Ultrasound perfusion signal processing for tumor detection

Minwoo Kim, Craig K. Abbey, Michael Insana

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


Enhanced blood perfusion in a tissue mass is an indication of neo-vascularity and a sign of a potential malignancy. Ultrasonic pulsed-Doppler imaging is a preferred modality for noninvasive monitoring of blood flow. However, the weak blood echoes and disorganized slow flow make it difficult to detect perfusion using standard methods without the expense and risk of contrast enhancement. Our research measures the efficiency of conventional power-Doppler (PD) methods at discriminating flow states by comparing measurement performance to that of an ideal discriminator. ROC analysis applied to the experimental results shows that power Doppler methods are just 30-50 % efficient at perfusion flows less than 1ml/min, suggesting an opportunity to improve perfusion assessment through signal processing. A new perfusion estimator is proposed by extending the statistical discriminator approach. We show that 2-D perfusion color imaging may be enhanced using this approach.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2016
Subtitle of host publicationUltrasonic Imaging and Tomography
EditorsBrecht Heyde, Brecht Heyde, Neb Duric
ISBN (Electronic)9781510600256
StatePublished - 2016
EventMedical Imaging 2016: Ultrasonic Imaging and Tomography - San Diego, United States
Duration: Feb 28 2016Feb 29 2016

Publication series

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


OtherMedical Imaging 2016: Ultrasonic Imaging and Tomography
Country/TerritoryUnited States
CitySan Diego


  • Ideal Discriminator
  • Perfusion
  • Ultrasound Doppler

ASJC Scopus subject areas

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


Dive into the research topics of 'Ultrasound perfusion signal processing for tumor detection'. Together they form a unique fingerprint.

Cite this