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Keywords = serial block-face imaging

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18 pages, 5307 KiB  
Article
Image Segmentation-Based Oilseed Rape Row Detection for Infield Navigation of Agri-Robot
by Guoxu Li, Feixiang Le, Shuning Si, Longfei Cui and Xinyu Xue
Agronomy 2024, 14(9), 1886; https://doi.org/10.3390/agronomy14091886 - 23 Aug 2024
Cited by 7 | Viewed by 1215
Abstract
The segmentation and extraction of oilseed rape crop rows are crucial steps in visual navigation line extraction. Agricultural autonomous navigation robots face challenges in path recognition in field environments due to factors such as complex crop backgrounds and varying light intensities, resulting in [...] Read more.
The segmentation and extraction of oilseed rape crop rows are crucial steps in visual navigation line extraction. Agricultural autonomous navigation robots face challenges in path recognition in field environments due to factors such as complex crop backgrounds and varying light intensities, resulting in poor segmentation and slow detection of navigation lines in oilseed rape crops. Therefore, this paper proposes VC-UNet, a lightweight semantic segmentation model that enhances the U-Net model. Specifically, VGG16 replaces the original backbone feature extraction network of U-Net, Convolutional Block Attention Module (CBAM) are integrated at the upsampling stage to enhance focus on segmentation targets. Furthermore, channel pruning of network convolution layers is employed to optimize and accelerate the model. The crop row trapezoidal ROI regions are delineated using end-to-end vertical projection methods with serialized region thresholds. Then, the centerline of oilseed rape crop rows is fitted using the least squares method. Experimental results demonstrate an average accuracy of 94.11% for the model and an image processing speed of 24.47 fps/s. After transfer learning for soybean and maize crop rows, the average accuracy reaches 91.57%, indicating strong model robustness. The average yaw angle deviation of navigation line extraction is 3.76°, with a pixel average offset of 6.13 pixels. Single image transmission time is 0.009 s, ensuring real-time detection of navigation lines. This study provides upper-level technical support for the deployment of agricultural robots in field trials. Full article
(This article belongs to the Collection Advances of Agricultural Robotics in Sustainable Agriculture 4.0)
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20 pages, 4756 KiB  
Article
A Rapid Parallel Mosaicking Algorithm for Massive Remote Sensing Images Utilizing Read Filtering
by Pei Nie, Zhenqi Cui and Yaping Wan
Remote Sens. 2023, 15(19), 4863; https://doi.org/10.3390/rs15194863 - 7 Oct 2023
Cited by 2 | Viewed by 2856
Abstract
Mosaicking is a crucial step in the application of remote sensing images. The amount of remote sensing image data has grown rapidly, along with the expansion of observed areas and increased image resolution. As a result, traditional serial mosaicking techniques are facing significant [...] Read more.
Mosaicking is a crucial step in the application of remote sensing images. The amount of remote sensing image data has grown rapidly, along with the expansion of observed areas and increased image resolution. As a result, traditional serial mosaicking techniques are facing significant challenges. In recent times, various studies have utilized high-performance computing to hasten image mosaicking and attain favorable outcomes. Nevertheless, the current research only accelerates mosaicking through external technology, without optimizing from the perspective of algorithm flow, which introduces unnecessary data I/O and slows down the mosaicking. This paper introduces a rapid parallel remote sensing image mosaicking algorithm utilizing read filtering. To begin with, the target images are divided into blocks and stored in a distributed file system. Subsequently, the image blocks are read and filtered based on a designated input format. Finally, the overlapping and non-overlapping areas are read and processed asynchronously, reducing the data I/O and computing overhead, thereby improving the efficiency of parallel computing. The experiments indicate that the mosaicking algorithm introduced in this paper enhances throughput and speedup by an average of 1.38 MB/S and 0.87 relative to the current techniques, respectively, concerning various datasets and cores. This study provides a theoretical foundation and novel ideas for processing remote sensing images on cluster platforms. Full article
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13 pages, 5931 KiB  
Article
Cell–Cell and Cell–Matrix Interactions at the Presumptive Stem Cell Niche of the Chick Corneal Limbus
by Kiranjit K. Bains, Robert D. Young, Elena Koudouna, Philip N. Lewis and Andrew J. Quantock
Cells 2023, 12(19), 2334; https://doi.org/10.3390/cells12192334 - 22 Sep 2023
Cited by 1 | Viewed by 1546
Abstract
(1) Background: Owing to its ready availability and ease of acquisition, developing chick corneal tissue has long been used for research purposes. Here, we seek to ascertain the three-dimensional microanatomy and spatiotemporal interrelationships of the cells (epithelial and stromal), extracellular matrix, and vasculature [...] Read more.
