Bilateral edge filter: photometrically weighted, discontinuity based edge detection

Semiautomatic contour tracking method for biological object segmentation in thin-section electron microscope images with modified zero DC component-type Gabor wavelets

In electron microscopic image processing, artificial intelligence (AI) is a powerful method for segmentation. Because creating training data remains time-consuming and burdensome, a simple and accurate segmentation tool, which is effective and does not rely on manual drawings, is necessary to create training data for AI and to support immediate image analysis. A Gabor wavelet-based contour tracking method has been devised as a step toward realizing such a tool. Although many papers on Gabor filter-based and Gabor filter bank-based texture segmentations have been published, previous studies did not apply the Gabor wavelet-based method to straightforwardly detect membrane-like ridges and step edges for segmentation because earlier works used a nonzero DC component-type Gabor wavelets. The DC component has a serious flaw in such detection. Although the DC component can be removed by a formula that satisfies the wavelet theory or by a log-Gabor function, this is not practical for the proposed scheme. Herein, we devised modified zero DC component-type Gabor wavelets. The proposed method can practically confine a wavelet within a small image area. This type of Gabor wavelet can appropriately track various contours of organelles appearing in thin-section transmission electron microscope images prepared by the freeze-substitution fixation method. The proposed method not only more accurately tracks ridge and step edge contours but also tracks pattern boundary contours consisting of slightly different image patterns. Simulations verified these results.

It's noisy out there! A review of denoising techniques in cryo-electron tomography

Cryo-electron tomography is the only technique that can provide sub-nanometer resolved images of cell regions or even whole cells, without the need of labeling or staining methods. Technological advances over the past decade in electron microscope stability, cameras, stage precision and software have resulted in faster acquisition speeds and considerably improved resolution. In pursuit of even better image resolution, researchers seek to reduce noise - a crucial factor affecting the reliability of the tomogram interpretation and ultimately limiting the achieved resolution. Sub-tomogram averaging is the method of choice for reducing noise in repetitive objects. However, when averaging is not applicable, a trade-off between reducing noise and conserving genuine image details must be achieved. Thus, denoising is an important process that improves the interpretability of the tomogram not only directly but also by facilitating other downstream tasks, such as segmentation and 3D visualization. Here, I review contemporary denoising techniques for cryo-electron tomography by taking into account noise-specific properties of both reconstruction and detector noise. The outcomes of different techniques are compared, in order to help researchers select the most appropriate for each dataset and to achieve better and more reliable interpretation of the tomograms.

[Progress in filters for denoising cryo-electron microscopy images]

Cryo-electron microscopy (cryo-EM) imaging has the unique potential to bridge the gap between cellular and molecular biology. Therefore, cryo-EM three-dimensional (3D) reconstruction has been rapidly developed in recent several years and applied widely in life science research to reveal the structures of large macromolecular assemblies and cellular complexes, which is critical to understanding their functions at all scales. Although the technical breakthrough in recent years, for example, the introduction of the direct detection device (DDD) camera and the development of cryo-EM software tools, made the three cryo-EM pioneers share the 2017 Nobel Prize, several bottleneck problems still exist that hamper the further increase of the resolution of single-particle reconstruction and hold back the application of in situ subnanometer structure determination by cryo-tomography. Radiation damage is still the key limiting factor in cryo-EM. In order to minimize the radiation damage and preserve as much resolution as possible, the imaging conditions of a low dose and weak contrast make cryo-EM images extremely noisy with very low signal-to-noise ratios (SNR), generally about 0.1. The high noise will obscure the fine details in cryo-EM images or reconstructed maps. Thus, a method to reduce the level of noise and improve the resolution has become an important issue. In this paper, we systematically reviewed and compared some robust filters in the cryo-EM field of two aspects, single-particle analysis (SPA) and cryo-electron tomography (cryo-ET), and especially studied their applications, such as, 3D reconstruction, visualization, structural analysis, and interpretation. Conventional approaches to noise reduction in cryo-EM imaging include the use of Gaussian, median, and bilateral filters, among other means. A Gaussian filter selects an appropriate filter kernel to conduct spatial convolution with a noisy image. Although noise with larger standard deviations in cryo-EM images can be suppressed and satisfactory performance is achieved in certain cases, this filter also blurs the images and over-smooths small-scale image features. This is especially detrimental when precise quantitative information needs to be extracted. Unlike a Gaussian filter, a median filter is based on the order statistics of the image and selects the median intensity in a window of the adjacent pixels to denoise the image. Although this filter is robust to outliers, it suffers from aliasing problems that possibly result in incorrect information for cryo-EM structure interpretation. A bilateral filter is a nonlinear filter that performs spatial weighted averaging and is more selective in the pixels allowing to contribute to the weighted sum, excluding the high frequency noise from the smoothing process. Thus, this filter can be used to smooth out noise while maintaining the edge details, which is similar to an anisotropic diffusion filter, and distinct from a Gaussian filter but its utility will be limited when the SNR of a cryo-EM image is very low. Generally, spatial filtering methods have the disadvantage of losing image resolution when reducing noise. A wavelet transform can exploit the wavelet's natural ability to separate a signal from noise at multiple image scales to allow for joint resolution in both the spatial and frequency domains, and thus has the potential to outperform existing methods. The modified wavelet shrinkage filter we developed can offer a remarkable improvement in image quality with a good compromise between detail preservation and noise smoothing. We expect that our review study on different filters can provide benefits to cryo-EM applications and the interpretation of biological structures.

