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Special Sessions

Special sessions are very small and specialized events to be held during the conference as a set of oral and poster presentations that are highly specialized in some particular theme or consisting of the works of some particular international project. The goal of special sessions (minimum 4 papers; maximum 9) is to provide a focused discussion on innovative topics. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on CD-ROM support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), INSPEC, DBLP, EI (Elsevier Engineering Village Index) and Scopus.


Special session proposals are accepted until:

August 31, 2017


If you wish to propose a new Special Session please kindly fill out and submit this Expression of Interest form.

SPECIAL SESSIONS LIST

KALSIMIS 2018Special Session on Knowledge Acquisition and Learning in Semantic Interpretation of Medical Image Structures
Chair(s): Piotr Szczepaniak, Piotr Grzelak and Arkadiusz Tomczyk

Special Session on Knowledge Acquisition and Learning in Semantic Interpretation of Medical Image Structures - KALSIMIS 2018

Paper Submission: November 7, 2017
Authors Notification: November 21, 2017
Camera Ready and Registration: November 29, 2017


Co-chairs

Piotr Szczepaniak
Lodz University of Technology
Poland
e-mail
 
Piotr Grzelak
Department of Radiology and Imagining Diagnostic, Polish Mother’s Memorial Hospital - Research Institute
Poland
e-mail
 
Arkadiusz Tomczyk
Lodz University of Technology
Poland
e-mail
 
Scope

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.



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