Anchor point based image registration for absolute scale topographic structure detection in microscopy

Diao, Zhuo; Meng, Zijie; Li, Fengxuan; Hou, Linfeng; Yamashita, Hayato; Tohei, Tetsuya; Abe, Masayuki; Sakai, Akira

doi:https://doi.org/10.1038/s41598-025-98390-5

Anchor point based image registration for absolute scale topographic structure detection in microscopy

Diao, Zhuo; Meng, Zijie; Li, Fengxuan et al.

Scientific Reports, 2025, 15(1), 13486

Number of Access:24（2025-12-09 04:55 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/102915

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Title	Anchor point based image registration for absolute scale topographic structure detection in microscopy
Creator	NRID 1000031005515 1000031005515 ORCID 0000-0001-5358-444X 0000-0001-5358-444X researchmap permalink diaozhuo diaozhuo Scopus Author ID 57218387012 57218387012 CreatorName Diao, Zhuo
	CreatorName Meng, Zijie
	CreatorName Li, Fengxuan
	CreatorName Hou, Linfeng
	NRID 1000010595440 1000010595440 ORCID 0000-0003-4473-5773 0000-0003-4473-5773 researchmap permalink 10595440 10595440 Scopus Author ID 57202699112 57202699112 CreatorName Yamashita, Hayato
	NRID 1000000463878 1000000463878 ORCID 0000-0002-4113-2566 0000-0002-4113-2566 researchmap permalink ttohei ttohei Scopus Author ID 55880985600 55880985600 CreatorName Tohei, Tetsuya
	NRID 1000000362666 1000000362666 ORCID 0000-0001-5619-3911 0000-0001-5619-3911 researchmap permalink read0089681 read0089681 Scopus Author ID 7404123577 7404123577 CreatorName Abe, Masayuki
	NRID 1000020314031 1000020314031 ORCID 0000-0002-0654-504X 0000-0002-0654-504X researchmap permalink read0192520 read0192520 Scopus Author ID 7402911242 7402911242 CreatorName Sakai, Akira
Description	Diao Z., Meng Z., Li F., et al. Anchor point based image registration for absolute scale topographic structure detection in microscopy. Scientific Reports 15, 13486 (2025); https://doi.org/10.1038/s41598-025-98390-5.
Abstract	Microscopy images obtained through remote sensing often suffer from misalignment and deformation, complicating accurate data analysis. As experimental instruments improve and scientific discoveries deepen, the volume of data requiring processing continues to grow. Image registration can contribute to microscopy automation, which enables more efficient data analysis and experimental workflows. For this implementation, image processing techniques that can handle both image registration and localized object analysis are required. This research introduces a computer interface designed to calibrate and analyze specific structures with prior knowledge of the observed target. Our method achieves image registration by aligning anchor points, which correspond to the coordinates of a structural model within the image. It employs homography transform to correct images, restoring them to their original, undistorted form, thus enabling consistent quantitative comparisons across different images on an absolute scale. Additionally, the method provides valuable information from the registered anchor points, allowing for the precise localization of local objects in the structure. We demonstrate this technique across various microscopy scenarios at different scales and evaluate its precision against a keypoint detection AI approach from our previous research, which promises its enhancement in microscopy data analysis and automation.
Publisher	Nature Research
Source Title	Scientific Reports
Volume (Issue)	15(1)
Page	13486
Date of Issued	2025-04-18
Language	English
Handle URL	https://hdl.handle.net/11094/102915
eISSN	20452322
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1038/s41598-025-98390-5
Access Rights	open access
CopyRight	This article is licensed under a Creative Commons Attribution 4.0 International License.
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	Scientific Reports. 2025, 15(1), p. 13486
DC.title	Anchor point based image registration for absolute scale topographic structure detection in microscopy
DC.creator	Diao, Zhuo
	Meng, Zijie
	Li, Fengxuan
	Hou, Linfeng
	Yamashita, Hayato
	Tohei, Tetsuya
	Abe, Masayuki
	Sakai, Akira
DC.publisher	Nature Research
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2025-04-18
DC.identifier	https://doi.org/10.1038/s41598-025-98390-5
DC.description	Diao Z., Meng Z., Li F., et al. Anchor point based image registration for absolute scale topographic structure detection in microscopy. Scientific Reports 15, 13486 (2025); https://doi.org/10.1038/s41598-025-98390-5.
DCTERMS.abstract	Microscopy images obtained through remote sensing often suffer from misalignment and deformation, complicating accurate data analysis. As experimental instruments improve and scientific discoveries deepen, the volume of data requiring processing continues to grow. Image registration can contribute to microscopy automation, which enables more efficient data analysis and experimental workflows. For this implementation, image processing techniques that can handle both image registration and localized object analysis are required. This research introduces a computer interface designed to calibrate and analyze specific structures with prior knowledge of the observed target. Our method achieves image registration by aligning anchor points, which correspond to the coordinates of a structural model within the image. It employs homography transform to correct images, restoring them to their original, undistorted form, thus enabling consistent quantitative comparisons across different images on an absolute scale. Additionally, the method provides valuable information from the registered anchor points, allowing for the precise localization of local objects in the structure. We demonstrate this technique across various microscopy scenarios at different scales and evaluate its precision against a keypoint detection AI approach from our previous research, which promises its enhancement in microscopy data analysis and automation.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	102915
citation_title	Anchor point based image registration for absolute scale topographic structure detection in microscopy
citation_author	Diao, Zhuo
	Meng, Zijie
	Li, Fengxuan
	Hou, Linfeng
	Yamashita, Hayato
	Tohei, Tetsuya
	Abe, Masayuki
	Sakai, Akira
citation_publisher	Nature Research
citation_language	English
citation_date	2025-04-18
citation_journal_title	Scientific Reports
citation_volume	15
citation_issue	1
citation_firstpage	13486
citation_doi	https://doi.org/10.1038/s41598-025-98390-5
citation_public_url	https://hdl.handle.net/11094/102915

Anchor point based image registration for absolute scale topographic structure detection in microscopy

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