Biomedical Imaging Physics and Instrumentation Laboratory
Research Field
Jyh-Cheng Chen received the BS degree in physics from National Central University, Taiwan, in 1983, and the MS degree in physics and PhD degree in optical sciences from the University of Arizona, USA in 1988 and 1995, respectively. In 1995, he joined the Opto-Electronics and System Laboratories, Industrial Technology Research Institute, Taiwan, as a research associate working on semiconductor laser packaging. In 1996, he became a member of the faculty of Division of Radiological Science and Technology, Department of Medical Technology, National Yang-Ming University (NYMU), Taiwan. In 1998, he became an associate professor of Institute of Radiological Sciences, NYMU, Taiwan. Since 2005, he has been a professor in the Department of Biomedical Imaging and Radiological Sciences (BIRS), NYMU, Taiwan, teaching and pursuing his research in areas of molecular imaging physics and instrumentation. During 2012-2015, He had been the Chairman of the Department of BIRS, NYMU, Taiwan. Since 2017, he has been a distinguished professor of Department of BIRS, NYMU. His research interests include image processing, analysis, reconstruction, radiomics, AI. He is using microPET/SPECT/CT to do image reconstruction, processing, and analysis for animal molecular imaging studies. He has also designed homemade microCT, FMT/CT, XLCT, and PET/CT animal imaging systems. He has published over 100 peer-reviewed journal papers, a number of book chapters and owns several patents. He received NYMU Teacher’s Academic Excellence Award, and a few other research awards including Taiwan Innovation Award in 2019 & 2023. He is a member of IEEE, SNMMI, and FASMI. He serves on the editorial board of International Journal of Biomedical Imaging, guest editors of special issues in Computerized Medical Imaging and Graphic and Electronics and reviewer for more than 15 SCI journals. He has served in the program committees of several international conferences. He served as the editor-in-chief of ANMMI.
Our lab has been conducting the research on the AI image processing/analysis, optimization techniques, and the algorithms for cone-beam CT (CBCT) reconstruction. In addition, we also do software development, hardware design, and incorporate our research work into commercialized CBCT systems.
For easy access to our research, some of our work (e.g. AI model training for fast CT imaging) will be deployed as web service in the future.
Tumor Detection In Clinical Applications
Prototyping of the Biomedical Imaging Systems
Objective Image Quality Assessment
Image Processing and Analysis
Preclinical Molecular Imaging
Advanced Image analysis and Radiomics
AI Based Algorithm Development
TAF-3871 Approved Laboratory
Certificates of the National Innovation Award, 2019 and 2023.
National Yang-Ming University’s teacher’s academic excellence award, 2007-2023.
Best paper award at 2010 International Workshop on Image Analysis, Aug. 2010, France
Listed in “Who’s Who in the World, 23rd Edition and 24th Edition”, A Marquis who’s who Publication, 2006, p 435 and 2007, USA
First place in Scientific Exhibits, “A Stationary 3D SPECT Brain Imaging System,” at the Society of Nuclear Medicine Annual Meeting, June 1991.
He received the BS degree in physics from National Central University, Taiwan, in 1983, and the MS degree in physics and PhD degree in optical sciences from the University of Arizona, USA in 1988 and 1995, respectively.
2 Vacancies
Job Description
We are seeking a motivated and enthusiastic student to join our team as a deep-learning (DL) intern, focusing on PET image processing with a particular emphasis on attenuation correction (AC). In this role, you will have the opportunity to work alongside experienced researchers to contribute to the implementation of DL networks to improve the accuracy and quality of PET images.
Responsibilities:
- Assist in the design and implementation of a DL network for PET image attenuation correction, under the guidance of senior researchers.
- Contribute to the development and optimization of deep learning models for converting non-attenuation-corrected PET images (NAC PET) into attenuation-corrected PET images (AC PET).
- Learn and apply programming skills in Python and relevant deep learning frameworks (e.g., TensorFlow, PyTorch) to support model implementation and testing.
- Participate in team meetings, discussions, and knowledge-sharing sessions to enhance your understanding of PET imaging technology and deep learning techniques.
Preferred Intern Education Level
Undergraduate students, Master students, and Ph.D students.
Skill sets or Qualities
Background knowledge should be in any of the following fields, such as deep learning techniques, programming (such as Python, and Matlab), Medical imaging, Medical Devices, and Nuclear medicine.
2 Vacancies
Job Description
We are looking for a highly skilled deep learning (DL) specialist with expertise in CT-based image reconstruction to join our team. In this role, you will be responsible for dataset generation, DL model development, CT image reconstruction, and performing quantitative analysis.
Responsibilities:
- Assist in the development and implementation of the DL model for CT image reconstruction.
- Generate datasets using Monte Carlo GATE simulation and conduct real experiments utilizing a CT scanner.
- Perform both conventional and iterative CT image reconstruction.
- Calculate quantitative values in DL output images and analyze features using Radiomic.
- Actively participate in team meetings, discussions, and knowledge-sharing sessions.
Preferred Intern Education Level
Undergraduate students, Master students, and Ph.D. students.
Skill sets or Qualities
Background knowledge should be in any of the following fields, such as deep learning techniques, programming (such as Python, and Matlab), Medical Imaging, Medical Devices, and Nuclear medicine.