@article{1481319,
      note = {Includes author index.},
      author = {Greenspan, Hayit, and Madabhushi, Anant, and Mousavi,  Parvin, and Salcudean, Septimiu Edmund, and Duncan, James,  and Syeda-Mahmood, Tanveer, and Taylor, Russell,},
      url = {http://library.usi.edu/record/1481319},
      title = {Medical image computing and computer assisted intervention  -- MICCAI 2023 : 26th International Conference, Vancouver,  BC, Canada, October 8-12, 2023, Proceedings., Part IV /.  International Conference on Medical Image Computing and  Computer-Assisted Intervention},
      abstract = {The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224,  14225, 14226, 14227, 14228, and 14229 constitutes the  refereed proceedings of the 26th International Conference  on Medical Image Computing and Computer-Assisted  Intervention, MICCAI 2023, which was held in Vancouver,  Canada, in October 2023. The 730 revised full papers  presented were carefully reviewed and selected from a total  of 2250 submissions. The papers are organized in the  following topical sections: Part I: Machine learning with  limited supervision and machine learning - transfer  learning; Part II: Machine learning -- learning strategies;  machine learning -- explainability, bias, and uncertainty;  Part III: Machine learning -- explainability, bias and  uncertainty; image segmentation; Part IV: Image  segmentation; Part V: Computer-aided diagnosis; Part VI:  Computer-aided diagnosis; computational pathology; Part  VII: Clinical applications -- abdomen; clinical  applications -- breast; clinical applications -- cardiac;  clinical applications -- dermatology; clinical applications  -- fetal imaging; clinical applications -- lung; clinical  applications -- musculoskeletal; clinical applications --  oncology; clinical applications -- ophthalmology; clinical  applications -- vascular; Part VIII: Clinical applications  -- neuroimaging; microscopy; Part IX: Image-guided  intervention, surgical planning, and data science; Part X:  Image reconstruction and image registration.},
      doi = {https://doi.org/10.1007/978-3-031-43901-8},
      recid = {1481319},
      pages = {1 online resource (xxxviii, 801 pages) :},
}