WQ-L.C2.4

DEEP LEARNING MEETS RADIOMICS FOR END-TO-END BRAIN TUMOR MRI ANALYSIS

Wojciech Ponikiewski, Jakub Nalepa, Silesian University of Technology, Poland
Session:
Biomedical Image Segmentation
Lecture
Track:
Applications of Machine Learning
Location:
Room C2
Presentation Time:
Wed, 19 Oct, 20:45 - 21:00 China Standard Time (UTC +8)
Wed, 19 Oct, 14:45 - 15:00 Central European Time (UTC +1)
Wed, 19 Oct, 12:45 - 13:00 UTC
Wed, 19 Oct, 08:45 - 09:00 Eastern Time (UTC -5)
Session Chair:
Jean-Christophe Olivo-Marin, Institut Pasteur
Presentation
Discussion
Resources
No resources available.
Session WQ-L.C2
WQ-L.C2.1: ACT-Net: Asymmetric Co-Teacher Network for Semi-supervised Memory-efficient Medical Image Segmentation
Ziyuan Zhao, Zeng Zeng, I2R, A*STAR, Singapore; Andong Zhu, Bharadwaj Veeravalli, National University of Singapore, Singapore; Cuntai Guan, Nanyang Technological University, Singapore
WQ-L.C2.2: COMPUTATIONALLY-EFFICIENT VISION TRANSFORMER FOR MEDICAL IMAGE SEMANTIC SEGMENTATION VIA DUAL PSEUDO-LABEL SUPERVISION
Ziyang Wang, Nanqing Dong, Irina Voiculescu, University of Oxford, United Kingdom of Great Britain and Northern Ireland
WQ-L.C2.3: JOINT MOTION CORRECTION AND 3D SEGMENTATION WITH GRAPH-ASSISTED NEURAL NETWORKS FOR RETINAL OCT
Yiqian Wang, Carlo Galang, William Freeman, Truong Nguyen, Cheolhong An, University of California, San Diego, United States of America
WQ-L.C2.4: DEEP LEARNING MEETS RADIOMICS FOR END-TO-END BRAIN TUMOR MRI ANALYSIS
Wojciech Ponikiewski, Jakub Nalepa, Silesian University of Technology, Poland
WQ-L.C2.5: ROBUST 3D CELL SEGMENTATION: EXTENDING THE VIEW OF CELLPOSE
Dennis Eschweiler, Johannes Stegmaier, Rheinisch-Westfälische Technische Hochschule Aachen, Germany; Richard Smith, Norwich Research Park, United Kingdom of Great Britain and Northern Ireland
WQ-L.C2.6: AN UNSUPERVISED PARAMETER-FREE NUCLEI SEGMENTATION METHOD FOR HISTOLOGY IMAGES
Vasileios Magoulianitis, Peida Han, Yijing Yang, C.-C. Jay Kuo, University of Southern California, United States of America