معرفی
Chunliang Wang is a researcher with Docent title at the School of Technology and Health (STH), KTH Royal Institute of Technology, Sweden. His primary affiliation is with the Division of Biomedical Imaging at Hälsovägen 11C, Stockholm. He serves as course responsible for Deep Learning Methods for Medical Image Analysis (CM2003) and Medical Engineering, Basic Course (HL1007), while also teaching 3D Image Reconstruction and Analysis in Medicine (HL2027) and Degree Projects in Medical Engineering.
His educational background includes medical training at Tianjin Medical University (1998-2005) and a PhD in Medical Science from Linköping University (2011). Prior to his academic career, he worked as a software engineer at Sectra AB in Linköping (2011-2015).
Wang's research focuses on medical image analysis, specializing in image segmentation, deep learning, and statistical shape modeling. His work bridges clinical applications with computational methods, particularly in cardiovascular and neurological imaging. As the key contributor to MiaLab software (mialab.org), he develops practical tools for medical image processing.
His publication portfolio spans 21 journal articles and 18 conference papers since 2007, with recent work emphasizing deep learning applications in multi-organ segmentation, coronary artery analysis, and neurological imaging. The 15 most recent publications demonstrate consistent focus on algorithm development for clinical image interpretation, particularly in segmentation challenges across multiple anatomical systems.
Wang has developed significant research software including MiaLab (since 2011), CMIV CTA plug-in for OsiriX, MeVisHub, and MiaLite. His patented work on level-set based image processing (2013) demonstrates translational impact. While no formal awards are listed, his leadership in multiple MICCAI challenges and VISCERAL benchmarks highlights community recognition.
