Department of Computer Science and Informatics, University of Energy and Natural Resources, Sunyani, Ghana
Research Article
Performance Evaluation of State-of-the-Art Texture Feature Extraction Techniques on Medical Imagery Tasks
Author(s): Samuel Kusi-Duah*, Obed Appiah and Peter Appiahene
Purpose: Interpreting medical images is certainly a complex task which requires extensive knowledge. According to
Computer Aided Diagnosis (CAD) serves as a second opinion that will help radiologists in diagnosis and on the
other hand content based image retrieval uses visual content to help users browse, search and retrieve similar medical
images from a database based on the user’s interest. The competency of the CBMIR system depends on feature
extraction methods. The textural features are very important to determine the content of a medical image. Textural
features provide scenic depth, the spatial distribution of tonal variation, and surface orientation. Therefore, this study
seeks to compare and evaluate some of the hand-crafted texture feature extraction techniques in CBMIR. This is to
help those concerned in enhancing CBIR systems to m.. View more»