Automatic Quality Enhancement of Medical Diagnostic Scans with Deep Neural Image Super-Resolution Models

K. Karthik, S. Sowmya Kamath, Surendra U. Kamath

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

Abstract

In modern healthcare, diagnostic imaging is an essential component for diagnosing ailments and delivering quality healthcare. Given the variety in medical scanning techniques, a recurring issue across different modalities is that the scan quality is often affected by artifacts introduced by hardware and software faults in the imaging equipment. Significant challenges in the 3D Imaging Techniques include low quality/low-resolution scan images or the addition of unwanted artifacts due to patient movement. Researchers have put forth solutions ranging from machine learning algorithms like Gradient Descent to more complex Deep CNN models for rectifying these faults. In this paper, we aim to benchmark deep learning models for improving the quality of diagnostic images, through Super-resolution, for enabling faster and easier detection of anomalies that may be missed otherwise. Super-resolution CNN and Deep CNN architectures were employed for up-sampling medical scans for enhancing their quality. The CNN models were trained to learn motion artifact characteristics that are a result of patient movement and negate its effects in the super-resolved output. We present comparative results of six super-resolution models on a standard dataset and metrics. During the experimental evaluation, it was observed that the ResNet SRCNN model outperformed all other models used for comparison by a large margin, with an improvement of 4.87 to 8.68% over the other state-of-the-art models.

Original languageEnglish
Title of host publication2020 IEEE 15th International Conference on Industrial and Information Systems, ICIIS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages162-167
Number of pages6
ISBN (Electronic)9781728185248
DOIs
Publication statusPublished - 26-11-2020
Event15th IEEE International Conference on Industrial and Information Systems, ICIIS 2020 - Rupnagar, Punjab, India
Duration: 26-11-202028-11-2020

Publication series

Name2020 IEEE 15th International Conference on Industrial and Information Systems, ICIIS 2020 - Proceedings

Conference

Conference15th IEEE International Conference on Industrial and Information Systems, ICIIS 2020
CountryIndia
CityRupnagar, Punjab
Period26-11-2028-11-20

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence
  • Information Systems
  • Information Systems and Management
  • Renewable Energy, Sustainability and the Environment

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