Finite point sets in recognizing location and orientation of machine parts of complex shapes

In the article, a method of recognizing the position, location and orientation of irregular machine parts with a complex outline of the external contour is suggested. Recognition is performed on the basis of a raster image that has undergone preliminary processing in a vision system. The developed method is based on matching the finite set of points retrieved from the external contour of the classified object. The originality of the approach consists of the form of the object pattern taken into account in determining the degree of similarity to reference objects. The similarity index was defined in the category of fuzzy sets. A cellular automaton has been proposed to generate the outline of the perimeter quickly while simultaneously smoothing it out. The process chain necessary for the recognition function to be implemented has been presented. The developed method has been illustrated with an example related to recognizing the position, location and orientation of a rear wheel pin. The results were compared to the classic Blair-Bliss, Danielsson and Haralick shape coefficients. The sensitivity of the developed method to a change in the scale and rotating the object as well as errors in outlining its edge has been tested. The obtained results confirmed the advantageous features of the developed method, both in the aspect of the recognition quality and the practically viable time of waiting for the results of processing.

RAZA: A Rapid 3D z-crossings algorithm to segment electron tomograms and extract organelles and macromolecules

Resolving the 3D architecture of cells to atomic resolution is one of the most ambitious challenges of cellular and structural biology. Central to this process is the ability to automate tomogram segmentation to identify sub-cellular components, facilitate molecular docking and annotate detected objects with associated metadata. Here we demonstrate that RAZA (Rapid 3D z-crossings algorithm) provides a robust, accurate, intuitive, fast, and generally applicable segmentation algorithm capable of detecting organelles, membranes, macromolecular assemblies and extrinsic membrane protein domains. RAZA defines each continuous contour within a tomogram as a discrete object and extracts a set of 3D structural fingerprints (major, middle and minor axes, surface area and volume), enabling selective, semi-automated segmentation and object extraction. RAZA takes advantage of the fact that the underlying algorithm is a true 3D edge detector, allowing the axes of a detected object to be defined, independent of its random orientation within a cellular tomogram. The selectivity of object segmentation and extraction can be controlled by specifying a user-defined detection tolerance threshold for each fingerprint parameter, within which segmented objects must fall and/or by altering the number of search parameters, to define morphologically similar structures. We demonstrate the capability of RAZA to selectively extract subgroups of organelles (mitochondria) and macromolecular assemblies (ribosomes) from cellular tomograms. Furthermore, the ability of RAZA to define objects and their contours, provides a basis for molecular docking and rapid tomogram annotation.

A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria

Recent studies reveal that mitochondria take substantial responsibility in cellular functions that are closely related to aging diseases caused by degeneration of neurons. These studies emphasize that the membrane and crista morphology of a mitochondrion should receive attention in order to investigate the link between mitochondrial function and its physical structure. Electron microscope tomography (EMT) allows analysis of the inner structures of mitochondria by providing highly detailed visual data from large volumes. Computerized segmentation of mitochondria with minimum manual effort is essential to accelerate the study of mitochondrial structure/function relationships. In this work, we improved and extended our previous attempts to detect and segment mitochondria from transmission electron microcopy (TEM) images. A parabolic arc model was utilized to extract membrane structures. Then, curve energy based active contours were employed to obtain roughly outlined candidate mitochondrial regions. Finally, a validation process was applied to obtain the final segmentation data. 3D extension of the algorithm is also presented in this paper. Our method achieved an average F-score performance of 0.84. Average Dice Similarity Coefficient and boundary error were measured as 0.87 and 14nm respectively.

