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What is Low-Level Image Features

Handbook of Research on Hybrid Learning Models: Advanced Tools, Technologies, and Applications
Primitive features characterizing image content, such as color, texture, and shape that are automated extracted from images and used in content-based visual query
Published in Chapter:
Medical Hybrid Learning Tools
Liana Stanescu (University of Craiova, Romania) and Dumitru Dan Burdescu (University of Craiova, Romania)
DOI: 10.4018/978-1-60566-380-7.ch022
Abstract
This chapter describes original modalities of combining traditional methods and technologies in medical learning with good results. The electronic tool is TESYS, a non-commercial e-learning platform designed for completing and improving traditional medical learning by using new methods. Traditional learning is thus blended together with e-learning, offering the students and teachers the possibility to permanently evaluate the learning and teaching process. Besides the usual functions of an e-learning platform, TESYS includes elements of originality. The first one is a database with medical images collected during the process of diagnosing patients, which also include other useful information (diagnostic, treatment, evolution) in order to complete the currently limited number of images found in university courses and medical books. The second element of originality is the content-based visual query module designed for this multimedia medical database, which uses features that are automatically extracted from images (color, texture, regions). The content-based visual query used both in the e-learning and e-testing process stimulates learning by comparing similar cases along with their particularities, or by comparing cases that are visually similar but with different diagnosis.
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