Open AccessFramework for comprehensive enhancement of brain tumor images with single-window operation
Author(s) -
T. S. Deepthi Murthy,
G. Sadashivappa
Publication year - 2020
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v10i1.pp801-808
Subject(s) - computer science , grayscale , flexibility (engineering) , window (computing) , artificial intelligence , set (abstract data type) , image (mathematics) , inference , computer vision , filter (signal processing) , image processing , pattern recognition (psychology) , statistics , mathematics , programming language , operating system
Usage of grayscale format of radiological images is proportionately more as compared to that of colored one. This format of medical image suffers from all the possibility of improper clinical inference which will lead to error-prone analysis in further usage of such images in disease detection or classification. Therefore, we present a framework that offers single-window operation with a set of image enhancing algorithm meant for further optimizing the visuality of medical images. The framework performs preliminary pre-processing operation followed by implication of linear and non-linear filter and multi-level image enhancement processes. The significant contribution of this study is that it offers a comprehensive mechanism to implement the various enhancement schemes in highly discrete way that offers potential flexibility to physical in order to draw clinical conclusion about the disease being monitored. The proposed system takes the case study of brain tumor to implement to testify the framework.