{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T21:19:35Z","timestamp":1791667175749,"version":"4.3.4"},"reference-count":41,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T00:00:00Z","timestamp":1769126400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Microscopy Res &amp; Technique"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Histological analysis is central to biomedical research and diagnostic pathology, yet conventional two\u2010dimensional (2D) sectioning captures only limited aspects of tissue architecture. Critical spatial relationships\u2014such as tumor boundaries, stromal organization, and vascular networks\u2014remain obscured, restricting diagnostic accuracy and biological interpretation. HistoNeRF addresses these limitations by adapting Neural Radiance Fields (NeRF) to reconstruct three\u2010dimensional (3D) tissue volumes from routine histological sections. In this study, 84 toluidine blue (TB)\u2013stained murine ovarian sections were digitized, alignment\u2010corrected, and integrated into volumetric models. Tissue segmentation was performed using a convolutional neural network, while visualization was achieved through an interactive, GPU\u2010accelerated interface. To ensure accessibility and reproducibility, a Python\u2010based graphical application (HistoNeRF GUI) was developed following Human\u2013Computer Interaction (HCI) principles and containerized with Docker, allowing installation\u2010free deployment via Docker Hub. HistoNeRF produced high\u2010fidelity 3D reconstructions (SSIM\u2009=\u20090.92; Dice similarity coefficient\u2009=\u20090.88), enabling expert histologists to better visualize follicular structures, stromal compartments, and vascular elements. The containerized GUI was deployed successfully from Docker Hub, providing immediate access to 3D reconstruction without a complex local setup. By overcoming the inherent constraints of 2D microscopy, HistoNeRF enhances the visualization, interpretability, and reproducibility of histological architecture. The HCI\u2010guided, cross\u2010platform interface supports scalability and rapid adoption in digital pathology workflows. Although validation was limited to murine ovarian tissue and one staining protocol, this framework can be extended across tissue types and clinical datasets. HistoNeRF bridges routine histology and 3D volumetric analysis through accurate, interactive reconstructions that advance diagnostic precision and biomedical research. While demonstrated on 84 serial TB\u2010stained ovarian sections, broader validation across tissues, stains, and pathological conditions remains future work; to support this, we provide a Dockerized, modular pipeline for straightforward extension.<\/jats:p>","DOI":"10.1002\/jemt.70124","type":"journal-article","created":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T13:13:01Z","timestamp":1769173981000},"page":"921-931","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["<scp>HistoNeRF<\/scp>\n                    : An Accessible and Intelligent Approach for Comprehensive\n                    <scp>2D\u2010to\u20103D<\/scp>\n                    Histological Assessment"],"prefix":"10.1002","volume":"89","author":[{"given":"Kubilay Do\u011fan","family":"Kili\u00e7","sequence":"first","affiliation":[{"name":"Department of Histology and Embryology, Faculty of Medicine Ege University  \u0130zmir T\u00fcrkiye"},{"name":"Institute for Intelligent Biotechnologies (iBio) Helmholtz Center  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4836-8352","authenticated-orcid":false,"given":"Kaan","family":"\u00d6zyazici","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Faculty of Engineering Ya\u015far University  \u0130zmir T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"H\u00fcseyin","family":"Kisao\u011flu","sequence":"additional","affiliation":[{"name":"Department of Histology and Embryology, Faculty of Medicine Ege University  \u0130zmir T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1460-8530","authenticated-orcid":false,"given":"Zeynep Simge","family":"Yilmaz","sequence":"additional","affiliation":[{"name":"Department of Histology and Embryology, Faculty of Medicine Ege University  \u0130zmir T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-6203-4111","authenticated-orcid":false,"given":"B\u00fc\u015fra","family":"Horuz","sequence":"additional","affiliation":[{"name":"Department of Histology and Embryology, Faculty of Medicine Ege University  \u0130zmir T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9780-6948","authenticated-orcid":false,"given":"Ay\u015feg\u00fcl","family":"Ta\u015fk\u0131ran \u00d6zyazici","sequence":"additional","affiliation":[{"name":"Department of Histology and Embryology, Faculty of Medicine Ege University  \u0130zmir T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,1,23]]},"reference":[{"key":"e_1_2_10_2_1","first-page":"265","volume-title":"12th USENIX Symposium on Operating Systems Design and Implementation (OSDI)","author":"Abadi M.","year":"2016"},{"key":"e_1_2_10_3_1","volume-title":"Theory and Practice of Histological Techniques","author":"Bancroft J. 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