# Region of interest determination algorithm of lensless calcium imaging datasets

**Authors:** Virgil Christian Garcia Castillo, Latiful Akbar, Ronnakorn Siwadamrongpong, Yasumi Ohta, Mamiko Kawahara, Yoshinori Sunaga, Hironari Takehara, Hiroyuki Tashiro, Kiyotaka Sasagawa, Jun Ohta

PMC · DOI: 10.1371/journal.pone.0308573 · PLOS ONE · 2024-09-17

## TL;DR

This paper introduces a new algorithm for identifying regions of interest in lensless calcium imaging data, improving the ability to detect brain activity in freely moving mice.

## Contribution

The novel contribution is an ROI determination algorithm optimized for lensless calcium imaging, validated with simulated and experimental data.

## Key findings

- The ROI algorithm successfully localized fluorescence activity and separated it from noise in simulated and experimental data.
- Significant increases in fluorescence activity were observed in the dorsal raphe nucleus after formalin injection compared to controls.
- The algorithm was validated using freely moving nociception experiments in transgenic G-CaMP mice.

## Abstract

Advances in fluorescence imaging technology have been crucial to the progress of neuroscience. Whether it was specific expression of indicator proteins, detection of neurotransmitters, or miniaturization of fluorescence microscopes, fluorescence imaging has improved upon electrophysiology, the gold standard for monitoring brain activity, and enabled novel methods to sense activity in the brain. Hence, we developed a lightweight and compact implantable CMOS-based lensless Ca2+ imaging device for freely moving transgenic G-CaMP mouse experiments. However, without a lens system, determination of regions of interest (ROI) has proven challenging. Localization of fluorescence activity and separation of signal from noise are difficult. In this study, we report an ROI selection method using a series of adaptive binarizations with a gaussian method and morphological image processing. The parameters for each operation such as the kernel size, sigma and footprint size were optimized. We then validated the utility of the algorithm with simulated data and freely moving nociception experiments using the lensless devices. The device was implanted in the dorsal raphe nucleus to observe pain-related brain activity following a formalin test to stimulate pain. We observed significant increases in fluorescence activity after formalin injection compared to the control group when using the ROI determination algorithm.

## Linked entities

- **Chemicals:** formalin (PubChem CID 712)
- **Species:** Mus musculus (taxon 10090)

## Full-text entities

- **Genes:** Camp (cathelicidin antimicrobial peptide) [NCBI Gene 12796] {aka CAP18, CLP, Cnlp, Cramp, FALL39, MCLP}
- **Diseases:** pain (MESH:D010146)
- **Chemicals:** calcium (MESH:D002118), Ca2+ (-), formalin (MESH:D005557)
- **Species:** Mus musculus (house mouse, species) [taxon 10090]

## Full text

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## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11407621/full.md

## References

37 references — full list in the complete paper: https://tomesphere.com/paper/PMC11407621/full.md

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Source: https://tomesphere.com/paper/PMC11407621