Shape Variables Research Articles

GENERAL STRUCTURE AND PRINCIPLES OF MORPHOMETRIC ANALYSIS OF GREATER OMENTUM IN WHITE RATS

The greater omentum is an organ belonging to the peripheral part of the immune system as it contains specialized lymphoid structures, known as milky spots. Moreover, the greater omentum plays an important role in the process of renewal and maintaining the quantitative constancy of the peritoneal fluid. According to the literature, the greater omentum of white rats in its main morphological features (in miniature) is homologous compared to a human one. The purpose of the study is to investigate the general structure and the principles of morphometric analysis of the greater omentum in white rats. Materials and methods. The experiment involved 15 white male rats of reproductive age, weighing from 278.08 to 346.47 g. After vivisection, carried out by an overdose of thiopental-sodium anesthesia, the abdominal cavity was opened providing an access to a complete examination of the internal organs in their natural positions; we took photographs and started a direct study of the greater omentum. Results and discussion. During a general examination of the contents of the peritoneal cavity of 15 test animals, we found out the greater omentum was not always present in its typical form; in 3 cases, it was hidden between the loops of the small intestine. Linear measurements of the size of the greater omentum were performed, the data obtained as a result of studying the corresponding sample of animals, were plotted in a frame of rectangular coordinates along the abscissa and ordinate axes, respectively; on the graph, they were visualized with parallel lines, and a visual diagram of the individual variability of the area of the greater omentum was obtained. Conclusion. When studying the greater omentum of a certain quantitative sample in white rats, it may turn out that in some cases it will be in a latent form, located mainly among the loops of the small intestine. The greater omentum of white rats is characterized by significant individual variability in shape and size that is not amenable to strict metric analysis, especially when determining its area, which is the main indicator of its surface contact with the peritoneal fluid, and, consequently, with its antigenic composition.

On the Micro-Foundations of Creative Economy: Life Satisfaction and Social Identity

Incorporating the unavoidable changes manifesting in the behavior of individuals as an outcome of evolution at the level of development of the economy and society, we pinpoint a new theoretical background requiring the reconfiguring of the micro-foundations of economic theory regarding the creative economy. We thus set the theoretical micro-foundations of the creative economy where the main microeconomic incentive lies in life satisfaction attainment rather than utility maximization. At the macroeconomic level, we propose the pairing of sustainability with the creative economy. The objective is met through the vehicle of social identity derived from the responses to a questionnaire distributed in Greek society. Through principal components analysis, we locate two sets of variables shaping life satisfaction: the exogenous influences within social identity (state of health, age, and level of education) and the endogenous primary influences within social identity (lending, cultural change, and happiness). Each one of these variables is determined by other interpretative variables. Furthermore, we observe a weakness of economic policy to influence life satisfaction in advanced Western societies, resulting in a paradox of the economic toolkit. Our findings are relevant for policymaking to promote life satisfaction, especially within the creative economy context.

Size, layout and tendon profile optimization of prestressed steel trusses using Jaya algorithm

Depending on the increasing raw material costs in the construction area, it is becoming more and more significant to design the structures using minimum materials. For steel systems, where raw material prices are relatively higher than reinforced concrete structures, prestressing is one of the factors that can reduce the cost. Therefore, this study aims to cost optimization of prestressed steel trusses, considering the size and shape variables, simultaneously. It is assumed in the study that the prestressing force is applied via a tendon settled under the bottom chord and shaped with deviators. The cross-sections of the truss elements and deviators are size variables; on the other hand, the layout of the truss beam and the profile of the prestressing tendon are the shape variables. Discrete and continuous values are preferred for the size and shape variables, respectively. Strength, slenderness, and displacement are considered as the constraints in the design of prestressed steel trusses, depending on the different prestress loss conditions. The Jaya, a popular metaheuristic algorithm, is used for the optimization procedure. As numerical examples, the optimization of trusses with different spans and shapes is conducted. The results achieved are compared with those of the non-prestressed trusses and the results in the literature. It is observed that the prestressing, especially thanks to shape variables used, provides a considerable cost saving in the optimum design of steel trusses.

