BISP-P16: Medical image reconstruction and Brain Computer Interfaces
Poster
Wed, 6 May, 16:30 - 18:30
Location: Poster Area 11
Session Type: Poster
Track: Biomedical Signal and Image Processing [BI]
Click the to view the manuscript on IEEE Xplore Open Preview

BISP-P16.1: A Robust Multi-Scale Framework with Test-Time Adaptation for sEEG-Based Speech Decoding

Yang-yang Li, Suli Wang, The Chinese University of Hong Kong, Shenzhen, China; Siqi Cai, Harbin Institute of Technology, Shenzhen, China

BISP-P16.3: INTERPRETING VISUAL CORTEX VIA DEEP NEURAL NETWORK NEURON EXPLANATION

Qiaolu Zhu, Changde Du, Huiguang He, Institute of Automation, Chinese Academy of Sciences, China

BISP-P16.4: DENSE RGB-D SLAM FOR ENDOSCOPIC SURGERY VIA QUADRATIC GAUSSIAN SPLATTING, ENDOQS-SLAM

Yang Zuhao, Liu Jie, Ding Xin, Nanchang University, China; Wei Weifeng, Central South University, China; Su Pengxiang, Nanchang University, China; He Congqing, Huzhou University, China

BISP-P16.6: CBR: A CARDINAL B-SPLINE REPRESENTATION FOR SPARSE-VIEW CT RECONSTRUCTION

Yueyi Zhang, Wei Chen, Gaoqiang Zhang, Jiangnan University, China

BISP-P16.7: PRISMOID-BASED SELF-ATTENTION NEURAL REPRESENTATION METHOD FOR LOW-DOSE TOMOGRAPHIC RECONSTRUCTION

Weiguo Zhang, Weifan Fang, Guoheng Huang, Yuanyuan Liu, Si Li, Guangdong University of Technology, China; Chi-Man Pun, University of Macau, Macao

BISP-P16.8: STAINPIDR: A STAIN NORMALIZATION METHOD FOR PATHOLOGICAL IMAGES VIA DECOUPLING AND COLOR CODEBOOK-BASED RECONSTRUCTION

Zheng Chen, Juan Liu, Ruizheng Zhang, Wuhan University, China; Cheng Li, Dehua Cao, Landing Artificial Intelligence Center for Pathological Diagnosis, China; Yi Zhang, Wenhua College, China

BISP-P16.9: ENDO-G2T: GEOMETRY-GUIDED & TEMPORALLY AWARE TIME-EMBEDDED 4DGS FOR ENDOSCOPIC SCENES

Yangle Liu, University of Liverpool, United Kingdom of Great Britain and Northern Ireland; Fengze Li, Kan Liu, University of Liverpool, Xi'an Jiaotong-Liverpool University, China; Jieming Ma, Xi'an Jiaotong-Liverpool University, China

BISP-P16.10: SwinCBAM-Net: Swin-transformer-enhanced Convolutional Block Attention Module-based Image Refinement Network for CBCT-guided radiotherapy

Kai Chen, Shipeng Xie, Nanjing University of Posts and Telecommunications, China; Biao Cheng, Aerosun Corporation, China; Yang Chen, Southeast University, China