(1) Background: Owing to its ready availability and ease of acquisition, developing chick corneal tissue has long been used for research purposes. Here, we seek to ascertain the three-dimensional microanatomy and spatiotemporal interrelationships of the cells (epithelial and stromal), extracellular matrix, and vasculature at the corneo-scleral limbus as the site of the corneal stem cell niche of the chicken eye. (2) Methods: The limbus of developing (i.e., embryonic days (E) 16 and 18, just prior to hatch) and mature chicken eyes was imaged using scanning electron microscopy (SEM), transmission electron microscopy (TEM), and the volume electron microscopy technique, serial-block face SEM (SBF-SEM), the latter technique allowing us to generate three-dimensional reconstructions from data sets of up to 1000 serial images; (3) Results: Data revealed that miniature limbal undulations of the embryonic basement membrane, akin to Palisades of Vogt (PoV), matured into distinct invaginations of epithelial cells that extended proximally into a vascularized limbal stroma. Basal limbal epithelial cells, moreover, occasionally exhibited a high nuclear:cytoplasmic ratio, which is a characteristic feature of stem cells. SBF-SEM identified direct cell–cell associations between corneal epithelial and stromal cells at the base of structures akin to limbal crypts (LCs), with cord-like projections of extracellular matrix extending from the basal epithelial lamina into the subjacent stroma, where they made direct contact with stomal cells in the immature limbus. (4) Conclusion: Similarities with human tissue suggest that the corneal limbus of the mature chicken eye is likely the site of a corneal stem cell niche. The ability to study embryonic corneas pre-hatch, where we see characteristic niche-like features emerge, thus provides an opportunity to chart the development of the limbal stem cell niche of the cornea. Full article
(This article belongs to the Special Issue Cell Biology of the Cornea and Ocular Surface)
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19 pages, 12830 KiB  
Article
Biomechanics of the JCT and SC Inner Wall Endothelial Cells with Their Basement Membrane Using 3D Serial Block-Face Scanning Electron Microscopy
by Alireza Karimi, Reza Razaghi, Mary J. Kelley, Ted S. Acott and Haiyan Gong
Bioengineering 2023, 10(9), 1038; https://doi.org/10.3390/bioengineering10091038 - 4 Sep 2023
Cited by 7 | Viewed by 1956
Abstract
Background: More than ~70% of the aqueous humor exits the eye through the conventional aqueous outflow pathway that is comprised of the trabecular meshwork (TM), juxtacanalicular tissue (JCT), the inner wall endothelium of Schlemm’s canal (SC). The flow resistance in the JCT and [...] Read more.
Background: More than ~70% of the aqueous humor exits the eye through the conventional aqueous outflow pathway that is comprised of the trabecular meshwork (TM), juxtacanalicular tissue (JCT), the inner wall endothelium of Schlemm’s canal (SC). The flow resistance in the JCT and SC inner wall basement membrane is thought to play an important role in the regulation of the intraocular pressure (IOP) in the eye, but current imaging techniques do not provide enough information about the mechanics of these tissues or the aqueous humor in this area. Methods: A normal human eye was perfusion-fixed and a radial wedge of the TM tissue from a high-flow region was dissected. The tissues were then sliced and imaged using serial block-face scanning electron microscopy. Slices from these images were selected and segmented to create a 3D finite element model of the JCT and SC cells with an inner wall basement membrane. The aqueous humor was used to replace the intertrabecular spaces, pores, and giant vacuoles, and fluid–structure interaction was employed to couple the motion of the tissues with the aqueous humor. Results: Higher tensile stresses (0.8-kPa) and strains (25%) were observed in the basement membrane beneath giant vacuoles with open pores. The volumetric average wall shear stress was higher in SC than in JCT/SC. As the aqueous humor approached the inner wall basement membrane of SC, the velocity of the flow decreased, resulting in the formation of small eddies immediately after the flow left the inner wall. Conclusions: Improved modeling of SC and JCT can enhance our understanding of outflow resistance and funneling. Serial block-face scanning electron microscopy with fluid–structure interaction can achieve this, and the observed micro-segmental flow patterns in ex vivo perfused human eyes suggest a hypothetical mechanism. Full article
(This article belongs to the Section Biomechanics and Sports Medicine)
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7 pages, 1991 KiB  
Communication
Estimation of Nanoporous Au Young’s Modulus from Serial Block Face-SEM 3D-Characterisation
by Michele Brun, Elisa Sogne, Andrea Falqui, Federico Scaglione, Paola Rizzi, Francesco Delogu and Giorgio Pia
Materials 2022, 15(10), 3644; https://doi.org/10.3390/ma15103644 - 19 May 2022
Viewed by 1925
Abstract
Nanoporous Au has been subjected to serial block face-scanning electron microscopy (SBF-SEM) 3D-characterisation. Corresponding sections have been digitalized and used to evaluate the associated mechanical properties. Our investigation demonstrates that the sample is homogeneous and isotropic. The effective Young’s modulus estimated by an [...] Read more.
