Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part VII

• Author(s): Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li,
• Publisher: Springer Nature
• Pages: 779
• ISBN_10: 3031164490
  ISBN_13: 9783031164491
  
• Language: en
• Categories: Computers / Artificial Intelligence / Computer Vision & Pattern Recognition , Technology & Engineering / Electronics / General , Computers / Data Science / General , Computers / User Interfaces , Computers / Artificial Intelligence / General , Computers / Software Development & Engineering / General , Technology & Engineering / Imaging Systems , Computers / General ,

Description:... The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.
The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;

Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;

Part III: Breast imaging; colonoscopy; computer aided diagnosis;

Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;

Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;

Part VI: Image registration; image reconstruction;

Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization;

Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.