Synthetic Vertebral Column Fracture Image Generation by Deep Convolution Generative Adversarial Networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the field of medical imaging, the challenging objective is to generate synthetic, realistic images which resembles the original images. The generated synthetic images would enhance the accuracy of the computer-assisted classification, Decision Support System, which aid the doctor in diagnosis of diseases. The Generative Adversarial Networks (GANs), is a method of data augmentation which can be used to generate synthetic realistic looking images, however low quality images are generated. For AI models, it is challenging tasks to do classification using this low quality images. In this work, generation of high quality synthetic medical image using Deep Convolutional Generative Adversarial Networks (DCGANs) is presented. Data augmentation method by DCGANs is illustrated on the limited dataset of CT (Computed Tomography) images of vertebral column fracture. A total of 340 CT scan images were taken for the study, which comprises of complete burst fracture scans of vertebral column. The evaluation of the generated images was done with Visual Turing Test.

Original languageEnglish
Title of host publicationProceedings of CONECCT 2021
Subtitle of host publication7th IEEE International Conference on Electronics, Computing and Communication Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665428491
DOIs
Publication statusPublished - 2021
Event7th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2021 - Bangalore, India
Duration: 09-07-202111-07-2021

Publication series

NameProceedings of CONECCT 2021: 7th IEEE International Conference on Electronics, Computing and Communication Technologies

Conference

Conference7th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2021
Country/TerritoryIndia
CityBangalore
Period09-07-2111-07-21

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Instrumentation
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture

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