Full-field laser Doppler perfusion imaging and monitoring with an intelligent CMOS camera

Theo Lasser
2005
Journal paper

A system for full-field laser Doppler blood flow imaging has been developed and tested on biomedical samples. The new imaging system allows 2D flow maps or monitoring flux signals to be obtained from a plurality of measured points simultaneously by using a 2D array of photodetectors. The detection part of the system is based on an intelligent CMOS camera with a built-in digital signal processor and memory. The imaging time of the system is as much as to 4 times faster than for the conventional scanning laser Doppler imager. The performance of the system was evaluated in vitro and in vivo. The first measurement results with this new system on human skin are reported. (C) 2005 Optical Society of America.

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Theo Lasser
2005
Journal paper

Abstract

Official source

https://infoscience.epfl.ch/record/90474?ln=en

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Related concepts (10)

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Digital signal processor

A digital signal processor (DSP) is a specialized microprocessor chip, with its architecture optimized for the operational needs of digital signal processing. DSPs are fabricated on MOS integrated c

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A system is a group of interacting or interrelated elements that act according to a set of rules to form a unified whole. A system, surrounded and influenced by its environment, is described by its

Measurement

Measurement is the quantification of attributes of an object or event, which can be used to compare with other objects or events. In other words, measurement is a process of determining how large or

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

Theo Lasser

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 x 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. (c) 2005 Optical Society of America.

2005

Learning rich optical embeddings for privacy-preserving lensless image classification

Eric Bezzam, Matthieu Martin Jean-André Simeoni, Martin Vetterli

By replacing the lens with a thin optical element, lensless imaging enables new applications and solutions beyond those supported by traditional camera design and post-processing, e.g. compact and lightweight form factors and visual privacy. The latter arises from the highly multiplexed measurements of lensless cameras, which require knowledge of the imaging system to recover a recognizable image. In this work, we exploit this unique multiplexing property: casting the optics as an encoder that produces learned embeddings directly at the camera sensor. We do so in the context of image classification, where we jointly optimize the encoder's parameters and those of an image classifier in an end-to-end fashion. Our experiments show that jointly learning the lensless optical encoder and the digital processing allows for lower resolution embeddings at the sensor, and hence better privacy as it is much harder to recover meaningful images from these measurements. Additional experiments show that such an optimization allows for lensless measurements that are more robust to typical real-world image transformations. While this work focuses on classification, the proposed programmable lensless camera and end-to-end optimization can be applied to other computational imaging tasks.

2022

Design and characterization of a CMOS 3-D image sensor based on single photon avalanche diodes

Pierre-André Besse, Edoardo Charbon, Cristiano Niclass, Alexis Rochas

The design and characterization of an imaging system is presented for depth information capture of arbitrary three-dimensional (3-D) objects. The core of the system is an array of 32 × 32 rangefinding pixels that independently measure the time-of-flight of a ray of light as it is reflected back from the objects in a scene. A single cone of pulsed laser light illuminates the scene, thus no complex mechanical scanning or expensive optical equipment are needed. Millimetric depth accuracies can be reached thanks to the rangefinder's optical detectors that enable picosecond time discrimination. The detectors, based on a single photon avalanche diode operating in Geiger mode, utilize avalanche multiplication to enhance light detection. On-pixel high-speed electrical amplification can therefore be eliminated, thus greatly simplifying the array and potentially reducing its power dissipation. Optical power requirements on the light source can also be significantly relaxed, due to the array's sensitivity to single photon events. A number of standard performance measurements, conducted on the imager, are discussed in the paper. The 3-D imaging system was also tested on real 3-D subjects, including human facial models, demonstrating the suitability of the approach.

2005