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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2015, Vol. 9 Issue (1) : 30-45     DOI: 10.1007/s11684-014-0337-z
REVIEW |
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
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Abstract  

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.

Keywords microtomy      3D imaging      computer-assisted image processing      3D printing      tissue scaffold     
Corresponding Authors: Jun Wu   
Online First Date: 19 June 2014    Issue Date: 02 March 2015
URL:  
http://academic.hep.com.cn/fmd/EN/10.1007/s11684-014-0337-z     OR     http://academic.hep.com.cn/fmd/EN/Y2015/V9/I1/30
XY resolution Application Advantages Drawbacks References
X-ray microtomography (microCT) 300–700 nm In vivo analysis and 3D imaging (embryos, bone, tumor, stomatology, granular, and porous materials) Non-destructive;different perspective imaging No ideal methods for specific staining [2,5,6]
Microscopic magnetic resonance imaging (microMRI) Approximately 10 μm 1. In vivo monitoring and 3D imaging Non-destructive; Limitations of physical resolution [2,7]
2. Untreated or living biological specimens can also be used higher soft tissue contrast
Orthogonal-plane fluorescence optical sectioning (OPFOS) microscopy 20 μm 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 [1012]
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 [2,1315]
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  Descriptions and comparisons of several 3D imaging and visualization techniques
Fig.1  HE-stained skin sections with different fiducial markers. A V-shaped groove made by cutting part of the epidermis (A) and mouse sciatic nerves (B). A surgical cotton suture (C) and medical absorbable sutures (D) were used as vertical registration markers through skin specimens. We can clearly observe man-made structural deformations (A, B) and missing suture fibers (C, D). The shapes of the markers vary dramatically between adjacent slices.
Fig.2  Flow diagram for image registration.

Step 1: Feature detection. Manual or automatic detection of salient and distinctive objects, such as edges, contours, line intersections, closed-boundary regions, and corners, etc.

Step 2: Feature matching. Establishing the correspondence between the features detected in both the sensed and reference images.

Step 3: Transform model estimation. Establishing the type and parameters of the mapping functions.

Step 4: Image resampling and transformation. Transforming the sensed image using the mapping functions.

Fig.3  Alignment of adjacent sections from prostatic tissue. Left: HE; Right: p63/AMACR. The arrows link the matching inliers on the two images after rotation and scaling of the right image. In a perfect alignment, the arrows would be parallel. However, this expectation is unrealistic in practice. Cited from Lippolis et al.’s Ref. [42], with permission from BioMed Central.
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)
Tab.2  Comparison of rigid registration and non-rigid registration
Fig.4  Transverse section of the follicular unit at the largest dimension of the sebaceous gland. Blue margin, sebaceous lobules located in the angular position; yellow margin, sebaceous lobules located in the counter-angular position. APM, arrector pili muscle; HF, hair follicle; SG, sebaceous gland. Masson’s trichrome stain. Scale bar= 200 μm. Cited from Song et al.’s Ref. [26], with permission from John Wiley and Sons.
Segmentation algorithm Classification Applications
Based on thresholds Edge-based algorithms Wavelet transform, Canny edge detection [53], Sobel edge detection, and Laplacian edge detection
Region-based algorithms Region growing algorithms [54]
Hybrid algorithms Watershed algorithms [55]
Based on clustering techniques Supervised classification algorithms 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  Algorithms for medical image segmentation
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)
4 Rat liver 15 μm/146 Liquid nitrogen Glucose-6-phosphatase (G6Pase)histochemical staining Glucose-6-phosphatase (G6Pase) Histol (Germany)
5 Duck lung 0.3 μm/194 2.5% glutaraldehyde solution Toluidene blue stain Air capillaries (ACs) and blood capillaries (BCs) Corel Photopaint V.08? (Corel Corporation)
Tab.4  Applications of 3D reconstruction
Fig.5  Reconstructed three-hair follicular units. (a1, b1, and c1) Lateral views; (a2, b2, and c2) superior oblique views; (a3, b3, and c3) superior views. Blue, hair follicles; red, arrector pili muscle; yellow, sebaceous gland. Cited from Song et al.’s Ref. [26], with permission from John Wiley and Sons.
Fig.6  Reconstructions of a 3D lymphatic capillary network of human lower limb skin specimens using five individually stained 5 mm serial sections with podoplanin. The reconstructed lymphatic vessels are shown in yellow. Cited from Wu et al.’s Ref. [63], with permission from John Wiley and Sons.
Fig.7  (A) Transection of the median nerve at the place where the median nerve passed through the pronator teres. Among the 17 fascicles, six motor fascicles, six sensory fascicles, and five mixed fascicles can be found. (B) 3D visualization of a segment of the median nerve at this site. The direction of the arrow is from proximal to distal of the median nerve. Red represents the sensory fascicles; yellow represents the motor fascicles; and green represents the mixed fascicles. Cited from Sun et al.’s Ref. [64], with permission from John Wiley and Sons.
Fig.8  3D reconstruction of the secondary parenchymal unit and draining central venular tree. (A) Front view of the secondary unit. (B) Back view. Numerals indicate the primary units that are color-coded. Portal tracts are marked in red (p1, p2, and p3). (C) Front view of the draining central venular tree. (D) Back view. Numerals indicate the different central venular branches that are color-coded to correspond to the primary units. The stem of the central venular tree empties into a sublobular vein (sv). Cited from Teutsch et al.’s Ref. [65], with permission from John Wiley and Sons.
Fig.9  (A, B) Integrated (combined) reconstruction of the blood vessels (red) and airways (blue) (A) and that of the vasculature (B): the area of the reconstruction is close to the parabronchial lumen. Labels are similar to show the topographic locations of the same structures. AC, air capillary; BC, blood capillary; If, infundibulae; stars, points at which ACs interconnect. Evidently, the ACs and BCs are not mirror images. Scale bar, 10 μm. (C, D) Structure of the ACs. The ACs are heterogeneous, rather rotund structures that anastomose openly or via narrow tubules (stars). The spaces between the ACs are almost completely filled by BCs. If, infundibulum. (D) An AC and interconnection (star) are delineated with dashed lines. Scale bars: (C) 20 μm; (D) 10 μm. Cited from Woodward et al.’s Ref.[25], with permission from John Wiley and Sons.
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