Evidence map›Paper›PMID 42397088›Full record

ArticleJournal of anatomy2026

Two-step workflow integrating automatic registration and manual refinement for the accurate alignment of serial histological sections in 3D reconstruction.

Satoru Muro, Takuya Ibara, Akimoto Nimura, Keiichi Akita

Abstract read
In one paragraph

Article in Journal of anatomy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

4 authors.

Satoru MuroDepartment of Clinical Anatomy, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-4709-6359
Takuya IbaraDepartment of Functional Joint Anatomy, Biomedical Engineering Laboratory, Institute of Industry Incubation, Institute of Science Tokyo, Tokyo, Japan.
Akimoto NimuraDepartment of Functional Joint Anatomy, Biomedical Engineering Laboratory, Institute of Industry Incubation, Institute of Science Tokyo, Tokyo, Japan.
Keiichi AkitaDepartment of Clinical Anatomy, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-2927-2937

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accurate alignment of serial histological sections is essential for preserving anatomical continuity in 3D reconstruction. Although automated registration tools can efficiently correct global alignment errors, they often fail to resolve local misalignments caused by sectioning artifacts, tissue deformation, staining variability, or missing slices. Thus, we propose a practical two-step registration workflow that uses MultiStackReg (an ImageJ/Fiji plugin) for automatic alignment and AlignRef (a standalone application for interactive adjustment) for manual refinement. In the first step, MultiStackReg performs global registration by using rigid body transformations. In the second step, AlignRef corrects residual misalignments through semi-transparent overlay visualization, keyboard-based translation and rotation, and batch propagation of recorded transformations across selected slice ranges. We applied our workflow to 135 serial sections of a Carnegie Stage 15 embryo from the Virtual Human Embryo dataset that were stained with hematoxylin and eosin. MultiStackReg resolved most global inconsistencies, whereas AlignRef enabled the precise adjustment of subtle local deviations, particularly in curved structures such as neural tubes and limb buds. After automatic registration with MultiStackReg, the subsequent manual refinement step using AlignRef was completed in approximately 30 min and produced a suitable stack for 3D reconstruction. This two-step workflow balances automation with expert-guided correction and provides an accessible, reproducible, and anatomically precise method for the serial section alignment of morphological and developmental anatomy.

Indexed as

3D reconstructionimage registrationserial histological sections

Identifiers

PMID42397088
PMCPMC13398511

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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.