Comparative analysis of tissue reconstruction algorithms for 3D histology.
Ontology highlight
ABSTRACT:
SUBMITTER: Kartasalo K
PROVIDER: S-EPMC6129300 | biostudies-literature | 2018 Sep
REPOSITORIES: biostudies-literature
Publications
Comparative analysis of tissue reconstruction algorithms for 3D histology.
Kartasalo Kimmo K Latonen Leena L Vihinen Jorma J Visakorpi Tapio T Nykter Matti M Ruusuvuori Pekka P
Bioinformatics (Oxford, England) 20180901 17
<h4>Motivation</h4>Digital pathology enables new approaches that expand beyond storage, visualization or analysis of histological samples in digital format. One novel opportunity is 3D histology, where a three-dimensional reconstruction of the sample is formed computationally based on serial tissue sections. This allows examining tissue architecture in 3D, for example, for diagnostic purposes. Importantly, 3D histology enables joint mapping of cellular morphology with spatially resolved omics da ...[more]
Similar Datasets
Project description:3D reconstruction of human brain volumes at high resolution is now possible thanks to advancements in tissue clearing methods and fluorescence microscopy techniques. Analyzing the massive data produced with these approaches requires automatic methods able to perform fast and accurate cell counting and localization. Recent advances in deep learning have enabled the development of various tools for cell segmentation. However, accurate quantification of neurons in the human brain presents specific challenges, such as high pixel intensity variability, autofluorescence, non-specific fluorescence and very large size of data. In this paper, we provide a thorough empirical evaluation of three techniques based on deep learning (StarDist, CellPose and BCFind-v2, an updated version of BCFind) using a recently introduced three-dimensional stereological design as a reference for large-scale insights. As a representative problem in human brain analysis, we focus on a 4-cm3 portion of the Broca's area. We aim at helping users in selecting appropriate techniques depending on their research objectives. To this end, we compare methods along various dimensions of analysis, including correctness of the predicted density and localization, computational efficiency, and human annotation effort. Our results suggest that deep learning approaches are very effective, have a high throughput providing each cell 3D location, and obtain results comparable to the estimates of the adopted stereological design.
| S-EPMC11199592 | biostudies-literature
Project description:BACKGROUND: Finding the genetic causes of quantitative traits is a complex and difficult task. Classical methods for mapping quantitative trail loci (QTL) in miceuse an F2 cross between two strains with substantially different phenotype and an interval mapping method to compute confidence intervals at each position in the genome. This process requires significant resources for breeding and genotyping, and the data generated are usually only applicable to one phenotype of interest. Recently, we reported the application of a haplotype association mapping method which utilizes dense genotyping data across a diverse panel of inbred mouse strains and a marker association algorithm that is independent of any specific phenotype. As the availability of genotyping data grows in size and density, analysis of these haplotype association mapping methods should be of increasing value to the statistical genetics community. RESULTS: We describe a detailed comparative analysis of variations on our marker association method. In particular, we describe the use of inferred haplotypes from adjacent SNPs, parametric and nonparametric statistics, and control of multiple testing error. These results show that nonparametric methods are slightly better in the test cases we study, although the choice of test statistic may often be dependent on the specific phenotype and haplotype structure being studied. The use of multi-SNP windows to infer local haplotype structure is critical to the use of a diverse panel of inbred strains for QTL mapping. Finally, because the marginal effect of any single gene in a complex disease is often relatively small, these methods require the use of sensitive methods for controlling family-wise error. We also report our initial application of this method to phenotypes cataloged in the Mouse Phenome Database. CONCLUSION: The use of inbred strains of mice for QTL mapping has many advantages over traditional methods. However, there are also limitations in comparison to the traditional linkage analysis from F2 and RI lines. Application of these methods requires careful consideration of algorithmic choices based on both theoretical and practical factors. Our findings suggest general guidelines, though a complete evaluation of these methods can only be performed as more genetic data in complex diseases becomes available.
| S-EPMC1409800 | biostudies-other
Project description:A multiscale three-dimensional (3D) virtual histology approach is presented, based on two configurations of propagation phase-contrast X-ray tomography, which have been implemented in close proximity at the GINIX endstation at the beamline P10/PETRA?III (DESY, Hamburg, Germany). This enables the 3D reconstruction of characteristic morphological features of human pancreatic normal and tumor tissue, as obtained from cancer surgery, first in the form of a large-scale overview by parallel-beam illumination, followed by a zoom into a region-of-interest based on zoom tomography using a Kirkpatrick-Baez mirror with additional waveguide optics. To this end 1?mm punch biopsies of the tissue were taken. In the parallel tomography, a volumetric throughput on the order of 0.01?mm3?s-1 was achieved, while maintaining the ability to segment isolated cells. With a continuous rotation during the scan, a total acquisition time of less than 2?min was required for a full tomographic scan. Using the combination of both setups, islets of Langerhans, a three-dimensional cluster of cells in the endocrine part of the pancreas, could be located. Cells in such an islet were segmented and visualized in 3D. Further, morphological alterations of tumorous tissue of the pancreas were characterized. To this end, the anisotropy parameter ?, based on intensity gradients, was used in order to quantify the presence of collagen fibers within the entire biopsy specimen. This proof-of-concept experiment of the multiscale approach on human pancreatic tissue paves the way for future 3D virtual pathology.
