Abstract

Medical image processing covers various types of images such as tomography, mammography, radiography (X-Ray images), cardiogram, CT scan images etc. Once the CT scan image is captured, Doctors diagnose it to detect abnormal or normal condition of the captured of the patient’s body. In the computerized image processing diagnosis, CT-scan image goes through sophisticated phases viz., acquisition, image enhancement, extraction of important features, Region of Interest (ROI) identification, result interpretation etc. Out of these phases, a feature extraction phase plays a vital role during automated/computerized image processing to detect ROI from CT-scan image. This phase performs scientific, mathematical and statistical operations/algorithms to identify features/characteristics from the CT-scan image to shrink image portion for diagnosis. In this chapter, I have presented an extensive review on “Feature Extraction” step of digital image processing based on CT-scan image of human being.

Highlights

  • IntroductionComputer Aided Diseases Diagnoses (CADD) plays an important role

  • In recent medical revolution, Computer Aided Diseases Diagnoses (CADD) plays an important role

  • There are many bio-medical imaging technologies available such as Radiography, computed tomography (CT-Scan), electrocardiography (ECG), Ultrasound, magnetic resonance imaging (MRI), etc. All these medical imaging modalities are best suited depending on the type of diseases to be detected from human body [1, 2]

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Summary

Introduction

Computer Aided Diseases Diagnoses (CADD) plays an important role. There are many bio-medical imaging technologies available such as Radiography, computed tomography (CT-Scan), electrocardiography (ECG), Ultrasound, magnetic resonance imaging (MRI), etc. All these medical imaging modalities are best suited depending on the type of diseases to be detected from human body [1, 2]. The step is Color Image Processing which deals with feature extraction on the basis of image color. Morphological processing step includes tools for extracting image components that are useful in the step that is representation and description of image shape. The aim of this chapter is to present an extensive research review on feature extraction sub-step of image processing cycle applied to human CT-scan images.

Feature extraction techniques
CT-scan image feature extraction
Findings
Conclusion and future attempts
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