Personalized CT organ noise estimation from scout images

Abdullah Al Zubaer Imran, Debashish Pal, Sen Wang, Sandeep Dutta, Evan Zucker, Adam Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Considering the potential radiation effect on patients in computed tomography (CT) imaging, it is desirable to reduce the radiation dose. Reduction in dose incurs degradation in image quality and possible reduced diagnostic performance. CT image quality needs to be maintained at standards sufficient for effective clinical reading. Therefore, the dose reduction should be guided by the potential image quality. Unfortunately, currently available CT image quality assessment (IQA) tools are based on maintaining a uniform image quality or use the CT exams themselves to retrospectively determine image quality. A robust and comprehensive IQA metric should represent the image quality of each patient at the organ level, and before the CT exams. Towards this objective, we devise a fully-automated, end-to-end deep learning-based solution to perform real-time, patient-specific, organ-level image quality prediction of CT scans. Leveraging the 2D scout (frontal and lateral) images of the actual patients, which are routinely acquired prior to the CT scan, our proposed Scout-IQA model estimates the patient-specific mean noise in real-time for six different organs. Our experimental evaluation on real patient data demonstrates the effectiveness of our Scout model not only in real-time noise estimation (only 6 ms on average per scan), but also as a potential tool for optimizing CT radiation dose in individual patients.

Original languageEnglish
Title of host publicationMedical Imaging 2022
Subtitle of host publicationPhysics of Medical Imaging
EditorsWei Zhao, Lifeng Yu
ISBN (Electronic)9781510649378
DOIs
StatePublished - 2022
EventMedical Imaging 2022: Physics of Medical Imaging - Virtual, Online
Duration: Mar 21 2022Mar 27 2022

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume12031
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2022: Physics of Medical Imaging
CityVirtual, Online
Period3/21/223/27/22

Bibliographical note

Publisher Copyright:
© 2022 SPIE.

Keywords

  • Computed Tomography
  • Deep learning
  • Image quality assessment
  • Organ noise
  • Scout images

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

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