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Current Medical Imaging

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ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

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General Research Article

A Cross Sectional Study of Tumors Using Bio-Medical Imaging Modalities

Author(s): Mashal Tariq, Ayesha A. Siddiqi*, Ghous Baksh Narejo and Shehla Andleeb

Volume 15, Issue 1, 2019

Page: [66 - 73] Pages: 8

DOI: 10.2174/1573405613666170614081434

Price: $65

Abstract

Background: Digital Signal Processing (D.S.P) is an evolutionary field. It has a vast variety of applications in all fields. Bio medical engineering has various applications of digital signal processing. Digital Image Processing is one of the branches of signal processing. Medical image modalities proved to be helpful for disease diagnosis. Higher expertise is required in image analysis by medical professional, either doctors or radiologists.

Methods: Extensive research is being done and has produced remarkable results. The study is divided into three main parts. The first deals with introduction of mostly used imaging modalities such as, magnetic resonance imaging, x-rays, ultrasound, positron emission tomography and computed tomography. The next section includes explanation of the basic steps of digital image processing are also explained in the paper. Magnetic Resonance imaging modalities is selected for this research paper. Different methods are tested on MRI images.

Discussion: Brain images are selected with and without tumor. Solid cum Cystic tumor is opted for the r esearch. Results are discussed and shown. The software used for digital image processing is MATLAB. It has in built functions which are used throughout the study. The study represents the importance of DIP for tumor segmentation and detection.

Conclusion: This study provides an initial guideline for researchers from both fields, that is, medicine and engineering. The analyses are shown and discussed in detail through images. This paper shows the significance of image processing platform for tumor detection automation.

Keywords: Brain, Image processing, digital imaging techniques, MRI, cancer, tumor.

Graphical Abstract

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