| S-EPMC7642968 | biostudies-literature
Project description:A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness.
| S-EPMC4764584 | biostudies-literature
Project description:Evaluating the quality of reconstructed images requires consistent approaches to extracting information and applying metrics. Partitioning medical images into tissue types permits the quantitative assessment of regions that contain a specific tissue. The assessment facilitates the evaluation of an imaging algorithm in terms of its ability to reconstruct the properties of various tissue types and identify anomalies. Microwave tomography is an imaging modality that is model-based and reconstructs an approximation of the actual internal spatial distribution of the dielectric properties of a breast over a reconstruction model consisting of discrete elements. The breast tissue types are characterized by their dielectric properties, so the complex permittivity profile that is reconstructed may be used to distinguish different tissue types. This manuscript presents a robust and flexible medical image segmentation technique to partition microwave breast images into tissue types in order to facilitate the evaluation of image quality. The approach combines an unsupervised machine learning method with statistical techniques. The key advantage for using the algorithm over other approaches, such as a threshold-based segmentation method, is that it supports this quantitative analysis without prior assumptions such as knowledge of the expected dielectric property values that characterize each tissue type. Moreover, it can be used for scenarios where there is a scarcity of data available for supervised learning. Microwave images are formed by solving an inverse scattering problem that is severely ill-posed, which has a significant impact on image quality. A number of strategies have been developed to alleviate the ill-posedness of the inverse scattering problem. The degree of success of each strategy varies, leading to reconstructions that have a wide range of image quality. A requirement for the segmentation technique is the ability to partition tissue types over a range of image qualities, which is demonstrated in the first part of the paper. The segmentation of images into regions of interest corresponding to various tissue types leads to the decomposition of the breast interior into disjoint tissue masks. An array of region and distance-based metrics are applied to compare masks extracted from reconstructed images and ground truth models. The quantitative results reveal the accuracy with which the geometric and dielectric properties are reconstructed. The incorporation of the segmentation that results in a framework that effectively furnishes the quantitative assessment of regions that contain a specific tissue is also demonstrated. The algorithm is applied to reconstructed microwave images derived from breasts with various densities and tissue distributions to demonstrate the flexibility of the algorithm and that it is not data-specific. The potential for using the algorithm to assist in diagnosis is exhibited with a tumor tracking example. This example also establishes the usefulness of the approach in evaluating the performance of the reconstruction algorithm in terms of its sensitivity and specificity to malignant tissue and its ability to accurately reconstruct malignant tissue.
| S-EPMC8321253 | biostudies-literature
Project description:The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.
| S-EPMC5471289 | biostudies-literature
Project description:BACKGROUND: Next-generation sequencing (NGS) offers a unique opportunity for high-throughput genomics and has potential to replace Sanger sequencing in many fields, including de-novo sequencing, re-sequencing, meta-genomics, and characterisation of infectious pathogens, such as viral quasispecies. Although methodologies and software for whole genome assembly and genome variation analysis have been developed and refined for NGS data, reconstructing a viral quasispecies using NGS data remains a challenge. This application would be useful for analysing intra-host evolutionary pathways in relation to immune responses and antiretroviral therapy exposures. Here we introduce a set of formulae for the combinatorial analysis of a quasispecies, given a NGS re-sequencing experiment and an algorithm for quasispecies reconstruction. We require that sequenced fragments are aligned against a reference genome, and that the reference genome is partitioned into a set of sliding windows (amplicons). The reconstruction algorithm is based on combinations of multinomial distributions and is designed to minimise the reconstruction of false variants, called in-silico recombinants. RESULTS: The reconstruction algorithm was applied to error-free simulated data and reconstructed a high percentage of true variants, even at a low genetic diversity, where the chance to obtain in-silico recombinants is high. Results on empirical NGS data from patients infected with hepatitis B virus, confirmed its ability to characterise different viral variants from distinct patients. CONCLUSIONS: The combinatorial analysis provided a description of the difficulty to reconstruct a quasispecies, given a determined amplicon partition and a measure of population diversity. The reconstruction algorithm showed good performance both considering simulated data and real data, even in presence of sequencing errors.
