High-speed laser Doppler perfusion imaging using an integrating CMOS image sensor

Alexandre Serov; Theo Lasser

doi:10.1364/OPEX.13.006416

Optics Express
Vol. 13,
Issue 17,
pp. 6416-6428
(2005)
•https://doi.org/10.1364/OPEX.13.006416

High-speed laser Doppler perfusion imaging using an integrating CMOS image sensor

Alexandre Serov and Theo Lasser

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Alexandre Serov and Theo Lasser, "High-speed laser Doppler perfusion imaging using an integrating CMOS image sensor," Opt. Express 13, 6416-6428 (2005)

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Abstract

This paper describes the design and the performance of a new high-speed laser Doppler imaging system for monitoring blood flow over an area of tissue. The new imager delivers high-resolution flow images (256×256 pixels) every 2 to 10 seconds, depending on the number of points in the acquired time-domain signal (32–512 points). This new imaging modality utilizes a digital integrating CMOS image sensor to detect Doppler signals in a plurality of points over the area illuminated by a divergent laser beam of a uniform intensity profile. The integrating property of the detector improves the signal-to-noise ratio of the measurements, which results in high-quality flow images. We made a series of measurements in vitro to test the performance of the system in terms of bandwidth, SNR, etc. Subsequently we give some examples of flow-related images measured on human skin, thus demonstrating the performance of the imager in vivo. The perspectives for future implementations of the imager for clinical and physiological applications are discussed.

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Fig. 1. a) High-speed laser Doppler imaging system. The imager head was mounted on an articulating arm to simplify access to the measured objects. b) Block diagram of the laser Doppler imaging system modules (top); and the intensity profile of the illuminating beam (bottom).

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Fig. 2. a) The M₁/M₀ (velocity) imager response as a function of the measured signal frequency. b) The √M₀ (concentration) imager response as a function of the measured signal frequency. c) The √M₀ (concentration) imager response as a function of the measured signal amplitude. d) The SNR of the system as a function of the integration time for measurements on finger and forearm skin; error bars represent standard error for each measured SNR.

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Fig. 3. Flow-related maps obtained with the new imager on finger skin (ROI=256×256 pixels): a) perfusion map [Low=1500 a.u.; High=3000 a.u.]; b) blood concentration map [Low=150 a.u.; High=300 a.u.]; c) flow speed map [Low=500 a.u.; High=1500 a.u.]; d) image of the object. The imaging area is 5.5×5.5 cm². The imaging time is 3.5 seconds in total.

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Fig. 4. Artery occlusion experiment recording repeated perfusion images in real-time (ROI=256×256 pixels). Numbers show time (in seconds) when the images were obtained: 0–6 s, before occlusion; 16 s, occlusion on; 22–29 s, occlusion stopped blood flow; 35 s: occlusion is released; 38–45 s, post-occlusive hyperemia; 48–64 s, restored perfusion level. The imaging area is 5.5×5.5 cm². Low=1500 a.u.; High=3000 a.u.

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Fig. 5. Perfusion images obtained with the high-speed laser Doppler imager (ROI=256×256 pixels). The imaging area is 5.5×5.5 cm². The effect of the stimulant cream (from Induchem AG, Switzerland) is the increased blood flow in the area where the cream was applied. The cream was applied on the skin of the inner side of the forearm. Images show the blood flow changes trough time: at 90, 97, 110, 124, 138, and 152 seconds after the cream was applied to the skin. The imaging time is c.a. 3.5 seconds per image. Low=500 a.u.; High=2500 a.u. (the red bar on the latest perfusion image is caused by an accident artifact during the sensor readout).

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Equations (20)

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Δ t = \frac{T_{tot}}{N} .

X_{non_int} \propto \frac{P_{tot}}{N} Δ t .

X_{int} \propto \frac{P_{tot}}{N} T_{tot} .

SNR \propto \sqrt{X} .

\frac{{SNR}_{int}}{{SNR}_{non_int}} = \sqrt{N} .

TN = 〈 i_{TN}^{2} 〉 = \frac{4 \cdot k \cdot T \cdot B_{n}}{R},

SN = 〈 i_{SN}^{2} 〉 = 2 \cdot q \cdot 〈 I 〉 \cdot B_{n},

〈 I 〉 = 〈 I_{photo} 〉 + 〈 I_{dark} 〉 .

R = \frac{1}{2 π \cdot C \cdot f_{s}},

SNR = \frac{〈 i_{s}^{2} 〉}{2 \cdot q \cdot 〈 I 〉 \cdot B_{n} + 8 π \cdot k \cdot T \cdot C \cdot f_{s} \cdot B_{n}} .

〈 i_{s}^{2} 〉 = \frac{{〈 I_{photo} 〉}^{2}}{M} .

f_{s} = \frac{1}{2 π \cdot R \cdot C} .

B_{n} = \frac{1}{4 \cdot R \cdot C} = \frac{π}{2} f_{s} .

{SNR}_{non_int} = \frac{〈 i_{s}^{2} 〉}{π \cdot q \cdot 〈 I 〉 \cdot f_{s} + {4 π}^{2} \cdot k \cdot T \cdot C \cdot f_{s}^{2}} .

B_{n} = \frac{1}{2 \cdot T_{int}} = f_{s} .

{SNR}_{int} = \frac{〈 i_{s}^{2} 〉}{2 \cdot q \cdot 〈 I 〉 \cdot f_{s} + 8 π \cdot k \cdot T \cdot C \cdot f_{s}^{2}} = \frac{π}{2} {SNR}_{non_int} .

\frac{{SNR}_{int}}{{SNR}_{non_int}} = \frac{π}{2} \sqrt{N} .

Concentration = 〈 C 〉 \propto M_{0} = \int_{0}^{\infty} S (ν) dν,

Perfusion = 〈 C 〉 V_{rms} \propto M_{1} = \int_{0}^{\infty} vS (ν) dν,

S (ν) = {∣ \int_{0}^{\infty} I (t) \exp (- i 2 π ν t) d t ∣}^{2} .

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