Nanoporous Au has been subjected to serial block face-scanning electron microscopy (SBF-SEM) 3D-characterisation. Corresponding sections have been digitalized and used to evaluate the associated mechanical properties. Our investigation demonstrates that the sample is homogeneous and isotropic. The effective Young’s modulus estimated by an analytical multiscale approach agrees remarkably well with the values stated in the literature. Full article
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14 pages, 4283 KiB  
Review
3D Ultrastructural Imaging of Chromosomes Using Serial Block-Face Scanning Electron Microscopy (SBFSEM)
by Mohammed Yusuf, Atiqa Sajid, Ian K. Robinson and El-Nasir Lalani
DNA 2022, 2(1), 30-43; https://doi.org/10.3390/dna2010003 - 5 Feb 2022
Cited by 5 | Viewed by 5096
Abstract
To date, our understanding of how DNA is packaged in the cell nucleus, condensed from chromatin into chromosomes, and organized throughout the cell cycle remains sparse. Three dimensional (3D) ultrastructural imaging is an important tool for unravelling the organizational structure of chromosomes. For [...] Read more.
To date, our understanding of how DNA is packaged in the cell nucleus, condensed from chromatin into chromosomes, and organized throughout the cell cycle remains sparse. Three dimensional (3D) ultrastructural imaging is an important tool for unravelling the organizational structure of chromosomes. For large volume 3D imaging of biological samples, serial block-face scanning electron microscopy (SBFSEM) has been applied, whereby ultrastructural information is achieved by analyzing 3D reconstructions acquired from measured data sets. In this review, we summarize the contribution of SBFSEM for obtaining 3D images of chromosomes to investigate their ultrastructure and organization in the cell and its nucleus. Furthermore, this review highlights the potential of SBFSEM for advancing 3D chromosome research. Full article
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16 pages, 7019 KiB  
Article
Nuclear Fragility in Radiation-Induced Senescence: Blebs and Tubes Visualized by 3D Electron Microscopy
by Benjamin M. Freyter, Mutaz A. Abd Al-razaq, Anna Isermann, Anne Dietz, Omid Azimzadeh, Liesbeth Hekking, Maria Gomolka and Claudia E. Rübe
Cells 2022, 11(2), 273; https://doi.org/10.3390/cells11020273 - 13 Jan 2022
Cited by 15 | Viewed by 4098
Abstract
Irreparable DNA damage following ionizing radiation (IR) triggers prolonged DNA damage response and induces premature senescence. Cellular senescence is a permanent state of cell-cycle arrest characterized by chromatin restructuring, altered nuclear morphology and acquisition of secretory phenotype, which contributes to senescence-related inflammation. However, [...] Read more.
