Sekeun Kim

According to our database, Sekeun Kim authored at least 20 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation.

Cheng Chen, Juzheng Miao, Dufan Wu, Aoxiao Zhong, Zhiling Yan, Sekeun Kim, Jiang Hu, Zhengliang Liu, Lichao Sun, Xiang Li, Tianming Liu, Pheng-Ann Heng, Quanzheng Li

Medical Image Anal., 2024

EchoFM: Foundation Model for Generalizable Echocardiogram Analysis.

Sekeun Kim, Pengfei Jin, Sifan Song, Cheng Chen, Yiwei Li, Hui Ren, Xiang Li, Tianming Liu, Quanzheng Li

CoRR, 2024

Retrieval Instead of Fine-tuning: A Retrieval-based Parameter Ensemble for Zero-shot Learning.

Pengfei Jin, Peng Shu, Sekeun Kim, Qing Xiao, Sifan Song, Cheng Chen, Tianming Liu, Xiang Li, Quanzheng Li

CoRR, 2024

ECHOPulse: ECG controlled echocardio-grams video generation.

Yiwei Li, Sekeun Kim, Zihao Wu, Hanqi Jiang, Yi Pan, Pengfei Jin, Sifan Song, Yucheng Shi, Tianming Liu, Quanzheng Li, Xiang Li

CoRR, 2024

Autonomous Robotic Ultrasound System for Liver Follow-up Diagnosis: Pilot Phantom Study.

Tianpeng Zhang, Sekeun Kim, Jerome Charton, Haitong Ma, Kyungsang Kim, Na Li, Quanzheng Li

CoRR, 2024

Prompt-driven Universal Model for View-Agnostic Echocardiography Analysis.

Sekeun Kim, Hui Ren, Peng Guo, Abder-Rahman Ali, Patrick Zhang, Kyungsang Kim, Xiang Li, Quanzheng Li

CoRR, 2024

Cardiac Magnetic Resonance 2D+T Short- and Long-axis Segmentation via Spatio-temporal SAM Adaptation.

Zhennong Chen, Sekeun Kim, Hui Ren, Quanzheng Li, Xiang Li

CoRR, 2024

Temporal-Spatial Adaptation of Promptable SAM Enhance Accuracy and Generalizability of Cine CMR Segmentation.

Zhennong Chen, Sekeun Kim, Hui Ren, Quanzheng Li, Xiang Li

Proceedings of the Foundation Models for General Medical AI, 2024

2023

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction.

Sekeun Kim, Zhenxiang Jiang, Byron A. Zambrano, Yeonggul Jang, Seungik Baek, Sun K. Yoo, Hyuk-Jae Chang

IEEE Trans. Medical Imaging, 2023

Radiology-Llama2: Best-in-Class Large Language Model for Radiology.

Zhengliang Liu, Yiwei Li, Peng Shu, Aoxiao Zhong, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Jie Luo, Cheng Chen, Sekeun Kim, Jiang Hu, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Tianming Liu, Quanzheng Li, Xiang Li

CoRR, 2023

Radiology-GPT: A Large Language Model for Radiology.

Zhengliang Liu, Aoxiao Zhong, Yiwei Li, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Peng Shu, Cheng Chen, Sekeun Kim, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Xiang Li, Quanzheng Li, Tianming Liu

CoRR, 2023

Tailoring Large Language Models to Radiology: A Preliminary Approach to LLM Adaptation for a Highly Specialized Domain.

Zhengliang Liu, Aoxiao Zhong, Yiwei Li, Longtao Yang, Chao Ju, Zihao Wu, Chong Ma, Peng Shu, Cheng Chen, Sekeun Kim, Haixing Dai, Lin Zhao, Dajiang Zhu, Jun Liu, Wei Liu, Dinggang Shen, Quanzheng Li, Tianming Liu, Xiang Li

Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

Multi-task Learning for Hierarchically-Structured Images: Study on Echocardiogram View Classification.

Jerome Charton, Hui Ren, Sekeun Kim, Carola Maraboto Gonzalez, Jay Khambhati, Justin Cheng, Jeena DeFrancesco, Anam A. Waheed, Sylwia Marciniak, Filipe Moura, Rhanderson Cardoso, Bruno B. Lima, Michael H. Picard, Xiang Li, Quanzheng Li

Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023

2022

Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification.

Jaeik Jeon, Yeonggul Jang, Youngtaek Hong, Hackjoon Shim, Sekeun Kim

CoRR, 2022

Reconnection of fragmented parts of coronary arteries using local geometric features in X-ray angiography images.

Kyunghoon Han, Jaeik Jeon, Yeonggul Jang, Sunghee Jung, Sekeun Kim, Hackjoon Shim, Byunghwan Jeon, Hyuk-Jae Chang

Comput. Biol. Medicine, 2022

2019

A Cascaded Two-step Approach For Segmentation of Thoracic Organs.

Sekeun Kim, Yeonggul Jang, Kyunghoon Han, Hackjoon Shim, Hyuk-Jae Chang

Proceedings of the 2019 Challenge on Segmentation of THoracic Organs at Risk in CT Images, 2019

2018

Fully Automatic Segmentation of Coronary Arteries Based on Deep Neural Network in Intravascular Ultrasound Images.

Sekeun Kim, Yeonggul Jang, Byunghwan Jeon, Youngtaek Hong, Hackjoon Shim, Hyuk-Jae Chang

Proceedings of the Intravascular Imaging and Computer Assisted Stenting - and - Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, 2018

Full Quantification of Left Ventricle Using Deep Multitask Network with Combination of 2D and 3D Convolution on 2D + t Cine MRI.

Yeonggul Jang, Sekeun Kim, Hackjoon Shim, Hyuk-Jae Chang

Proceedings of the Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges, 2018

2017

Automatic Segmentation of LV and RV in Cardiac MRI.

Yeonggul Jang, Yoonmi Hong, Seongmin Ha, Sekeun Kim, Hyuk-Jae Chang

Proceedings of the Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, 2017

Coronary luminal and wall mask prediction using convolutional neural network.

Youngtaek Hong, Yoonmi Hong, Yeonggul Jang, Sekeun Kim, Byunghwan Jeon, Sunghee Jung, Seongmin Ha, Dongjin Han, Hackjoon Shim, Hyuk-Jae Chang

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017