posted by user: arcus || 3582 views || tracked by 9 users: [display]

KALSIMIS 2019 : Knowledge Acquisition and Learning in Semantic Interpretation of Medical Image Structures

FacebookTwitterLinkedInGoogle

Link: http://www.biostec.org/KALSIMIS.aspx
 
When Feb 22, 2019 - Feb 24, 2019
Where Prague, Czech Republic
Submission Deadline Dec 20, 2018
Notification Due Jan 7, 2019
Final Version Due Jan 15, 2019
Categories    image analysis   computer vision   machine learning   medical imaging
 

Call For Papers

Current machine learning techniques are able to achieve spectacular results in automatic understanding of natural images whereas in the area of medical image analysis the progress is not that evident. The problem is medical knowledge essential for proper interpretation of image content. That knowledge, possessed by relatively small number of radiological or biomedical experts, usually cannot be directly expressed using mathematical formulas. This can be overcome by laborious knowledge acquisition or by techniques to some extent imitating expert behaviour. Both approaches are, however, still challenging tasks. That is why the goal of the special session is to discuss the problems in acquisition and utilization of domain knowledge in automatic understanding of semantic image structure.

Both computer scientists as well as radiological and biomedical experts are welcome as participants. The session should constitute a perfect forum to express expectations, suggest solutions and share experience for members of those communities.

The scope of the session contains, but is not limited to, the following topics:
- deep architectures and learning in image analysis (e.g. convolutional neural networks, LSTM networks, etc.);
- expert knowledge acquisition and representation methods (how effectively medical knowledge can be acquired and used in existing models of image analysis);
- classical image segmentation and object localization techniques capable of using domain specific knowledge (e.g. active contours, neural networks, etc.);
- structural image representation and analysis (e.g. image decomposition, structured prediction, probabilistic graphical models).

Related Resources

IJCKG 2021   International Joint Conference on Knowledge Graphs
CVPR 2022   Computer Vision and Pattern Recognition
CFDSP 2022   2022 International Conference on Frontiers of Digital Signal Processing (CFDSP 2022)
KiTS 2021   The 2021 MICCAI Kidney Tumor Segmentation Challenge
JCRAI 2021-Ei Compendex & Scopus 2021   2021 International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2021)
MLDM 2022   18th International Conference on Machine Learning and Data Mining
FAIML 2022   2022 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2022)
CMCA 2022   11th International Conference on Control, Modelling, Computing and Applications
CAIML 2022   3rd International Conference on Artificial Intelligence and Machine Learning
PAKDD 2022   The 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2022)