Irreparable DNA damage following ionizing radiation (IR) triggers prolonged DNA damage response and induces premature senescence. Cellular senescence is a permanent state of cell-cycle arrest characterized by chromatin restructuring, altered nuclear morphology and acquisition of secretory phenotype, which contributes to senescence-related inflammation. However, the mechanistic connections for radiation-induced DNA damage that trigger these senescence-associated hallmarks are poorly understood. In our in vitro model of radiation-induced senescence, mass spectrometry-based proteomics was combined with high-resolution imaging techniques to investigate the interrelations between altered chromatin compaction, nuclear envelope destabilization and nucleo-cytoplasmic chromatin blebbing. Our findings confirm the general pathophysiology of the senescence-response, with disruption of nuclear lamin organization leading to extensive chromatin restructuring and destabilization of the nuclear membrane with release of chromatin fragments into the cytosol, thereby activating cGAS-STING-dependent interferon signaling. By serial block-face scanning electron microscopy (SBF-SEM) whole-cell datasets were acquired to investigate the morphological organization of senescent fibroblasts. High-resolution 3-dimensional (3D) reconstruction of the complex nuclear shape allows us to precisely visualize the segregation of nuclear blebs from the main nucleus and their fusion with lysosomes. By multi-view 3D electron microscopy, we identified nanotubular channels formed in lamin-perturbed nuclei of senescent fibroblasts; the potential role of these nucleo-cytoplasmic nanotubes for expulsion of damaged chromatin has to be examined. Full article
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16 pages, 9076 KiB  
Article
Protocols for Generating Surfaces and Measuring 3D Organelle Morphology Using Amira
by Edgar Garza-Lopez, Zer Vue, Prasanna Katti, Kit Neikirk, Michelle Biete, Jacob Lam, Heather K. Beasley, Andrea G. Marshall, Taylor A. Rodman, Trace A. Christensen, Jeffrey L. Salisbury, Larry Vang, Margaret Mungai, Salma AshShareef, Sandra A. Murray, Jianqiang Shao, Jennifer Streeter, Brian Glancy, Renata O. Pereira, E. Dale Abel and Antentor Hintonadd Show full author list remove Hide full author list
Cells 2022, 11(1), 65; https://doi.org/10.3390/cells11010065 - 27 Dec 2021
Cited by 39 | Viewed by 8793 | Correction
Abstract
High-resolution 3D images of organelles are of paramount importance in cellular biology. Although light microscopy and transmission electron microscopy (TEM) have provided the standard for imaging cellular structures, they cannot provide 3D images. However, recent technological advances such as serial block-face scanning electron [...] Read more.
High-resolution 3D images of organelles are of paramount importance in cellular biology. Although light microscopy and transmission electron microscopy (TEM) have provided the standard for imaging cellular structures, they cannot provide 3D images. However, recent technological advances such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion beam scanning electron microscopy (FIB-SEM) provide the tools to create 3D images for the ultrastructural analysis of organelles. Here, we describe a standardized protocol using the visualization software, Amira, to quantify organelle morphologies in 3D, thereby providing accurate and reproducible measurements of these cellular substructures. We demonstrate applications of SBF-SEM and Amira to quantify mitochondria and endoplasmic reticulum (ER) structures. Full article
(This article belongs to the Special Issue 10th Anniversary of Cells—Advances in Cell Techniques)
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21 pages, 10810 KiB  
Review
Field-Emission Scanning Electron Microscope as a Tool for Large-Area and Large-Volume Ultrastructural Studies
by Bogdan Lewczuk and Natalia Szyryńska
Animals 2021, 11(12), 3390; https://doi.org/10.3390/ani11123390 - 27 Nov 2021
Cited by 34 | Viewed by 7681
Abstract
The development of field-emission scanning electron microscopes for high-resolution imaging at very low acceleration voltages and equipped with highly sensitive detectors of backscattered electrons (BSE) has enabled transmission electron microscopy (TEM)-like imaging of the cut surfaces of tissue blocks, which are impermeable to [...] Read more.
