Evidence map›Paper›PMID 40236252›Full record

ArticlebioRxiv : the preprint server for biology2025

Suite3D: Volumetric cell detection for two-photon microscopy.

Ali Haydaroğlu, Tinya Chang, Andrew Landau, Michael Krumin, Sam Dodgson, Liad J Baruchin, Maria Cozan, Jingkun Guo, David Meyer, Charu Bai Reddy and 6 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Ali HaydaroğluUniversity College London, London, UK.ORCID 0000-0002-8006-3145
Tinya ChangUniversity College London, London, UK.
Andrew LandauUniversity College London, London, UK.ORCID 0000-0001-9105-1636
Michael KruminUniversity College London, London, UK.ORCID 0000-0001-7356-6994
Sam DodgsonUniversity College London, London, UK.ORCID 0009-0009-5217-8605
Liad J BaruchinUniversity of Sussex, Brighton, UK.ORCID 0000-0002-0539-696X
Maria CozanUniversity of Sussex, Brighton, UK.
Jingkun GuoRockefeller University, New York, NY, USA.ORCID 0000-0002-3470-1433
David MeyerRockefeller University, New York, NY, USA.
Charu Bai ReddyUniversity College London, London, UK.ORCID 0000-0002-8195-3326
Jian ZhongUniversity of California Berkeley, CA, USA.
Na JiUniversity of California Berkeley, CA, USA.ORCID 0000-0002-5527-1663
Sylvia SchröderUniversity of Sussex, Brighton, UK.ORCID 0000-0002-9938-3931
Kenneth D HarrisUniversity College London, London, UK.ORCID 0000-0002-5930-6456
Alipasha VaziriRockefeller University, New York, NY, USA.ORCID 0000-0001-8346-7551
Matteo CarandiniUniversity College London, London, UK.ORCID 0000-0003-4880-7682

Funding

Resource for Biocomputing Visualization and InformaticsP41GM103311 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2012 to 2017
$8.2M
Optimization, Application, and Dissemination of Imaging Modules for High-speed Mesoscopic Volumetric Recording of Neuroactivity in Scattering BrainsU01NS126057 · NINDS · ROCKEFELLER UNIVERSITY · PI VAZIRI, ALIPASHA · 2022 to 2025
$5.0M
kHz-rate in vivo imaging of neural activity througout the living brainUF1NS107696 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI JI, NA, TSIA, KEVIN KIN MAN · 2018 to 2018
$2.1M
Optimizing FACED for robust large-scale activity recordingU01NS137449 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI NA Ji · 2024 to 2026
$2.1M
Adaptive optical microscopy for high-accuracy recording of neural activity in vivoU01NS118300 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI JI, NA · 2021 to 2023
$1.7M
NIGMS NIH HHS P41 GM103311NINDS NIH HHS U01 NS118300NINDS NIH HHS U01 NS126057NINDS NIH HHS U01 NS137449NINDS NIH HHS UF1 NS107696Wellcome Trust
6 · The paper itself

Abstract

In two-photon imaging of neuronal activity it is common to acquire 3-dimensional volumes. However, these volumes are typically processed plane by plane, leading to duplicated cells across planes, reduced signal-to-noise ratio per cell, uncorrected axial movement, and missed cells. To overcome these limitations, we introduce Suite3D, a volumetric cell detection pipeline. Suite3D corrects for 3D brain motion, estimating axial motion and improving estimates of lateral motion. It detects neurons using 3D correlation, which improves the signal-to-background ratio and detectability of cells. Finally, it performs 3D segmentation, detecting cells across imaging planes. We validated Suite3D with data from conventional multi-plane microscopes and advanced volumetric microscopes, at various resolutions and in various brain regions. Suite3D successfully detected cells appearing on multiple imaging planes, improving cell detectability and signal quality, avoiding duplications, and running >20x faster than a prior volumetric pipeline. Suite3D offers a powerful solution for analyzing volumetric two-photon data.

Identifiers

PMID40236252
PMCPMC11996422

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.