Optical Methods and Instrumentation in Brain Imaging and Therapy 2012
DOI: 10.1007/978-1-4614-4978-2_5
|View full text |Cite
|
Sign up to set email alerts
|

Laser Speckle Imaging of Cerebral Blood Flow

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
5
0

Year Published

2013
2013
2017
2017

Publication Types

Select...
3
1

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(5 citation statements)
references
References 42 publications
0
5
0
Order By: Relevance
“…The ability of the technique to measure flow velocities with high sensitivity has been confirmed by comparison to both Laser Doppler measurements [24], time of flight measurements in vivo [23], and in microfluidic systems in-vitro [25]. A number of review papers in the last few years outline the breadth of applications enabled by the technique in cortical blood flow imaging in healthy and damaged tissue [26][27][28][29].…”
Section: Introductionmentioning
confidence: 92%
“…The ability of the technique to measure flow velocities with high sensitivity has been confirmed by comparison to both Laser Doppler measurements [24], time of flight measurements in vivo [23], and in microfluidic systems in-vitro [25]. A number of review papers in the last few years outline the breadth of applications enabled by the technique in cortical blood flow imaging in healthy and damaged tissue [26][27][28][29].…”
Section: Introductionmentioning
confidence: 92%
“…[21][22][23][24][31][32][33] As LSCI gains popularity and clinical investigations increase, it is important to assess the impact of physiological motion and investigate methods to compensate for these artifacts. Because LSCI is inherently sensitive to motion, the recorded images are impacted by both pulsatile flow and tissue deformation from the cardiac cycle and respiration.…”
Section: Discussionmentioning
confidence: 99%
“…To account for blood flow changes that occur during the cardiac cycle, an ad hoc ECG filter [31][32][33] was implemented to reduce fluctuations in recorded τ c values. Briefly, the actual time of each image was determined from the recorded camera exposure signal and the actual time of each heartbeat was determined from the ECG waveform.…”
Section: Cardiac Filteringmentioning
confidence: 99%
“…7 Registered images were selected from the same 0.2-s normalized time window of the cardiac cycle to synchronize with the heartbeat and minimize pulsatile variation across exposure times. 6,7,19 Fifty images spanning multiple heartbeats were averaged for each exposure time to reduce noise for the computation of MESI ICT maps. A sub-set of recorded images (20–30 s, 1400–2000 frames) from each exposure time was used for analysis on select regions of interest (ROIs), which were cardiac filtered similar to previous work.…”
Section: Methodsmentioning
confidence: 99%
“…A sub-set of recorded images (20–30 s, 1400–2000 frames) from each exposure time was used for analysis on select regions of interest (ROIs), which were cardiac filtered similar to previous work. 6,7,19 ICT values were computed and displayed as summary values, since each exposure corresponded to different time points. For the single-exposure LSCI recording during tissue cautery in case 8, ROI data were cardiac filtered, smoothed using a 0.5-s moving average filter, and displayed as a time course.…”
Section: Methodsmentioning
confidence: 99%