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Updated: Feb 28, 2026

Dual Raster-Scanning Photoacoustic Small-Animal Imager for Vascular Visualization

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Published on: July 15, 2020

Dual-Readout Self-Resetting CMOS Image Sensor for Resolving Sub-Percent Optical Contrast in Biomedical Imaging.

Kiyotaka Sasagawa^1,2, Subaru Iwaki¹, Kenji Morimoto¹

¹Division of Materials Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma 630-0192, Nara, Japan.

Sensors (Basel, Switzerland)

|February 27, 2026

Summary

This summary is machine-generated.

This study introduces a novel CMOS image sensor with a dual-readout architecture. It achieves over 70 dB signal-to-noise ratio (SNR) and detects subtle contrast changes, crucial for advanced bio-imaging.

Keywords:

CMOS image sensor artifact reduction biomedical imaging dual-readout architecture high dynamic range microcirculation self-resetting pixel signal-to-noise ratio

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Area of Science:

* Electrical Engineering
* Biomedical Imaging
* Sensor Technology

Background:

* Conventional CMOS image sensors struggle with reset artifacts, limiting their ability to detect subtle contrast variations.
* High signal-to-noise ratio (SNR) and wide dynamic range are critical for precise bio-imaging applications like monitoring blood flow.

Purpose of the Study:

* To develop a self-resetting CMOS image sensor with enhanced SNR and contrast detection capabilities.
* To overcome the limitations of existing sensors in capturing dynamic, low-contrast signals.

Main Methods:

* Implementation of a Dual-Readout architecture with temporally offset scanners for continuous data acquisition.
* Utilization of a minimum frame-to-frame difference algorithm for signal restoration without in-pixel counters.
* Fabrication of a prototype chip in a 0.35-μm process.

Main Results:

* Achieved a peak signal-to-noise ratio (SNR) exceeding 70 dB, approaching the shot-noise limit.
* Successfully visualized contrast fluctuations as low as ±0.25% in vascular phantom experiments.
* Demonstrated effective suppression of reset artifacts.

Conclusions:

* The developed dual-readout sensor significantly improves SNR and contrast detection sensitivity.
* This technology offers a powerful platform for high-precision bio-imaging, including brain surface blood flow monitoring.
* Enables detection of previously undetectable dynamic signals.