See also IPMI-2021-CfP.
- Paper registration: 29 November 2020
- Submission of full papers: 6 December 2020
- Reviews due date: 24 January 2021
- Notification of acceptance: February 2021 (To be announced)
- Camera copy ready: March 2021 (To be announced)
- Conference: 27 June – 2 July 2021
Cutting edge research in the medical imaging field
IPMI’s mission is to facilitate and showcase the latest methodological developments within medical imaging. An “IPMI paper” presents novel methodological developments that solve medical imaging analysis problems. Today, IPMI is widely recognised as a preeminent international forum for presentation of cutting edge research in the medical imaging field including the topics below.
IPMI 2021 is a MICCAI endorsed event.
- Image registration
- Image segmentation
- Image acquisition and reconstruction
- Image fusion and synthesis
- Novel deep learning methods for medical imaging
- Statistics for medical imaging
- Computer-aided detection and diagnosis
- Computational anatomy and physiology
- Visualization and physicalization
- Multimodal image processing and analysis
- Functional and molecular imaging
- Imaging and genomics
- Image guided surgery
- Uncertainty estimation
- Interpretability and explainable algorithms
- Loss functions for medical imaging
- Transfer learning, domain adaptation, data harmonization
- Generative modelling
- Learning with noisy or limited data
- Statistical and mathematical models
- Geometric learning, geometric deep learning, geometric statistics
- Shape modeling and analysis
We plan a strong agenda of scientific presentations that will secure the attendance of outstanding researchers from throughout the world in a pleasant and informal setting conducive to in-depth scientific exchange and lively debate.
Our objective in organizing IPMI 2021 is to continue to nurture and encourage contributions from students and junior faculty with the hope that exchanges between the newer and the more established members of the research community will strengthen the scientific program and the field of biomedical image analysis in general.
Proceedings will be published as a volume in the Springer Lecture Notes Computer Science (LNCS) series. Selected papers will be invited to publish extended versions in a special issue in the new free online journal Machine Learning for Biomedical Imaging (MELBA) – http://melba-journal.org.