Automatic Medical Objects Classification Based on Data Sets and Domain Knowledge

Pardel, Przemyslaw Wiktor; Bazan, Jan G.; Zarychta, Jacek; Bazan-Socha, Stanisława

doi:10.1007/978-3-319-18422-7_37

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2015

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“…Advisers suggest what should be a decision (YES advisers) or suggested what should not be a decision (NO advisers). If any of the advisors suggested otherwise than the classifier (in some sense, the low-level classifier), decision was suspended (see [12]). All the decisions taken by the DKA pause the classifier decision where decisions are different.…”

Section: B Methodsmentioning

confidence: 99%

A two-level classifier for automatic medical objects classification

Pardel

Bazan

Zarychta³

et al. 2015

Annals of Computer Science and Information Systems

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Abstract-The goal of this paper is to describe the approach for automatic identifying human organs from a medical CT images and discuss results of its comparison to different classification methods. The main premise of this approach is the use of data sets together with the relevant domain knowledge. We test our approach on multiple CT images of chest organs (trachea, lungs, bronchus) and demonstrate usefulness and effectiveness of the resulting classifications. The presented approach can be used to assist in solving more complex medical problems.

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Section: B Methodsmentioning

confidence: 99%