Medical Image Synthesis using Computer Vision Techniques
Rahil Sarvaiya1, Chirag Patel2, Karthik Shetty3, Somil Shah4, Pankaj Sonawane5
1Rahil Sarvaiya*, Student, Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India.
2Chirag Patel, Student, Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India.
3Karthik Shetty, Student, Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India.
4Somil Shah, Student, Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India.
5Pankaj Sonawane, Assistant Professor, Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 16-20 | Volume-9 Issue-3, January 2020. | Retrieval Number: B6847129219/2020©BEIESP | DOI: 10.35940/ijitee.B6847.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Magnetic Resonance Imaging (MRI) is a type of scan that produces comprehensive images of the inside of the body using a steady magnetic field and radio waves. On the other hand, Computed Tomography (CT) scans, is a combination of a series of X-ray images, which are a type of radiation called ionizing radiation. It can be harmful to the DNA in your cells and also increase the chances that they’ll turn cancerous. MRI is a safer option compared to CT and does not involve any radiation exposure. In this paper, we propose the use of Generative Adversarial Networks (GANs) to translate MRI images into equivalent CT images. We compare it with past techniques of MRI to CT scan conversion and elaborate on why GANs produce more realistic CT images while modeling the nonlinear relationship from MRI to CT.
Keywords: MRI, CT, GANs, CNNs, FCN, Segmentation Based Method, Atlas Based Methods.
Scope of the Article: Computer Science and Its applications