| S-EPMC3022557 | biostudies-literature
Project description:Many community detection algorithms have been developed to uncover the mesoscopic properties of complex networks. However how good an algorithm is, in terms of accuracy and computing time, remains still open. Testing algorithms on real-world network has certain restrictions which made their insights potentially biased: the networks are usually small, and the underlying communities are not defined objectively. In this study, we employ the Lancichinetti-Fortunato-Radicchi benchmark graph to test eight state-of-the-art algorithms. We quantify the accuracy using complementary measures and algorithms' computing time. Based on simple network properties and the aforementioned results, we provide guidelines that help to choose the most adequate community detection algorithm for a given network. Moreover, these rules allow uncovering limitations in the use of specific algorithms given macroscopic network properties. Our contribution is threefold: firstly, we provide actual techniques to determine which is the most suited algorithm in most circumstances based on observable properties of the network under consideration. Secondly, we use the mixing parameter as an easily measurable indicator of finding the ranges of reliability of the different algorithms. Finally, we study the dependency with network size focusing on both the algorithm's predicting power and the effective computing time.
| S-EPMC4967864 | biostudies-other
Project description:BackgroundOne of the main aims of phylogenomics is the reconstruction of objects defined in the leaves along the whole phylogenetic tree to minimize the specified functional, which may also include the phylogenetic tree generation. Such objects can include nucleotide and amino acid sequences, chromosomal structures, etc. The structures can have any set of linear and circular chromosomes, variable gene composition and include any number of paralogs, as well as any weights of individual evolutionary operations to transform a chromosome structure. Many heuristic algorithms were proposed for this purpose, but there are just a few exact algorithms with low (linear, cubic or similar) polynomial computational complexity among them to our knowledge. The algorithms naturally start from the calculation of both the distance between two structures and the shortest sequence of operations transforming one structure into another. Such calculation per se is an NP-hard problem.ResultsA general model of chromosomal structure rearrangements is considered. Exact algorithms with almost linear or cubic polynomial complexities have been developed to solve the problems for the case of any chromosomal structure but with certain limitations on operation weights. The computer programs are tested on biological data for the problem of mitochondrial or plastid chromosomal structure reconstruction. To our knowledge, no computer programs are available for this model.ConclusionsExactness of the proposed algorithms and such low polynomial complexities were proved. The reconstructed evolutionary trees of mitochondrial and plastid chromosomal structures as well as the ancestral states of the structures appear to be reasonable.
| S-EPMC4717669 | biostudies-literature
Project description:INTRODUCTION:Kinorhyncha is a clade of marine invertebrate meiofauna. Their body plan includes a retractable introvert bearing rings of cuticular spines, and a limbless trunk with distinct segmentation of nervous, muscular and epidermal organ systems. As derived members within the basal branch of Ecdysozoa, kinorhynchs may provide an important example of convergence on the evolution of segmentation within one of three bilaterian superclades. We describe the myoanatomy of Echinoderes, the most specious kinorhynch genus, and build upon historical studies of kinorhynch ultrastructure and gross morphology. This is the first multi-species comparison of a complete organ system by confocal microscopy and three-dimensional reconstruction within Kinorhyncha. RESULTS:Myoanatomy of adult Echinoderes is composed of the following: Head with two mouth cone circular muscles, nine pairs of oral style muscles, ten introvert retractors, one introvert circular muscle, and fourteen introvert circular muscle retractors; Neck with one circular muscle; Trunk showing distinct pairs of ventral and dorsal muscles within segments 1-10, dorsoventral muscles within segments 3-10, diagonal muscles within segments 1-8, longitudinal fibers spanning segments 1-9, three pairs of terminal spine muscles, and one pair of male penile spine muscles; Gut showing a pharynx with ten alternating rings of radial and circular muscle fibers enclosed in a complex sheath of protractors and retractors, an orthogonal grid of longitudinal and circular fibers surrounding the intestine, and paired hindgut dilators. CONCLUSIONS:Myoanatomy is highly conserved between species of Echinoderes. Interspecific variation is observed in the arrangement and number of introvert fibers and the composition of pharyngeal muscles. Segmented trunk musculature facilitates the movements of articulated cuticular plates along the anterior-posterior axis. Intersegmental muscle fibers assist with dorsoventral and lateral trunk movements. Protractors, retractors and circular muscles coordinate eversion and retraction of the introvert and mouth cone, and relocation of the pharynx during locomotion and feeding behaviors. Pairs of posterior fibers suggest independent movements of terminal spines, and male penile spines. Within Scalidophora, myoanatomy is more similar between Kinorhyncha and Loricifera, than either group is to Priapulida. Kinorhynch myoanatomy may reflect a convergent transition from vermiform to segmented body plans during the early radiation of Ecdysozoa.
| S-EPMC4021568 | biostudies-literature