A 3D image filter for parameter-free segmentation of macromolecular structures from electron tomograms

3D image reconstruction of large cellular volumes by electron tomography (ET) at high (≤ 5 nm) resolution can now routinely resolve organellar and compartmental membrane structures, protein coats, cytoskeletal filaments, and macromolecules. However, current image analysis methods for identifying in situ macromolecular structures within the crowded 3D ultrastructural landscape of a cell remain labor-intensive, time-consuming, and prone to user-bias and/or error. This paper demonstrates the development and application of a parameter-free, 3D implementation of the bilateral edge-detection (BLE) algorithm for the rapid and accurate segmentation of cellular tomograms. The performance of the 3D BLE filter has been tested on a range of synthetic and real biological data sets and validated against current leading filters-the pseudo 3D recursive and Canny filters. The performance of the 3D BLE filter was found to be comparable to or better than that of both the 3D recursive and Canny filters while offering the significant advantage that it requires no parameter input or optimisation. Edge widths as little as 2 pixels are reproducibly detected with signal intensity and grey scale values as low as 0.72% above the mean of the background noise. The 3D BLE thus provides an efficient method for the automated segmentation of complex cellular structures across multiple scales for further downstream processing, such as cellular annotation and sub-tomogram averaging, and provides a valuable tool for the accurate and high-throughput identification and annotation of 3D structural complexity at the subcellular level, as well as for mapping the spatial and temporal rearrangement of macromolecular assemblies in situ within cellular tomograms.

Collagen fibril morphology and mechanical properties of the Achilles tendon in two inbred mouse strains

The relationship between collagen fibril morphology and the functional behavior of tendon tissue has been investigated in numerous experimental studies. Several of these studies suggest that larger fibril radius is a primary determinant of higher tendon stiffness and strength; others have shown that factors apart from fibril radius (such as fibril-fibril interactions) may be critical to improved tendon strength. In the present study, we investigate these factors in two inbred mouse strains that are widely used in skeletal structure-function research: C57BL/6J (B6) and C3H/HeJ (C3H). The aim was to establish a quantitative baseline that will allow one to assess how regulation of tendon extracellular matrix architecture affects tensile mechanical properties. We specifically focused on collagen fibril structure and glycosaminoglycan (GAG) content--the two primary constituents of tendon by dry weight--and their potential functional interactions. For this purpose, Achilles tendons from both groups were tested to failure in tension. Tendon collagen morphology was analyzed from transmission electron microscopy images of tendon sections perpendicular to the longitudinal axis. Our results showed that the two inbred strains are macroscopically similar, but C3H mice have a higher elastic modulus (P < 0.05). Structurally, C3H mice showed a larger collagen fibril radius compared to B6 mice (96 +/- 7 nm and 80 +/- 10 nm respectively). Tendons from C3H mice also showed smaller specific fibril surface (0.015 +/- 0.001 nm nm(-2) vs. 0.017 +/- 0.003 nm nm(-2) in the B6 tendons, P < 0.05), and accordingly a lower concentration of GAGs (0.60 +/- 0.07 microg mg(-1) vs. 0.83 +/- 0.11 microg mg(-1), P < 0.05). As in other studies of tendon structure and function, larger collagen fibril radius appears to be associated with stiffer tendon, but this functional difference could also be attributed to reduced potential surface area exchange between fibrils and the surrounding proteoglycan-rich matrix, in which the hydrophilic GAG side chains may promote inter-fibril sliding. This study provides an architectural and functional baseline for a comparative murine model that can be used to investigate the genetic regulation of tendon biomechanics.

Molecular electron microscopy: state of the art and current challenges

The objective of molecular electron microscopy (EM) is to use electron microscopes to visualize the structure of biological molecules. This Review provides a brief overview of the methods used in molecular EM, their respective strengths and successes, and current developments that promise an even more exciting future for molecular EM in the structural investigation of proteins and macromolecular complexes, studied in isolation or in the context of cells and tissues.