The development of field-emission scanning electron microscopes for high-resolution imaging at very low acceleration voltages and equipped with highly sensitive detectors of backscattered electrons (BSE) has enabled transmission electron microscopy (TEM)-like imaging of the cut surfaces of tissue blocks, which are impermeable to the electron beam, or tissue sections mounted on the solid substrates. This has resulted in the development of methods that simplify and accelerate ultrastructural studies of large areas and volumes of biological samples. This article provides an overview of these methods, including their advantages and disadvantages. The imaging of large sample areas can be performed using two methods based on the detection of transmitted electrons or BSE. Effective imaging using BSE requires special fixation and en bloc contrasting of samples. BSE imaging has resulted in the development of volume imaging techniques, including array tomography (AT) and serial block-face imaging (SBF-SEM). In AT, serial ultrathin sections are collected manually on a solid substrate such as a glass and silicon wafer or automatically on a tape using a special ultramicrotome. The imaging of serial sections is used to obtain three-dimensional (3D) information. SBF-SEM is based on removing the top layer of a resin-embedded sample using an ultramicrotome inside the SEM specimen chamber and then imaging the exposed surface with a BSE detector. The steps of cutting and imaging the resin block are repeated hundreds or thousands of times to obtain a z-stack for 3D analyses. Full article
(This article belongs to the Special Issue Microscopic Structure Research in Animals)
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16 pages, 12595 KiB  
Article
Attention Enhanced Serial Unet++ Network for Removing Unevenly Distributed Haze
by Wenxuan Zhao, Yaqin Zhao, Liqi Feng and Jiaxi Tang
Electronics 2021, 10(22), 2868; https://doi.org/10.3390/electronics10222868 - 22 Nov 2021
Cited by 8 | Viewed by 3136
Abstract
The purpose of image dehazing is the reduction of the image degradation caused by suspended particles for supporting high-level visual tasks. Besides the atmospheric scattering model, convolutional neural network (CNN) has been used for image dehazing. However, the existing image dehazing algorithms are [...] Read more.
The purpose of image dehazing is the reduction of the image degradation caused by suspended particles for supporting high-level visual tasks. Besides the atmospheric scattering model, convolutional neural network (CNN) has been used for image dehazing. However, the existing image dehazing algorithms are limited in face of unevenly distributed haze and dense haze in real-world scenes. In this paper, we propose a novel end-to-end convolutional neural network called attention enhanced serial Unet++ dehazing network (AESUnet) for single image dehazing. We attempt to build a serial Unet++ structure that adopts a serial strategy of two pruned Unet++ blocks based on residual connection. Compared with the simple Encoder–Decoder structure, the serial Unet++ module can better use the features extracted by encoders and promote contextual information fusion in different resolutions. In addition, we take some improvement measures to the Unet++ module, such as pruning, introducing the convolutional module with ResNet structure, and a residual learning strategy. Thus, the serial Unet++ module can generate more realistic images with less color distortion. Furthermore, following the serial Unet++ blocks, an attention mechanism is introduced to pay different attention to haze regions with different concentrations by learning weights in the spatial domain and channel domain. Experiments are conducted on two representative datasets: the large-scale synthetic dataset RESIDE and the small-scale real-world datasets I-HAZY and O-HAZY. The experimental results show that the proposed dehazing network is not only comparable to state-of-the-art methods for the RESIDE synthetic datasets, but also surpasses them by a very large margin for the I-HAZY and O-HAZY real-world dataset. Full article
(This article belongs to the Topic Machine and Deep Learning)
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15 pages, 6462 KiB  
Protocol
Contrast-Enhanced Tissue Processing of Fibrillin-Rich Elastic Fibres for 3D Visualization by Volume Scanning Electron Microscopy
by Philip N. Lewis, Robert D. Young, R. B. Souza, Andrew J. Quantock and Keith M. Meek
Methods Protoc. 2021, 4(3), 56; https://doi.org/10.3390/mps4030056 - 15 Aug 2021
Cited by 6 | Viewed by 2749
Abstract
Elastic fibres constitute an important component of the extracellular matrix and currently are the subject of intensive study in order to elucidate their assembly, function and involvement in cell–matrix interactions and disease. However, few studies to date have investigated the 3D architecture of [...] Read more.