Subtitusi Mocaf Pada Donat Kentang: Apakah berpengaruh Terhadap Daya Terima Konsumen?

This research purpose to find attributes that influence the selection potato donuts made from mocaf and find out the consumer's attitude towards potato donuts made from mocaf. Total respondents in this research are 30 people who had ever bought and ate potato donuts. The respondents were taken by purposive sampling. The methods used in this research is survey methods. The data analysis in this research is using Fishbein Model, the model applied is “the attitude toward object model”. It’s model were used to identify consumer attitudes towards the attributes potato donuts from mocaf and raw material includes taste, texture, shape, color and price suitability. The results show that the most influential attributes in the selection potato donuts made from mocaf are taste (13,74) and color (15,89). Consumer attitudes towards the overall attributes potato donuts are ordinary product. This study recommends potato donut producers to make improvements to the variables of texture, shape and price suitability from consumer input so that it becomes a potato donut product that is preferred by consumers.

Habitat selection and density of common pheasant (Phasianus colchicus) in Northern Italy: effects of land use cover and landscape configuration

Knowing the ecology of game species is important to define sustainable hunting pressure and to plan management actions aimed to maintain viable populations. Common pheasant (Phasianus colchicus) is one of the main gamebird species in Europe and North America, despite its native range extending from the Caucasus to Eastern China. This research aimed to define the environmental variables shaping the spatial distribution of male pheasants and to estimate their breeding density in an agroecosystem of northern Italy. During the breeding season, 2015, we carried out 372 point counts with unlimited distances, randomly placed following a stratified sampling survey design. The habitat requirements of the pheasant were evaluated following a presence vs. availability approach, using environmental variables related to land use cover and landscape configuration. We built generalized linear models with a binary distribution, selecting variables following an information-theoretic approach. Densities were estimated through both conventional and multiple-covariate distance sampling. We estimated a density of 1.45 males/km2, with 4.26 males/km2 in suitable areas and 0.91 males/km2 in unsuitable ones. We found pheasants in areas with meadows and tree plantations, which were used to find food and refuges from predators and bad weather conditions. Similarly, woodlands have a positive effect on species occurrence, whereas arable lands were avoided, specifically maize and paddy fields. We found little evidence that landscape configuration affects pheasant occurrence. We found pheasants to be negatively affected by the length of edges between woodlands and arable lands, whereas edges between woodlands and grasslands seem to be beneficial for the species. These findings could help landscape and wildlife managers to plan habitat improvement actions useful to maintain self-sustaining populations of this species, by increasing cover of woodlands, meadows, and tree plantations.

Male ant reproductive investment in a seasonal wet tropical forest: Consequences of future climate change.

Tropical forests sustain many ant species whose mating events often involve conspicuous flying swarms of winged gynes and males. The success of these reproductive flights depends on environmental variables and determines the maintenance of local ant diversity. However, we lack a strong understanding of the role of environmental variables in shaping the phenology of these flights. Using a combination of community-level analyses and a time-series model on male abundance, we studied male ant phenology in a seasonally wet lowland rainforest in the Panama Canal. The male flights of 161 ant species, sampled with 10 Malaise traps during 58 consecutive weeks (from August 2014 to September 2015), varied widely in number (mean = 9.8 weeks, median = 4, range = 1 to 58). Those species abundant enough for analysis (n = 97) flew mainly towards the end of the dry season and at the start of the rainy season. While litterfall, rain, temperature, and air humidity explained community composition, the time-series model estimators elucidated more complex patterns of reproductive investment across the entire year. For example, male abundance increased in weeks when maximum daily temperature increased and in wet weeks during the dry season. On the contrary, male abundance decreased in periods when rain receded (e.g., at the start of the dry season), in periods when rain fell daily (e.g., right after the beginning of the wet season), or when there was an increase in the short-term rate of litterfall (e.g., at the end of the dry season). Together, these results suggest that the BCI ant community is adapted to the dry/wet transition as the best timing of reproductive investment. We hypothesize that current climate change scenarios for tropical regions with higher average temperature, but lower rainfall, may generate phenological mismatches between reproductive flights and the adequate conditions needed for a successful start of the colony.

The role of intangible resources in shaping the financial potential of high technology enterprises on the example of CD Projekt SA

Motivation: As a result of economic changes over the last few decades, the structure of enterprise resources has changed significantly. Therefore, their development potential is concentrated on intangible resources. A reflection of these changes is the emergence of the Resource-Based View of the Firm (RBV) which has its roots in the works of scientists such as: J.A. Schumpeter, A. Marshall, or E.H. Chamberlin. The importance of the resource theory is mainly based on the technological potential, people’s knowledge or the improvement of management techniques.
 Aim: The aim of the article is to propose a method for assessing the strength and direction of the impact of intangible resources on the financial potential of high-tech enterprises. In the article, as a case study, the impact of intangible resources on the financial potential of CD Projekt SA was presented. from the high-technology industry (Section C, subclass 26.20.) in 2011–2019. The choice of the company as the research object was primarily determined by the type of business activity, the high position of the enterprise among the fastest growing companies and a significant share of intangible resources.
 Results: To achieve the aim of the article, the soft modeling method was used which allows to study the relationship between directly unobservable variables. In the constructed soft model, two unobservable (hidden) variables constituting the internal model were adopted: intangible resources (IR) and financial potential (FP). Hidden variables were defined based on the potential set of indicators (observable variables). Specification of the model of the soft impact of intangible resources on the financial result of high-tech enterprises based on the concept of the resource theory. Identification of the most important variables shaping the intangible resources of high technology enterprises, their impact on the financial potential of enterprises, together with the analysis of the dynamics of changes. Defining proposals for recommendations for high-tech companies based on the results of empirical research.

VARIANT ANATOMY OF TRANSITIONAL OCCLUSION DENTAL ARCH AT OPTIMAL OCCLUSAL RELATIONSHIPS

Through the transitional bite period, the variability of the dental arch shape and size is due to the replacement of milk teeth with permanent ones, which feature different odontometric values. The aim of this study was to identify the main linear and angular parameters of dental arches, in view of the trusive position of the incisors with optimal functional occlusion. A stratified study was involved 76 children ages 8–12 years old, who were divided into three groups (protrusive, retrusive and mesotrusive dental arches). An analysis of cone-beam computed tomograms and plaster models of jaws was carried out, which was preceded by obtaining informed consents according to the Ethics Committee requirements. The study revealed certain features of the variant anatomy of transitional occlusion dental arch. The calculated factors allowed identifying the proportionality of the dental arch parameters to odontometric indicators. During that, the dental-diagonal factor (the ratio of the dental arch length to the incisor-molar diagonals) for the upper jaw was 1.06±0.01, for the lower arch being equal to 1.09±0.01, in all types of dental arches, which is a fact to be used in clinical orthography to predict the location of the dental arch incisor (central) point in case of shape anomalies, specifically in the anterior part. The angular parameters of the diagnostic dental pentagon will allow simulating the geometric and graphical construction of arches through the transitional occlusion period.

A Three-Dimensional Finite Element Analysis Model of SAW Torque Sensor with Multilayer Structure

