Adaptive non-local means filtering based on local noise level for CT denoising

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

8 Citations (Scopus)

Abstract

Radiation dose from CT scans is an increasing health concern in the practice of radiology. Higher dose scans can produce clearer images with high diagnostic quality, but may increase the potential risk of radiation-induced cancer or other side effects. Lowering radiation dose alone generally produces a noisier image and may degrade diagnostic performance. Recently, CT dose reduction based on non-local means (NLM) filtering for noise reduction has yielded promising results. However, traditional NLM denoising operates under the assumption that image noise is spatially uniform noise, while in CT images the noise level varies significantly within and across slices. Therefore, applying NLM filtering to CT data using a global filtering strength cannot achieve optimal denoising performance. In this work, we have developed a technique for efficiently estimating the local noise level for CT images, and have modified the NLM algorithm to adapt to local variations in noise level. The local noise level estimation technique matches the true noise distribution determined from multiple repetitive scans of a phantom object very well. The modified NLM algorithm provides more effective denoising of CT data throughout a volume, and may allow significant lowering of radiation dose. Both the noise map calculation and the adaptive NLM filtering can be performed in times that allow integration with the clinical workflow.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume8313
DOIs
StatePublished - 2012
EventMedical Imaging 2012: Physics of Medical Imaging - San Diego, CA, United States
Duration: Feb 5 2012Feb 8 2012

Other

OtherMedical Imaging 2012: Physics of Medical Imaging
CountryUnited States
CitySan Diego, CA
Period2/5/122/8/12

Fingerprint

Noise
Dosimetry
dosage
Radiology
Radiation
Computerized tomography
radiation
Noise abatement
Radiation-Induced Neoplasms
Health
Workflow
radiology
noise reduction
health
estimating
cancer

Keywords

  • CT dose reduction
  • Image denoising
  • local noise level
  • noise estimation
  • non-local means filtering
  • radiation dose reduction
  • spatial filtering

ASJC Scopus subject areas

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

Cite this

Adaptive non-local means filtering based on local noise level for CT denoising. / Li, Zhoubo; Yu, Lifeng; Trazasko, Joshua D; Fletcher, Joel Garland; McCollough, Cynthia H; Manduca, Armando.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 8313 2012. 83131H.

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

Li, Z, Yu, L, Trazasko, JD, Fletcher, JG, McCollough, CH & Manduca, A 2012, Adaptive non-local means filtering based on local noise level for CT denoising. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 8313, 83131H, Medical Imaging 2012: Physics of Medical Imaging, San Diego, CA, United States, 2/5/12. https://doi.org/10.1117/12.913353
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