Repository logo
Communities & Collections
All of DSpace
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Kandala, R.N.V.P.S."

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • No Thumbnail Available
    Item
    Analyzing data incompleteness for MRI Data for quality enhancement
    (Institute of Electrical and Electronics Engineers Inc., 2024) Shanbhag, S.; Raju, S.; Gurupur, V.P.; Kamath, S.S.; Kandala, R.N.V.P.S.; Trader, A.E.; Lal, S.
    Magnetic resonance imaging (MRI) is a powerful medical imaging technique widely used for diagnosing various conditions because it provides detailed images of internal structures within the body. However, like any imaging modality, MRI images can be susceptible to artifacts that may arise from various sources, including hardware imperfections, patient motion, and image acquisition techniques. Detecting and mitigating these artifacts are crucial steps in ensuring MRI scans' reliability and clinical utility. In this paper, we present algorithms specifically designed to address the challenges of undersampling and motion artifacts in MR images. Our approach involves leveraging advanced image processing techniques, including line detection algorithms for undersampling detection and blur parameter estimation for motion artifact analysis. By accurately identifying and quantifying these artifacts, our algorithms aim to improve MRI data's overall quality and completeness, ultimately enhancing diagnostic accuracy and patient care. © 2024 The Authors.

Maintained by Central Library NITK | DSpace software copyright © 2002-2026 LYRASIS

  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify