Confocal DNA cytometry: a contour-based segmentation algorithm for automated three-dimensional image segmentation

BACKGROUND: Confocal laser scanning microscopy (CLSM) presents the opportunity to perform three-dimensional (3D) DNA content measurements on intact cells in thick histological sections. So far, these measurements have been performed manually, which is quite time-consuming. METHODS: In this study, an intuitive contour-based segmentation algorithm for automatic 3D CLSM image cytometry of nuclei in thick histological sections is presented. To evaluate the segmentation algorithm, we measured the DNA content and volume of human liver and breast cancer nuclei in 3D CLSM images. RESULTS: A high percentage of nuclei could be segmented fully automatically (e.g., human liver, 92%). Comparison with (time-consuming) interactive measurements on the same CLSM images showed that the results were well correlated (liver, r = 1.00; breast, r = 0.92). CONCLUSIONS: Automatic 3D CLSM image cytometry enables measurement of volume and DNA content of large numbers of nuclei in thick histological sections within an acceptable time. This makes large-scale studies feasible, whereby the advantages of CLSM can be exploited fully. The intuitive modular segmentation algorithm presented in this study detects and separates overlapping objects, also in two-dimensional (2D) space. Therefore, this algorithm may also be suitable for other applications.     

System for flow sorting chromosomes on the basis of pulse shape

Sorting on the basis of the complex features resolved by chromosome slit-scan analysis requires rapid and flexible pulse shape acquisition and processing for determining sort decisions before droplet breakoff. Fluorescence scans of chromosome morphology contain centromeric index and banding information suitable for chromosome classification, but these scans are often characterized by variability in length and height and require sophisticated data processing procedures for identification. Setting sort criteria on such complex morphological data requires digitization and subsequent computation by an algorithm tolerant of variations in overall pulse shape. We demonstrate here the capability to sort individual chromosomes based on their morphological features measured by slit-scan flow cytometry. To do this we have constructed a sort controller capable of acquiring an 128 byte chromosome waveform and executing a series of numerical computations resulting in an area-based centromeric index sort decision in less than 2 ms. The system is configured in a NOVIX microprocessor, programmed in FORTH, and interfaced to a slit-scan flow cytometer data acquisition system. An advantage of this configuration is direct control over the machine state during program execution for minimal processing time. Examples of flow sorted chromosomes are shown with their corresponding fluorescence pulse shapes.     

Improved SLIC imagine segmentation algorithm based on K-means

Dividing the image into superpixels contributes to further processing of the image. Simple linear iterative clustering (SLIC) algorithm achieves good segmentation result by clustering color and distance characteristics of pixels. However, finite superpixels easily cause under-segmentation. Therefore, the work corrects segmentation result of SLIC by k-means clustering method calculating similarity based on weighted Euclidean distance. After that, the under-segmentation superpixel blocks are conducted with k-means clustering based on binary classification. Result shows that the corrected SLIC segmentation has better visual effect and index.     

Edged watershed segmentation: A semi-interactive algorithm for segmentation of low-resolution maps from electron cryomicroscopy

Electron cryomicroscopy (cryo-EM) allows for the structural analysis of large protein complexes that may be difficult to study by other means. Frequently, maps of complexes from cryo-EM are obtained at resolutions between 10 and 25 Å. To aid in the interpretation of these medium- to low-resolution maps, they may be subdivided into three-dimensional segments representing subunits or subcomplexes. This division is often accomplished using a manual segmentation approach. While extremely useful, manual segmentation is subjective. We have developed a novel semi-interactive segmentation algorithm that can incorporate prior knowledge of subunit composition or structure without biasing the boundaries between subunits or subcomplexes. This algorithm has been characterized with experimental and simulated cryo-EM density maps at resolutions between 10 and 25 Å.     

AMASS: algorithm for MSI analysis by semi-supervised segmentation

Mass Spectrometric Imaging (MSI) is a molecular imaging technique that allows the generation of 2D ion density maps for a large complement of the active molecules present in cells and sectioned tissues. Automatic segmentation of such maps according to patterns of co-expression of individual molecules can be used for discovery of novel molecular signatures (molecules that are specifically expressed in particular spatial regions). However, current segmentation techniques are biased toward the discovery of higher abundance molecules and large segments; they allow limited opportunity for user interaction, and validation is usually performed by similarity to known anatomical features. We describe here a novel method, AMASS (Algorithm for MSI Analysis by Semi-supervised Segmentation). AMASS relies on the discriminating power of a molecular signal instead of its intensity as a key feature, uses an internal consistency measure for validation, and allows significant user interaction and supervision as options. An automated segmentation of entire leech embryo data images resulted in segmentation domains congruent with many known organs, including heart, CNS ganglia, nephridia, nephridiopores, and lateral and ventral regions, each with a distinct molecular signature. Likewise, segmentation of a rat brain MSI slice data set yielded known brain features and provided interesting examples of co-expression between distinct brain regions. AMASS represents a new approach for the discovery of peptide masses with distinct spatial features of expression. Software source code and installation and usage guide are available at http://bix.ucsd.edu/AMASS/ .     

Genetic basis of adaptive shape differences in the cichlid head

East African cichlids exhibit an extraordinary level of morphological diversity. Key to their success has been a dramatic radiation in trophic biology, which has occurred rapidly and repeatedly in different lakes. In this report we take the first step in understanding the genetic basis of differences in cichlid oral jaw design. We estimate the effective number of genetic factors that control differences in the cichlid head through a comprehensive morphological assessment of two Lake Malawi cichlid species and their F(1) and F(2) hybrid progeny. We estimate that between one and 11 factors underlie shape difference of individual bony elements. We show that many of the skeletal differences in the head and oral jaw apparatus are inherited together, suggesting a degree of pleiotropy in the genetic architecture of this character complex. Moreover, we find that cosegregation of shape differences in different elements corresponds to developmental, rather than functional, units.     

FACADE: a fast and sensitive algorithm for the segmentation and calling of high resolution array CGH data

The availability of high resolution array comparative genomic hybridization (CGH) platforms has led to increasing complexities in data analysis. Specifically, defining contiguous regions of alterations or segmentation can be computationally intensive and popular algorithms can take hours to days for the processing of arrays comprised of hundreds of thousands to millions of elements. Additionally, tumors tend to demonstrate subtle copy number alterations due to heterogeneity, ploidy and hybridization effects. Thus, there is a need for fast, sensitive array CGH segmentation and alteration calling algorithms. Here, we describe Fast Algorithm for Calling After Detection of Edges (FACADE), a highly sensitive and easy to use algorithm designed to rapidly segment and call high resolution array data.     

Axon shape as a basis for multinode functional units in a hierarchical neural model

The ability of animals to perform fixed action patterns and to access information by categories suggests that there are several types of hierarchical organization in the nervous system. This paper employs data about axon shape and neurotransmitter effect to demonstrate the emergence of hierarchical structure in a neural model. Two dimensions of neural classification, axon shape and neurotransmitter effect, are used to generate a five-node-type neural model. Neurons are classified as interneurons, relay cells, and monoamine transmitters on the basis of axon shape; the transmitter classifications include excitatory, inhibitory, and parameter-changing. The five types of nodes in the model correspond to all the biologically observed combinations: excitatory and inhibitory short-range, excitatory and inhibitory long-range-directional, and long-lasting long-range-diffuse nodes. The emergence of multinode functional units (MFUs) from the five-node-type model is mathematically demonstrated. These units correspond to cortical columns anatomically defined by the axon fields of relay cells, and are called columnar multinode functional units (CMFUs). CMFUs may, in turn, be part of larger functional groups designated coherent populations, which consist of widely distributed CMFUs in retinotopically equivalent locations. The existence of coherent populations imposes a three-level hierarchical structure on the model. To represent this hierarchical structure, a new type of CMFU node, which has a set of vector-valued inputs and outputs, is introduced. Each CMFU node contains a system of short-range nodes which supplies it with vector-valued inputs. Sets of long-range-diffuse nodes are also treated as vector-valued nodes whose outputs control the size and number of coherent populations. The role of coherent populations and hierarchical organization in the nervous system is discussed for such cognitive tasks as visual perception, attention and learning. Physiological and behavioral evidence are cited which support the existence of a similar three-level hierarchy in vertebrate brains.     

Adaxial–abaxial polarity: The developmental basis of leaf shape diversity

Leaves of flowering plants are diverse in shape. Part of this morphological diversity can be attributed to differences in spatiotemporal regulation of polarity in the upper (adaxial) and lower (abaxial) sides of developing leaves. In a leaf primordium, antagonistic interactions between polarity determinants specify the adaxial and abaxial domains in a mutually exclusive manner. The patterning of those domains is critical for leaf morphogenesis. In this review, we first summarize the gene networks regulating adaxial–abaxial polarity in conventional bifacial leaves and then discuss how patterning is modified in different leaf type categories. genesis 52:1–18, 2014. © 2013 The Authors. Genesis Published byWiley Periodicals, Inc.     

Whole-organ cell shape analysis reveals the developmental basis of ascidian notochord taper

Here we use in toto imaging together with computational segmentation and analysis methods to quantify the shape of every cell at multiple stages in the development of a simple organ: the notochord of the ascidian Ciona savignyi. We find that cell shape in the intercalated notochord depends strongly on anterior–posterior (AP) position, with cells in the middle of the notochord consistently wider than cells at the anterior or posterior. This morphological feature of having a tapered notochord is present in many chordates. We find that ascidian notochord taper involves three main mechanisms: Planar Cell Polarity (PCP) pathway-independent sibling cell volume asymmetries that precede notochord cell intercalation; the developmental timing of intercalation, which proceeds from the anterior and posterior towards the middle; and the differential rates of notochord cell narrowing after intercalation. A quantitative model shows how the morphology of an entire developing organ can be controlled by this small set of cellular mechanisms.     

Identifying compositionally homogeneous and nonhomogeneous domains within the human genome using a novel segmentation algorithm

It has been suggested that the mammalian genome is composed mainly of long compositionally homogeneous domains. Such domains are frequently identified using recursive segmentation algorithms based on the Jensen–Shannon divergence. However, a common difficulty with such methods is deciding when to halt the recursive partitioning and what criteria to use in deciding whether a detected boundary between two segments is real or not. We demonstrate that commonly used halting criteria are intrinsically biased, and propose IsoPlotter, a parameter-free segmentation algorithm that overcomes such biases by using a simple dynamic halting criterion and tests the homogeneity of the inferred domains. IsoPlotter was compared with an alternative segmentation algorithm, D_JS, using two sets of simulated genomic sequences. Our results show that IsoPlotter was able to infer both long and short compositionally homogeneous domains with low GC content dispersion, whereas D_JS failed to identify short compositionally homogeneous domains and sequences with low compositional dispersion. By segmenting the human genome with IsoPlotter, we found that one-third of the genome is composed of compositionally nonhomogeneous domains and the remaining is a mixture of many short compositionally homogeneous domains and relatively few long ones.     

Image segmentation: a tug-of-war for the eyeball

Separating objects from their background is one of the central abilities of the visual system. Recent evidence has revealed how populations of neurons, some of which have receptive fields with an antagonistic center-surround structure, and some of which do not, might contribute to this ability.     

Exploring the effects of gene dosage on mandible shape in mice as a model for studying the genetic basis of natural variation

Mandible shape in the mouse is a complex trait that is influenced by many genetic factors. However, little is known about the action of single genes on adult mandible shape so far, since most developmentally relevant genes are already required during embryogenesis, i.e., knockouts lead to embryonic death or severe deformations, before the mandible is fully formed. We employ here a geometric morphometric approach to identify subtle phenotypic differences caused by dosage effects of candidate genes. We use mouse strains with specific gene modifications (knockouts and knockins) to compare heterozygous animals with controls from the same stock, which is expected to be equivalent to a change of gene expression of the respective locus. Such differences in expression level are also likely to occur as part of the natural variation. We focus on Bmp pathway genes (Bmp4, its antagonist Noggin, and combinations of Bmp5-7 genotypes), but include also two other developmental control genes suspected to affect mandible development in some way (Egfr and Irf6). In addition, we study the effects of Hoxd13, as well as an extracellular matrix constituent (Col2a1). We find that subtle but significant shape differences are caused by differences in gene dosage of several of these genes. The changes seen for Bmp4 and Noggin are partially compatible with the action of these genes known from birds and fish. We find significant shape changes also for Hoxd13, although this gene has so far only been implicated in skeletal patterning processes of the limbs. Comparing the effect sizes of gene dosage changes to the variation found in natural populations of mice as well as quantitative trait loci (QTL) effects on mandible shape, we find that the effect sizes caused by gene dosage changes are at the lower end of the spectrum of natural variation, but larger than the average additive effects found in QTL studies. We conclude that studying gene dosage effects have the potential to provide new insights into aspects of craniofacial development, variation, and evolution.     

