Title:Data Tagging in Medical Images: A Survey of the State-of-Art
VOLUME: 16 ISSUE: 10
Author(s):Jyotismita Chaki* and Nilanjan Dey
Affiliation:School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Department of Information Technology, Techno India College of Technology, West Bengal
Keywords:Medical image tags, single-label tag, multi-label image tag, content-based tags, context-based tags, ontology-based
tags, semantic-based tags.
Abstract:A huge amount of medical data is generated every second, and a significant percentage
of the data are images that need to be analyzed and processed. One of the key challenges in this regard
is the recovery of the data of medical images. The medical image recovery procedure should
be done automatically by the computers that are the method of identifying object concepts and assigning
homologous tags to them. To discover the hidden concepts in the medical images, the lowlevel
characteristics should be used to achieve high-level concepts and that is a challenging task. In
any specific case, it requires human involvement to determine the significance of the image. To allow
machine-based reasoning on the medical evidence collected, the data must be accompanied by
additional interpretive semantics; a change from a pure data-intensive methodology to a model of
evidence rich in semantics. In this state-of-art, data tagging methods related to medical images are
surveyed which is an important aspect for the recognition of a huge number of medical images. Different
types of tags related to the medical image, prerequisites of medical data tagging, different
techniques to develop medical image tags, different medical image tagging algorithms and different
tools that are used to create the tags are discussed in this paper. The aim of this state-of-art paper
is to produce a summary and a set of guidelines for using the tags for the identification of medical
images and to identify the challenges and future research directions of tagging medical images.
