Yi Wang joined the School of Biomedical Engineering, Medical School at Shenzhen University in June 2017. He received his Ph.D. degree in Computer Science and Engineering from The Chinese University of Hong Kong (CUHK), under the supervision by Prof. Pheng-Ann Heng.

Yi Wang’s research interests mainly focus on Intelligent Computing Assisted Diagnosis and Interventions (especially in medical image registration, multi-modality prostate image analysis, computer-aided breast cancer diagnosis, and intelligent orthopedics). Dr. Wang has published several papers in the IEEE Transactions on Medical Imaging (TMI), IEEE Transactions on Image Processing (TIP), IEEE Transactions on Cybernetics (TCYB), International Conference on Computer Vision (ICCV), International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), and so on. Dr. Wang keeps good relationship with clinic and various research groups, and values practical techniques that can be transferred to clinically applicable systems.

News

06/2024: Our collaborative study with Prof. Jianhua Zhou (Department of Ultrasound, Sun Yat-sen University Cancer Center) is accepted by MICCAI2024. “Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound”, [code].

05/2024: Our collaborative study with Prof. Ming Xu and Prof. Xiaoyan Xie (Department of Medical Ultrasound, The First Affiliated Hospital, SYSU) is accepted by UMB. “Development and Validation of an Explainable Machine Learning Model for Identification of Hyperfunctioning Parathyroid Glands from High-Frequency Ultrasonographic Images”.

05/2024: Our paper on 2D for 3D Segmentation is accepted by Expert Systems with Applications. Congrats to Zhuoyuan. “Contextual Embedding Learning to Enhance 2D Networks for Volumetric Image Segmentation”, [code].

05/2024: Our paper on Breast Cancer Diagnosis in DCE-MRI is accepted by CBMS2024. Congrats to Zixian. “Exploring Kinetic Curves Features for the Classification of Benign and Malignant Breast Lesions in DCE-MRI”, [code].

04/2024: Our paper on Fractured Bone Segmentation is accepted by EMBC2024. Congrats to Yu Zhou. “Towards Cross-Scale Attention and Surface Supervision for Fractured Bone Segmentation in CT”, [code].

03/2024: Our paper on Multi-organ Segmentation in CT is accepted by Expert Systems with Applications. Congrats to Zefan. “Recurrent Feature Propagation and Edge Skip-Connections for Automatic Abdominal Organ Segmentation”, [code].

02/2024: Our paper on Deformable Image Registration without Pre-alignment is accepted by IEEE TMI. Congrats to Haiqiao. “Recursive Deformable Pyramid Network for Unsupervised Medical Image Registration”, [code].

02/2024: Our paper on Diagnosis of Clinically Significant Prostate Cancer (csPCa) is accepted by ISBI2024. Congrats to Hong Wu. “Multi-Modality Transrectal Ultrasound Video Classification for Identification of Clinically Significant Prostate Cancer”, [code].

02/2024: Our paper on Medical Image Registration is accepted by ISBI2024. Congrats to Zhuoyuan and Haiqiao. “Pyramid Attention Network for Medical Image Registration”, [code].

01/2024: Our collaborative study with Prof. Zida Li is accepted by PNAS. “StratoLAMP: Label-free, multiplex digital loop-mediated isothermal amplification based on visual stratification of precipitate”.

11/2023: Our “Guangdong-Hong Kong Joint Funding for Technology and Innovation” project named “Research and Development of Intelligent Preoperative Planning System for Tibial Plateau Fractures”, collaborated with Prof. Pheng-Ann Heng, has been successfully funded. Cheer!

10/2023: Dr. Wang has been selected as the “World’s Top 2% Scientists” (2022).

10/2023: We present our Motion Decomposition Transformer (ModeT) at MICCAI Learn2Reg 2023 as a spotlight talk.

10/2023: Our paper on Scribble-supervised Medical Image Segmentation is accepted by Expert Systems with Applications. Congrats to Zefan. “Non-Iterative Scribble-Supervised Learning with Pacing Pseudo-Masks for Medical Image Segmentation”, [code].

06/2023: Our paper on Point-supervised Medical Image Segmentation is accepted by MICCAI2023. Congrats to Yuming. “SimPLe: Similarity-Aware Propagation Learning for Weakly-Supervised Breast Cancer Segmentation in DCE-MRI”, [code].

05/2023: Our paper on Medical Image Registration is early accepted by MICCAI2023. Congrats to Haiqiao. “ModeT: Learning Deformable Image Registration via Motion Decomposition Transformer”, [code].

Contact

Email: onewang@szu.edu.cn, wilson.near@gmail.com

Mail Addr: Rm 510, A2 Biomedical Engineering Building, Shenzhen University (Lihu Campus), Shenzhen, Guangdong, China