A three-dimensional finite element analysis model of surface acoustic wave (SAW) torque sensor based on multilayer structure is proposed in this paper. Compared with the traditional saw torque sensor with quartz as piezoelectric substrate, the SAW torque sensor with multilayer structure has the advantages of fast propagation speed and high characteristic frequency. It is a very promising torque sensor, but there is very little related research. In order to successfully develop the sensor, it is essential to understand the propagation characteristics and torque sensing mode of SAW in multilayer structure. Therefore, in this study, we first established a multi-layered finite element analysis model of SAW device based on IDT/128° Y-X lithium niobate/diamond/Si (100). Then, the effects of different film thicknesses on the characteristic frequency, electromechanical coupling coefficient, s parameter, and mechanical quality factor of SAW device without changing the wavelength are analyzed. Then, based on the finite element analysis, a three-dimensional research model of a new SAW torque sensor suitable for small diameter torsion bar (d = 10 mm) is established, and the relationship between saw device deformation and torque under the condition of small torque (±40 Nm) is tested. The shape variable is introduced into the finite element analysis model of multi-layer SAW device. Finally, the relationship between saw torque sensor with multi-layer structure and torque is established by using the deformation relationship, which shows the perfect curve of sensor performance.

A Composite Flexible Sensor for Direct Ventricular Assist Device.

A direct ventricular assist device is one of the effective means to treat patients with heart failure; the key point of the problem is the flexible sensor that can measure the drive pressure and shape variable of the heart auxiliary device. This study was based on the high-voltage electric field guidance process and the porous foaming process, and designed an implantable resistance/capacitive composite flexible sensor that can effectively detect the pressure and deformation signal caused by fine surface contact and pneumatic muscle expansion. Experiments showed the performance of composite sensors with special structure design was greatly improved compared with the control group—the strain measurement sensitivity was 22, pressure measurement sensitivity was up to 0.19 Kpa−1. Stable strain measurements were made up to 35 times and pressure measurements over 100 times. In addition, we solved the interference problem of resistance/capacitance flexible sensors through an optimized common substrate process. Finally, we tested a pneumatic muscle direct ventricular assist device with a composite flexible sensor on a model heart; the experiment showed that this resistance/capacitive composite flexible sensor can effectively detect surface contact with pneumatic muscle and the displacement signals.

Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates

Abstract. A novel method of comparison between an atmospheric model and satellite probabilistic estimates of relative humidity (RH) in the tropical atmosphere is presented. The method is developed to assess the Météo-France numerical weather forecasting model ARPEGE (Action de Recherche Petite Echelle Grande Echelle) using probability density functions (PDFs) of RH estimated from the SAPHIR (Sondeur Atmosphérique du Profil d'Humidité Intertropicale par Radiométrie) microwave sounder. The satellite RH reference is derived by aggregating footprint-scale probabilistic RH to match the spatial and temporal resolution of ARPEGE over the April–May–June 2018 period. The probabilistic comparison is discussed with respect to a classical deterministic comparison confronting each model RH value to the reference average and using a set confidence interval. This study first documents the significant spatial and temporal variability in the reference distribution spread and shape. We demonstrate the need for a finer assessment at the individual case level to characterize specific situations beyond the classical bulk comparison using determinist “best” reference estimates. The probabilistic comparison allows for a more contrasted assessment than the deterministic one. Specifically, it reveals cases where the ARPEGE-simulated values falling within the deterministic confidence range actually correspond to extreme departures in the reference distribution, highlighting the shortcomings of the too-common Gaussian assumption of the reference, on which most current deterministic comparison methods are based.

Identifying a Novel Critical Access Difficulty Factor in Percutaneous Radiofrequency Rhizotomy for Trigeminal Neuralgia: Pterygoid Process Ridge.

Percutaneous stereotactic radiofrequency rhizotomy (PSR) is an ablative procedure for trigeminal neuralgia (TN). The anatomic structures that pass through, or around, the foramen ovale (FO) play vital roles in the success rate of PSR. The presence of a variant pterygoid process ridge (PPR) obscuring the FO renders the cannulation procedure difficult but had not been described in the literature before. To identify the variations of the PPR to assess cannulation difficulty. Fifty seven FOs of 57 patients with TN (TN group) and 438 FOs of 232 patients without TN (non-TN group) were analyzed using 3-dimensional computed tomography reconstruction images of cranial bases. Three-dimensional printer models were also used for TN patients with PPR-obscured FOs. Measurements were obtained for shape, size, and morphometric variability effect on cannulation. We identified 5 PPR-obscured FOs (8.8%) in the TN group and 32 FOs (7.3%) in the non-TN group. In the TN group, the transverse diameter obstruction ranged from 19.2% to 39.7% in 4 patients, and 1 case was 100%. Of particular note, approximately one-quarter to one-third of FO preset targets were affected by PPR. A PPR-obscured FO represents a new confounding factor in the conduct of PSR. Confirming the PPR-obscured FO is a critical step in improving the effectiveness of puncture target presetting, ie, evaluating the target with actual FO data is an improvement over the use of surgical view FO data. Discernment of the PPR can improve the success rate of difficult-to-access FO punctures, thereby rendering PSR more effective.