Elastic fibres constitute an important component of the extracellular matrix and currently are the subject of intensive study in order to elucidate their assembly, function and involvement in cell–matrix interactions and disease. However, few studies to date have investigated the 3D architecture of the elastic fibre system in bulk tissue. We describe a protocol for preparation of tissue samples, including primary fixation and backscatter electron contrast-enhancement steps, through dehydration into stable resin-embedded blocks for volume electron microscopy. The use of low molecular weight tannic acid and alcoholic lead staining are critical stages in this procedure. Block preparation by ultramicrotomy and evaporative metal coating prior to microscopical examination are also described. We present images acquired from serial block face scanning electron microscopy of cornea and aorta showing target structures clearly differentiated from cells and other matrix components. The processing method imparts high contrast to fibrillin-containing elastic fibres, thus facilitating their segmentation and rendering into 3D reconstructions by image analysis software from large serial image datasets. Full article
(This article belongs to the Section Tissue Engineering and Organoids)
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16 pages, 4788 KiB  
Article
Ultra-Structural Imaging Provides 3D Organization of 46 Chromosomes of a Human Lymphocyte Prophase Nucleus
by Atiqa Sajid, El-Nasir Lalani, Bo Chen, Teruo Hashimoto, Darren K. Griffin, Archana Bhartiya, George Thompson, Ian K. Robinson and Mohammed Yusuf
Int. J. Mol. Sci. 2021, 22(11), 5987; https://doi.org/10.3390/ijms22115987 - 1 Jun 2021
Cited by 5 | Viewed by 5690
Abstract
Three dimensional (3D) ultra-structural imaging is an important tool for unraveling the organizational structure of individual chromosomes at various stages of the cell cycle. Performing hitherto uninvestigated ultra-structural analysis of the human genome at prophase, we used serial block-face scanning electron microscopy (SBFSEM) [...] Read more.
Three dimensional (3D) ultra-structural imaging is an important tool for unraveling the organizational structure of individual chromosomes at various stages of the cell cycle. Performing hitherto uninvestigated ultra-structural analysis of the human genome at prophase, we used serial block-face scanning electron microscopy (SBFSEM) to understand chromosomal architectural organization within 3D nuclear space. Acquired images allowed us to segment, reconstruct, and extract quantitative 3D structural information about the prophase nucleus and the preserved, intact individual chromosomes within it. Our data demonstrate that each chromosome can be identified with its homolog and classified into respective cytogenetic groups. Thereby, we present the first 3D karyotype built from the compact axial structure seen on the core of all prophase chromosomes. The chromosomes display parallel-aligned sister chromatids with familiar chromosome morphologies with no crossovers. Furthermore, the spatial positions of all 46 chromosomes revealed a pattern showing a gene density-based correlation and a neighborhood map of individual chromosomes based on their relative spatial positioning. A comprehensive picture of 3D chromosomal organization at the nanometer level in a single human lymphocyte cell is presented. Full article
(This article belongs to the Special Issue Cytomolecular Organisation of the Nuclear Genome)
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22 pages, 53242 KiB  
Article
Volumetric Semantic Instance Segmentation of the Plasma Membrane of HeLa Cells
by Cefa Karabağ, Martin L. Jones and Constantino Carlos Reyes-Aldasoro
J. Imaging 2021, 7(6), 93; https://doi.org/10.3390/jimaging7060093 - 1 Jun 2021
Cited by 6 | Viewed by 4219
Abstract
In this work, an unsupervised volumetric semantic instance segmentation of the plasma membrane of HeLa cells as observed with serial block face scanning electron microscopy is described. The resin background of the images was segmented at different slices of a 3D stack of [...] Read more.
In this work, an unsupervised volumetric semantic instance segmentation of the plasma membrane of HeLa cells as observed with serial block face scanning electron microscopy is described. The resin background of the images was segmented at different slices of a 3D stack of 518 slices with 8192 × 8192 pixels each. The background was used to create a distance map, which helped identify and rank the cells by their size at each slice. The centroids of the cells detected at different slices were linked to identify them as a single cell that spanned a number of slices. A subset of these cells, i.e., the largest ones and those not close to the edges were selected for further processing. The selected cells were then automatically cropped to smaller regions of interest of 2000 × 2000 × 300 voxels that were treated as cell instances. Then, for each of these volumes, the nucleus was segmented, and the cell was separated from any neighbouring cells through a series of traditional image processing steps that followed the plasma membrane. The segmentation process was repeated for all the regions of interest previously selected. For one cell for which the ground truth was available, the algorithm provided excellent results in Accuracy (AC) and the Jaccard similarity Index (JI): nucleus: JI =0.9665, AC =0.9975, cell including nucleus JI =0.8711, AC =0.9655, cell excluding nucleus JI =0.8094, AC =0.9629. A limitation of the algorithm for the plasma membrane segmentation was the presence of background. In samples with tightly packed cells, this may not be available. When tested for these conditions, the segmentation of the nuclear envelope was still possible. All the code and data were released openly through GitHub, Zenodo and EMPIAR. Full article
(This article belongs to the Special Issue 2020 Selected Papers from Journal of Imaging Editorial Board Members)
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10 pages, 4396 KiB  
Article
Cell Volume (3D) Correlative Microscopy Facilitated by Intracellular Fluorescent Nanodiamonds as Multi-Modal Probes
by Neeraj Prabhakar, Ilya Belevich, Markus Peurla, Xavier Heiligenstein, Huan-Cheng Chang, Cecilia Sahlgren, Eija Jokitalo and Jessica M. Rosenholm
Nanomaterials 2021, 11(1), 14; https://doi.org/10.3390/nano11010014 - 23 Dec 2020
Cited by 6 | Viewed by 4014
Abstract
Three-dimensional correlative light and electron microscopy (3D CLEM) is attaining popularity as a potential technique to explore the functional aspects of a cell together with high-resolution ultrastructural details across the cell volume. To perform such a 3D CLEM experiment, there is an imperative [...] Read more.
