Knowledge Acquisition and Learning in Semantic Interpretation of Medical Image Structures(KALSIMIS 2017)

February  21-23, 2017

Portugal

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 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.

Topics

• Active contours and their generalizations
• Image decomposition
• Structured prediction
• Probabilistic graphical models
• Convolutional neural networks

Important Dates

• Paper submission: December 06, 2016
• Notification of acceptance: December 21, 2016
• Final manuscripts due: December 29, 2016

User Name : Claude
Posted 14-10-2016 on 09:37:35 AEDT

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