Non-linear cancer classification using a modified radial basis function classification algorithm

Summary This paper proposes a modified radial basis function classification algorithm for non-linear cancer classification. In the algorithm, a modified simulated annealing method is developed and combined with the linear least square and gradient paradigms to optimize the structure of the radial basis function (RBF) classifier. The proposed algorithm can be adopted to perform non-linear cancer classification based on gene expression profiles and applied to two microarray data sets involving various human tumor classes: (1) Normal versus colon tumor; (2) acute myeloid leukemia (AML) versus acute lymphoblastic leukemia (ALL). Finally, accuracy and stability for the proposed algorithm are further demonstrated by comparing with the other cancer classification algorithms.     

A Highlights from MBoC Selection: Cega: a single particle segmentation algorithm to identify moving particles in a noisy system

Improvements to particle tracking algorithms are required to effectively analyze the motility of biological molecules in complex or noisy systems. A typical single particle tracking (SPT) algorithm detects particle coordinates for trajectory assembly. However, particle detection filters fail for data sets with low signal-to-noise levels. When tracking molecular motors in complex systems, standard techniques often fail to separate the fluorescent signatures of moving particles from background signal. We developed an approach to analyze the motility of kinesin motor proteins moving along the microtubule cytoskeleton of extracted neurons using the Kullback-Leibler divergence to identify regions where there are significant differences between models of moving particles and background signal. We tested our software on both simulated and experimental data and found a noticeable improvement in SPT capability and a higher identification rate of motors as compared with current methods. This algorithm, called Cega, for “find the object,” produces data amenable to conventional blob detection techniques that can then be used to obtain coordinates for downstream SPT processing. We anticipate that this algorithm will be useful for those interested in tracking moving particles in complex in vitro or in vivo environments.     

Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for multiple alignment segmentation

Automatic identification of sub-structures in multi-aligned sequences is of great importance for effective and objective structural/functional domain annotation, phylogenetic treeing and other molecular analyses. We present a segmentation algorithm that optimally partitions a given multi-alignment into a set of potentially biologically significant blocks, or segments. This algorithm applies dynamic programming and progressive optimization to the statistical profile of a multi-alignment in order to optimally demarcate relatively homogenous sub-regions. Using this algorithm, a large multi-alignment of eukaryotic 16S rRNA was analyzed. Three types of sequence patterns were identified automatically and efficiently: shared conserved domain; shared variable motif; and rare signature sequence. Results were consistent with the patterns identified through independent phylogenetic and structural approaches. This algorithm facilitates the automation of sequence-based molecular structural and evolutionary analyses through statistical modeling and high performance computation.     

Pattern formation in embryos of the oligochaete annelid Tubifex: cellular basis for segmentation and specification of segmental identity

The embryonic origin of metameric segmentation was examined in the oligochaete Tubifex using lineage tracers. Segments in Tubifex embryos arise from five bilateral pairs of longitudinal coherent columns (bandlets) of primary blast cells which are generated by five bilateral pairs of embryonic stem cells called teloblasts (M, N, O, P and Q). As development proceeds, an initially linear array of blast cells in each ectodermal bandlet gradually changes its shape in a lineage-specific manner. These morphogenetic changes result in the formation of distinct cell clumps, which are separated from the bandlet to serve as segmental elements (SEs). SEs in the N and Q lineages are each comprised of clones of two consecutive primary blast cells. In contrast, in the O and P lineages, individual blast cell clones are distributed across SE boundaries; each SE is a mixture of a part of the preceding anterior clone and a part of the next posterior clone. Morphogenetic events, including segmentation, in an ectodermal bandlet proceed normally in the absence of neighboring ectodermal bandlets. Without the underlying mesoderm, separated SEs fail to space themselves at regular intervals along the anteroposterior axis. It is suggested that ectodermal segmentation in Tubifex consists of two stages; autonomous morphogenesis of each bandlet leading to generation of SEs, and the ensuing mesoderm-dependent alignment of separated SEs. In contrast, metameric segmentation in the mesoderm (M lineage) is a one-step process in that it arises from an initially simple organization (i.e. a linear series) of primary m-blast cells, which individually serve as a founder cell of each segment. The boundary between mesodermal segments is determined autonomously. The results of a set of cell ablation and transplantation experiments, using alkaline phosphatase activity as a biochemical marker for segments VII and VIII suggest that segmental identities in primary m-blast cells are determined according to the genealogical position in the M lineage and that the M teloblast possesses a developmental program through which the sequence of blast cell identities is determined.