ReviewRadiology research and practice2022
Current Approaches for Image Fusion of Histological Data with Computed Tomography and Magnetic Resonance Imaging.
Review in Radiology research and practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Registration-based 3D Light Sheet Fluorescence Microscopy and 2D histology image fusion tool for pathological specimen.Scientific reports · 2026Article
- Novel image registration approach for combining 2D Osterix and collagen bundles images with 3D micro-CT.JBMR plus · 2026Article
- Multidimensional lung imaging: integrated preclinical platforms enabling the identification of translational biomarkers for pulmonary research.Respiratory research · 2026Review
- Mapping lung cancer ventilation dynamics using functional imaging and lung mechanics.Disease models & mechanisms · 2025Article
- 2D-3D deformable image registration of histology slide and micro-CT with DISA-based initialization.Scientific reports · 2025Article
- Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans.Journal of neuroscience methods · 2025Article
- X-ray contrast-adjustable 3D printing for multimodal fusion of microCT and histology.Frontiers in medical technology · 2025Article
- Reconstructing 3D histological structures using machine learning (artificial intelligence) algorithms.Pathologie (Heidelberg, Germany) · 2024Review
- Spatial correlation of 2D hard-tissue histology with 3D microCT scans through 3D printed phantoms.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Classical analysis of biological samples requires the destruction of the tissue's integrity by cutting or grinding it down to thin slices for (Immuno)-histochemical staining and microscopic analysis. Despite high specificity, encoded in the stained 2D section of the whole tissue, the structural information, especially 3D information, is limited. Computed tomography (CT) or magnetic resonance imaging (MRI) scans performed prior to sectioning in combination with image registration algorithms provide an opportunity to regain access to morphological characteristics as well as to relate histological findings to the 3D structure of the local tissue environment. This review provides a summary of prevalent literature addressing the problem of multimodal coregistration of hard- and soft-tissue in microscopy and tomography. Grouped according to the complexity of the dimensions, including image-to-volume (2D ⟶ 3D), image-to-image (2D ⟶ 2D), and volume-to-volume (3D ⟶ 3D), selected currently applied approaches are investigated by comparing the method accuracy with respect to the limiting resolution of the tomography. Correlation of multimodal imaging could position itself as a useful tool allowing for precise histological diagnostic and allow the a priori planning of tissue extraction like biopsies.
Identifiers
What OpenQuestion holds
Registered trials
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.