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Related Experiment Video

Updated: Jun 4, 2026

Blood Flow Imaging with Ultrafast Doppler
05:57

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

Low resource processing algorithms for laser Doppler blood flow imaging.

Hoang C Nguyen1, Barrie R Hayes-Gill, Yiqun Zhu

  • 1Electrical Systems and Optics Research Division, Faculty of Engineering, The University of Nottingham, University Park, Nottingham, United Kingdom.

Medical Engineering & Physics
|February 15, 2011
PubMed
Summary
This summary is machine-generated.

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New algorithms for CMOS-based laser Doppler blood flow imaging efficiently process large datasets. These methods reduce system resource usage and data storage, enabling embedded system integration for accurate flow measurements.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Signal Processing

Background:

  • Full field laser Doppler blood flow imaging systems using CMOS cameras generate large data volumes.
  • Conventional processing algorithms are resource-intensive and unsuitable for efficient, real-time processing.

Purpose of the Study:

  • To develop and implement efficient processing algorithms for CMOS-based laser Doppler blood flow imaging.
  • To reduce system resource consumption and data storage requirements for embedded applications.

Main Methods:

  • Implemented two novel processing algorithms on a field-programmable gate array (FPGA).
  • Algorithm 1: Short Fourier Transform (length 8) with averaging (128 times).
  • Algorithm 2: Infinite Impulse Response (IIR) filter with frequency-weighted response in the time domain.

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Related Experiment Videos

Last Updated: Jun 4, 2026

Blood Flow Imaging with Ultrafast Doppler
05:57

Blood Flow Imaging with Ultrafast Doppler

Published on: October 14, 2020

A Novel Approach to Overcome Movement Artifact When Using a Laser Speckle Contrast Imaging System for Alternating Speeds of Blood Microcirculation
07:20

A Novel Approach to Overcome Movement Artifact When Using a Laser Speckle Contrast Imaging System for Alternating Speeds of Blood Microcirculation

Published on: August 30, 2017

How to Build a Laser Speckle Contrast Imaging (LSCI) System to Monitor Blood Flow
05:24

How to Build a Laser Speckle Contrast Imaging (LSCI) System to Monitor Blood Flow

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Main Results:

  • Both algorithms demonstrated significantly lower data storage needs per pixel (8 and 5 words) compared to the reference (1024 words).
  • The short length Fourier transform algorithm achieved a 1.3% error, while the IIR filter algorithm achieved a 0.7% error versus the reference Fast Fourier Transform.
  • Algorithms are accurate and require minimal system resources, suitable for embedded system integration.

Conclusions:

  • Developed efficient algorithms for laser Doppler blood flow imaging, optimizing resource usage and data handling.
  • These algorithms enable the integration of advanced blood flow imaging into embedded systems like ASICs.
  • The proposed methods offer a viable alternative to conventional algorithms for high-volume data processing in medical imaging.