Global soil microbiomes: A new frontline of biome‐ecology research

AbstractAimOrganisms on our planet form spatially congruent and functionally distinct communities, which at large geographical scales are called “biomes”. Understanding their pattern and function is vital for sustainable use and protection of biodiversity. Current global terrestrial biome classifications are based primarily on climate characteristics and functional aspects of plant community assembly. These and other existing biome schemes do not take account of soil organisms, including highly diverse and functionally important microbial groups. We aimed to define large‐scale structure in the diversity of soil microbes (soil microbiomes), pinpoint the environmental drivers shaping it and identify resemblance and mismatch with existing terrestrial biome schemes.LocationGlobal.Time periodCurrent.Major taxa studiedSoil eukaryotes and prokaryotes.MethodsWe collected soil samples from natural environments world‐wide, incorporating most known terrestrial biomes. We used high‐throughput sequencing to characterize soil biotic communities and k‐means clustering to define soil microbiomes describing the diversity of microbial eukaryotic and prokaryotic groups. We used climatic data and soil variables measured in the field to identify the environmental variables shaping soil microbiome structure.ResultsWe recorded strong correlations among fungal, bacterial, archaeal, plant and animal communities, defined a system of global soil microbiomes (producing seven biome types for microbial eukaryotes and six biome types for prokaryotes) and showed that these are typically structured by pH alongside temperature. None of the soil microbiomes are directly paralleled by any current terrestrial biome scheme, with mismatch most substantial for prokaryotes and for microbial eukaryotes in cold climates; nor do they consistently distinguish grassland and forest ecosystems.Main conclusionsExisting terrestrial biome classifications represent a limited surrogate for the large‐scale diversity patterns of microbial soil organisms. We show that empirically defined soil microbiomes are attainable using metabarcoding and statistical clustering approaches and suggest that they can have wide application in theoretical and applied biodiversity research.

The N-Link Swimmer in Three Dimensions: Controllability and Optimality Results

The controllability of a fully three-dimensional N-link swimmer is studied. After deriving the equations of motion in a low Reynolds number fluid by means of Resistive Force Theory, the controllability of the minimal 2-link swimmer is tackled using techniques from Geometric Control Theory. The shape of the 2-link swimmer is described by two angle parameters. It is shown that the associated vector fields that govern the dynamics generate, via taking their Lie brackets, all eight linearly independent directions in the combined configuration and shape space, leading to controllability; the swimmer can move from any starting configuration and shape to any target configuration and shape by operating on the two shape variables. The result is subsequently extended to the N-link swimmer. Finally, the minimal time optimal control problem and the minimization of the power expended are addressed and a qualitative description of the optimal strategies is provided.

Automated Particle Shape Identification and Quantification for DEM Simulation of Rockfill Materials in Subgrade Construction

Rockfill materials, conducted by impermeable stone, are frequently used in subgrade construction projects. The irregularity and variability of particle shape are demonstrated to affect the mechanical properties of rockfill subgrade, such as void ratio and coordination number. This study first identifies the subgrade rockfill particle contour by machine learning algorithms, including AdaBoost, Cascade, and sliding windows. Then, the shape evaluation indexes of length flatness, edge angle, and roughness are quantified, and the statistical analysis of each index is presented. In addition, the discrete element method (DEM) simulation is implemented on the compaction of rockfill subgrade to explore the impact of roundness on characteristics of particles. Finally, the macroanalysis on the void ratio and cumulative settlement and the microanalysis on particle coordination number, rotation momentum, and displacement are studied. The results illustrate that roundness has a significant effect on the mechanical characteristics of subgrade rockfill materials. With the increase of rolling passes, the porosity of packing decreases, whereas the settlement increases gradually. The change rate starts fast and ends slowly.

Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved via a Warping Strategy.

Brain mapping studies often need to identify brain structures or functional circuits into a set of individual brains. To this end, multiple atlases have been published to represent such structures based on different modalities, subject sets, and techniques. The mainstream approach to exploit these atlases consists in spatially deforming each individual data onto a given atlas using dense deformation fields, which supposes the existence of a continuous mapping between atlases and individuals. However, this continuity is not always verified, and this “iconic” approach has limits. We present in this study an alternative, complementary, “structural” approach, which consists in extracting structures from the individual data, and comparing them without deformation. A “structural atlas” is thus a collection of annotated individual data with a common structure nomenclature. It may be used to characterize structure shape variability across individuals or species, or to train machine learning systems. This study exhibits Anatomist, a powerful structural 3D visualization software dedicated to building, exploring, and editing structural atlases involving a large number of subjects. It has been developed primarily to decipher the cortical folding variability; cortical sulci vary enormously in both size and shape, and some may be missing or have various topologies, which makes iconic approaches inefficient to study them. We, therefore, had to build structural atlases for cortical sulci, and use them to train sulci identification algorithms. Anatomist can display multiple subject data in multiple views, supports all kinds of neuroimaging data, including compound structural object graphs, handles arbitrary coordinate transformation chains between data, and has multiple display features. It is designed as a programming library in both C++ and Python languages, and may be extended or used to build dedicated custom applications. Its generic design makes all the display and structural aspects used to explore the variability of the cortical folding pattern work in other applications, for instance, to browse axonal fiber bundles, deep nuclei, functional activations, or other kinds of cortical parcellations. Multimodal, multi-individual, or inter-species display is supported, and adaptations to large scale screen walls have been developed. These very original features make it a unique viewer for structural atlas browsing.

New periodograms separating orbital radial velocities and spectral shape variation

We present new periodograms that are effective in distinguishing Doppler shift from spectral shape variability in astronomical spectra. These periodograms, building upon the concept of partial distance correlation, separate the periodic radial velocity modulation induced by orbital motion from that induced by stellar activity. These tools can be used to explore large spectroscopic databases in search of targets in which spectral shape variations obscure the orbital motion; such systems include active planet-hosting stars or binary systems with an intrinsically variable component. We provide a detailed prescription for calculating the periodograms, demonstrate their performance via simulations and real-life case studies, and provide a public Python implementation.

Characterization of surface motion patterns in highly deformable soft tissue organs from dynamic MRI: An application to assess 4D bladder motion

