Three-dimensional reconstruction of light microscopy image sections: present and future
Yuzhen Wang,Rui Xu,Gaoxing Luo,Jun Wu()
Institute of Burn Research, Southwest Hospital, State Key Laboratory of Trauma, Burns, and Combined Injury, Chongqing Key Laboratory for Diseases Proteomics, the Third Military Medical University, Chongqing 400038, China
Three-dimensional (3D) image reconstruction technologies can reveal previously hidden microstructures in human tissue. However, the lack of ideal, non-destructive cross-sectional imaging techniques is still a problem. Despite some drawbacks, histological sectioning remains one of the most powerful methods for accurate high-resolution representation of tissue structures. Computer technologies can produce 3D representations of interesting human tissue and organs that have been serial-sectioned, dyed or stained, imaged, and segmented for 3D visualization. 3D reconstruction also has great potential in the fields of tissue engineering and 3D printing. This article outlines the most common methods for 3D tissue section reconstruction. We describe the most important academic concepts in this field, and provide critical explanations and comparisons. We also note key steps in the reconstruction procedures, and highlight recent progress in the development of new reconstruction methods.
1. Ideal for the analysis of the intact mammalian cochlea
1. Different series of 2D images from the same specimen can be acquired
1. Inevitable damage to tissue microstructures
[4,8,9]
2. Limited resolution
2. Quantitative measurements can be obtained
2. Less time-consuming
3. Not suitable for in vivo studies
Optical projection tomography (OPT)
A resolution of microns to tens of μm
1. 3D visualization of soft tissue, cells, protein distribution, and gene expression patterns in biomedical specimens
1. Suitable for in vivo studies
Difficult to control the distribution and provide sufficient fluorescent or colored stains
[10–12]
2. Suitable for 1–10 mm-thick specimens
2. Fills the imaging gap between MRI and confocal microscopy
Confocal laser scanning microscopy (CLSM)
0.5–1 μm
Cell behavior, nerve endings, distribution of biomolecules, analysis of 3D pore structures, and other biomechanical parameters in porous nano/microfibrous biomaterials
Suitable for non-invasive in vivo detection and quantification
1. Maximum specimen thickness is approximately 100 μm
[2,13–15]
2. Distribution and sufficient fluorescent markers
3D reconstruction of serial physical sections
Sub-micron resolution
Almost all tissue ranging from bones to soft tissue
1. High resolution and large specimen size
1. Comparatively laborious
[16]
2. Dyeing of the target components is easy to control
2. Not suitable for in vivo studies
Tab.1
Fig.1
Fig.2
Fig.3
Type of transformation
Distance between any two pixels in the image
Methods
Limitations
Rigid registration
Rotation and translation
Unchanged
Head-and-hat algorithm [46]
Not suitable for non-rigid or nonlinear objects, which are common in the human body
Non-rigid registration
Affine [47], projective [48], and curved transformation
Changed
Based on spatial transformation (Thin Plate Splines [49], Basis Function);
Comparatively time-consuming, not as robust, and fewer evaluation methods
Based on pseudophysical models (Elastic Model [45], Viscous Fluid Model [50], Optical Flow Model)
K-nearest neighbor classifiers, maximum likelihood algorithms, supervised artificial neural network, support vector machine, active shape model, and active appearance model
Unsupervised classification algorithms
CM algorithms, fuzzy C-means (FCM) algorithms, iterative self-organizing data analysis technique algorithm, and unsupervised neural networks
Based on deformable models
Parametric deformable models
Snake method [56]
Geometric deformable models
Geodesic active contour algorithm
Tab.3
Applications
Organ/tissue
Thickness/ number of sections
Fixation
Stain method
Displayed components
Software
1
Human scalp skin
6 μm/200–350
10% neutral buffered formalin
Masson’s trichrome
Arrector pili muscles, hair follicles, sebaceous glands
“Reconstruct” software
2
Human lower limb skin
5 μm/5
4% paraformaldehyde
Podoplanin Immunohistochemistry
Lymphatic vessels
Amira Version 5.0
3
Human median nerve
20 μm/4650
Liquid nitrogen
Acetylcholinesterase histochemical staining
Motor nerve fibers and sensory nerve fibers
Adobe Photoshop CS2 software; 3D nerve visualization system (China)
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