Three-dimensional correlative light and electron microscopy (3D CLEM) is attaining popularity as a potential technique to explore the functional aspects of a cell together with high-resolution ultrastructural details across the cell volume. To perform such a 3D CLEM experiment, there is an imperative requirement for multi-modal probes that are both fluorescent and electron-dense. These multi-modal probes will serve as landmarks in matching up the large full cell volume datasets acquired by different imaging modalities. Fluorescent nanodiamonds (FNDs) are a unique nanosized, fluorescent, and electron-dense material from the nanocarbon family. We hereby propose a novel and straightforward method for executing 3D CLEM using FNDs as multi-modal landmarks. We demonstrate that FND is biocompatible and is easily identified both in living cell fluorescence imaging and in serial block-face scanning electron microscopy (SB-EM). We illustrate the method by registering multi-modal datasets. Full article
(This article belongs to the Special Issue Application of Nanomaterials in Biomedical Imaging and Cancer Therapy)
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17 pages, 20520 KiB  
Article
Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy
by Cefa Karabağ, Martin L. Jones, Christopher J. Peddie, Anne E. Weston, Lucy M. Collinson and Constantino Carlos Reyes-Aldasoro
J. Imaging 2019, 5(9), 75; https://doi.org/10.3390/jimaging5090075 - 12 Sep 2019
Cited by 15 | Viewed by 7442
Abstract
This paper describes an unsupervised algorithm, which segments the nuclear envelope of HeLa cells imaged by Serial Block Face Scanning Electron Microscopy. The algorithm exploits the variations of pixel intensity in different cellular regions by calculating edges, which are then used to generate [...] Read more.
This paper describes an unsupervised algorithm, which segments the nuclear envelope of HeLa cells imaged by Serial Block Face Scanning Electron Microscopy. The algorithm exploits the variations of pixel intensity in different cellular regions by calculating edges, which are then used to generate superpixels. The superpixels are morphologically processed and those that correspond to the nuclear region are selected through the analysis of size, position, and correspondence with regions detected in neighbouring slices. The nuclear envelope is segmented from the nuclear region. The three-dimensional segmented nuclear envelope is then modelled against a spheroid to create a two-dimensional (2D) surface. The 2D surface summarises the complex 3D shape of the nuclear envelope and allows the extraction of metrics that may be relevant to characterise the nature of cells. The algorithm was developed and validated on a single cell and tested in six separate cells, each with 300 slices of 2000 × 2000 pixels. Ground truth was available for two of these cells, i.e., 600 hand-segmented slices. The accuracy of the algorithm was evaluated with two similarity metrics: Jaccard Similarity Index and Mean Hausdorff distance. Jaccard values of the first/second segmentation were 93%/90% for the whole cell, and 98%/94% between slices 75 and 225, as the central slices of the nucleus are more regular than those on the extremes. Mean Hausdorff distances were 9/17 pixels for the whole cells and 4/13 pixels for central slices. One slice was processed in approximately 8 s and a whole cell in 40 min. The algorithm outperformed active contours in both accuracy and time. Full article
(This article belongs to the Special Issue Medical Image Understanding and Analysis 2018)
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