generation using a deep convolutional neural network for cardiac substructure delineation in breast cancer radiation therapy: a feasibility studyJaehee Chun, Jee Suk Chang, Caleb Oh, et al.
Medical Physics|December 21, 2025
Uncertainty-guided test-time optimization for personalizing segmentation models in longitudinal medical imagingJaehee Chun, Austin Castelo, McKell Woodland, et al.
Medical Image Analysis|January 5, 2025
SegRap2023: A benchmark of organs-at-risk and gross tumor volume Segmentation for Radiotherapy Planning of Nasopharyngeal CarcinomaXiangde Luo, Jia Fu, Yunxin Zhong, et al.
Breast (Edinburgh, Scotland)|December 31, 2023
Corrigendum to 'Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study' [The Breast 73 (2024) 103599]Min Seo Choi, Jee Suk Chang, Kyubo Kim, et al.
Breast (Edinburgh, Scotland)|November 22, 2023
Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional studyMin Seo Choi, Jee Suk Chang, Kyubo Kim, et al.
Pageof 4