Background and objectives: Dynamic Magnetic Resonance Imaging (MRI) may capture temporal anatomical changes in soft tissue organs with high-contrast but the obtained sequences usually suffer from limited volume coverage which makes the high-resolution reconstruction of organ shape trajectories a major challenge in temporal studies. Because of the variability of abdominal organ shapes across time and subjects, the objective of the present study is to go towards 3D dense velocity measurements to fully cover the entire surface and to extract meaningful features characterizing the observed organ deformations and enabling clinical action or decision.Methods: We present a pipeline for characterization of bladder surface dynamics during deep respiratory movements. For a compact shape representation, the reconstructed temporal volumes were first used to establish subject-specific dynamical 4D mesh sequences using the large deformation diffeomorphic metric mapping (LDDMM) framework. Then, we performed a statistical characterization of organ dynamics from mechanical parameters such as mesh elongations and distortions. Since we refer to organs as non-flat surfaces, we have also used the mean curvature change as metric to quantify surface evolution. However, the numerical computation of curvature is strongly dependant on the surface parameterization (i.e. the mesh resolution). To cope with this dependency, we employed a non-parametric method for surface deformation analysis. Independent of parameterization and minimizing the length of the geodesic curves, it stretches smoothly the surface curves towards a sphere by minimizing a Dirichlet energy. An Eulerian PDE approach is used to derive a shape descriptor from the curve-shortening flow. Intercorrelations between individuals’ motion patterns are computed using the Laplace-Beltrami Operator (LBO) eigenfunctions for spherical mapping.Results: Application to extracting characterization correlation curves for locally-controlled simulated shape trajectories demonstrates the stability of the proposed shape descriptor. Its usability was shown on MRI acquired for seven healthy participants for which the bladder was highly deformed by maximum of inspiration. As expected, the study showed that deformations occured essentially on the top lateral regions.Conclusion:Promising results were obtained, showing the organ in its 3D complexity during deformation due to strain conditions. Smooth genus-0 manifold reconstruction from sparse dynamic MRI data is employed to perform a statistical shape analysis for the determination of bladder deformation.

Instance segmentation of biological images using graph convolutional network

Instance segmentation in biological images is an important task in the field of biological images and biomedical analysis. Different from the instance segmentation of natural image scenes, this task is still challenging because there are a large number of overlapping objects with similar appearance as well as great variability in shape, size and texture in the foreground and background. In this paper, we propose a novel method for segmentation of graph-guided instances of biological images, which successfully addresses these peculiarities. Our method predicts the embedding at each pixel and uses clustering to recover instances during testing. Specifically, we design the Graph-guided Feature Fusion Module in response to overlapping instances. Our Graph-guided Feature Fusion Module combines fine deep features and coarse shallow features to learn the affinity matrix, and then uses graph convolutional network to guide the network to learn object-level local features. Next, we devise the Gated Spatial Attention Module to effectively learn key spatial information by introducing a gating mechanism. Furthermore, we give the Cluster Distance Loss that can effectively distinguish foreground objects from similar backgrounds. The effectiveness of our proposed method has been verified on various biological and biomedical datasets. The experimental results show that our method is superior to previous embedding-based instance segmentation methods. The SBD metric for our method reached 90.8% on the plant phenotype dataset (CVPPP), 72.5% on the cell nucleus dataset (DSB2018), and 81.8% on the C.elegans dataset, all achieving state-of-the-art performance.

Lung Segmentation in CT Images: A Residual U-Net Approach on a Cross-Cohort Dataset

Lung cancer is one of the most common causes of cancer-related mortality, and since the majority of cases are diagnosed when the tumor is in an advanced stage, the 5-year survival rate is dismally low. Nevertheless, the chances of survival can increase if the tumor is identified early on, which can be achieved through screening with computed tomography (CT). The clinical evaluation of CT images is a very time-consuming task and computed-aided diagnosis systems can help reduce this burden. The segmentation of the lungs is usually the first step taken in image analysis automatic models of the thorax. However, this task is very challenging since the lungs present high variability in shape and size. Moreover, the co-occurrence of other respiratory comorbidities alongside lung cancer is frequent, and each pathology can present its own scope of CT imaging appearances. This work investigated the development of a deep learning model, whose architecture consists of the combination of two structures, a U-Net and a ResNet34. The proposed model was designed on a cross-cohort dataset and it achieved a mean dice similarity coefficient (DSC) higher than 0.93 for the 4 different cohorts tested. The segmentation masks were qualitatively evaluated by two experienced radiologists to identify the main limitations of the developed model, despite the good overall performance obtained. The performance per pathology was assessed, and the results confirmed a small degradation for consolidation and pneumocystis pneumonia cases, with a DSC of 0.9015 ± 0.2140 and 0.8750 ± 0.1290, respectively. This work represents a relevant assessment of the lung segmentation model, taking into consideration the pathological cases that can be found in the clinical routine, since a global assessment could not detail the fragilities of the model.