scholarly journals MorphoGraphX: A platform for quantifying morphogenesis in 4D

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Pierre Barbier de Reuille ◽  
Anne-Lise Routier-Kierzkowska ◽  
Daniel Kierzkowski ◽  
George W Bassel ◽  
Thierry Schüpbach ◽  
...  
Keyword(s):  
Cell Shape ◽  
Modular Design ◽  
Simulation Models ◽  
Cell Segmentation ◽  
Fluorescence Signal ◽  
Curved Surfaces ◽  
3D Image ◽  
3D Data ◽  
Lineage Tracking ◽  
New Algorithms

Morphogenesis emerges from complex multiscale interactions between genetic and mechanical processes. To understand these processes, the evolution of cell shape, proliferation and gene expression must be quantified. This quantification is usually performed either in full 3D, which is computationally expensive and technically challenging, or on 2D planar projections, which introduces geometrical artifacts on highly curved organs. Here we present MorphoGraphX (www.MorphoGraphX.org), a software that bridges this gap by working directly with curved surface images extracted from 3D data. In addition to traditional 3D image analysis, we have developed algorithms to operate on curved surfaces, such as cell segmentation, lineage tracking and fluorescence signal quantification. The software's modular design makes it easy to include existing libraries, or to implement new algorithms. Cell geometries extracted with MorphoGraphX can be exported and used as templates for simulation models, providing a powerful platform to investigate the interactions between shape, genes and growth.

DMNet: Dual-Stream Marker Guided Deep Network for Dense Cell Segmentation and Lineage Tracking

2021 ◽  
Author(s):  
Rina Bao ◽  
Noor M. Al-Shakarji ◽  
Filiz Bunyak ◽  
Kannappan Palaniappan
Keyword(s):  
Cell Segmentation ◽  
Deep Network ◽  
Dense Cell ◽  
Lineage Tracking

scholarly journals 3D IMAGE RECONSTRUCTION OF OVARIAN TUMOR IN THE ULTRASONIC IMAGES

2001 ◽  
Vol 13 (02) ◽  
pp. 93-98 ◽  
Author(s):  
C. F. JIANG
Keyword(s):  
Ovarian Tumor ◽  
The Other ◽  
3D Image ◽  
Data Set ◽  
3D Image Reconstruction ◽  
3D Data ◽  
3D Information ◽  
Ultrasonic Images ◽  
2D Images ◽  
Degree Of Irregularity

The prevalence of ovarian tumor malignancy can be monitored by the degree of irregularity in the ovarian contour and by the septal structure inside the tumor observed in ultrasonic images. However the 2D ultrasonic images can not integrate 3D information form the ovarian tumor. In this paper, we present an algorithm that can render the 3D image of an ovarian tumor by reconstructing the 2D ultrasonic images into a 3D data set. This is based on sequentially boundary detection in a series of 2D images to form a 3D tumor contour. This contour is then used as a barrier to remove the data containing the other tissue adhering to the tumor surface. The final 3D image rendered by the isolated data provides a clear view of both the surface and inner structure of the ovarian tumor.

scholarly journals SMITER—A Python Library for the Simulation of LC-MS/MS Experiments

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 396
Author(s):  
Manuel Kösters ◽  
Johannes Leufken ◽  
Sebastian A. Leidel
Keyword(s):  
Mass Spectrometry ◽  
Gold Standard ◽  
Modular Design ◽  
Ground Truth ◽  
Peptide Fragmentation ◽  
Noise Model ◽  
Command Line Tool ◽  
The Rich ◽  
New Algorithms ◽  
Chemical Formulas

SMITER (Synthetic mzML writer) is a Python-based command-line tool designed to simulate liquid-chromatography-coupled tandem mass spectrometry LC-MS/MS runs. It enables the simulation of any biomolecule amenable to mass spectrometry (MS) since all calculations are based on chemical formulas. SMITER features a modular design, allowing for an easy implementation of different noise and fragmentation models. By default, SMITER uses an established noise model and offers several methods for peptide fragmentation, and two models for nucleoside fragmentation and one for lipid fragmentation. Due to the rich Python ecosystem, other modules, e.g., for retention time (RT) prediction, can easily be implemented for the tailored simulation of any molecule of choice. This facilitates the generation of defined gold-standard LC-MS/MS datasets for any type of experiment. Such gold standards, where the ground truth is known, are required in computational mass spectrometry to test new algorithms and to improve parameters of existing ones. Similarly, gold-standard datasets can be used to evaluate analytical challenges, e.g., by predicting co-elution and co-fragmentation of molecules. As these challenges hinder the detection or quantification of co-eluents, a comprehensive simulation can identify and thus, prevent such difficulties before performing actual MS experiments. SMITER allows the creation of such datasets easily, fast, and efficiently.

scholarly journals Generating NURBS cladding and structures with parametric programming and BIM

2020 ◽  
Vol 11 ◽  
pp. e020016
Author(s):  
Neander Furtado Silva ◽  
Lilian Maciel Furtado Silva ◽  
Ígor Lacroix
Keyword(s):  
Real Time ◽  
Building Information Modeling ◽  
Parametric Programming ◽  
Information Modeling ◽  
Curved Surfaces ◽  
Curved Beams ◽  
Building Information ◽  
Nurbs Surfaces ◽  
New Algorithms ◽  
Supporting Structures

The process of designing and building curvilinear architectures is still challenging. The use of multiple applications with distinctive design paradigms are unlikely to disappear. The interoperability used here was not only the conventional one. It was also ‘live’, in ‘real time’, with two of the applications involved opened and running simultaneously. A design workflow based on the use of form-forming applications connected via parametric programming to building information modeling, BIM, was proposed. The main objective was to facilitate designing and building curvilinear architectures and their supporting structures using simultaneously two different design paradigms. The tools needed in our research can be summarized as follows: NURBS Lofting for surface creation, contouring for modular slicing and structural axis grid definition, sweeping along axes for surface creation of the curved beams of I profile and paneling for the subdivision of curved surfaces into planar fractions. Parametric programming was used to automate sweeping along axes to generating curved I-beams and paneling to subdivide the NURBS surfaces into planar fractions. To the best of our knowledge, our major contribution resides in defining a workflow and developing new algorithms for facilitating designing NURBS surfaces and corresponding supporting structures through ‘live’ interoperability among different applications.

scholarly journals CONTOPT-JS: Metaheuristic Algorithms based JavaScript Software Library for Continuous Optimization Problems

2019 ◽  
pp. 1-7
Author(s):  
Osman Gokalp ◽  
Aybars Ugur ◽  
Sema Bodur
Keyword(s):  
Web Applications ◽  
Modular Design ◽  
Optimization Problems ◽  
Continuous Optimization ◽  
Software Library ◽  
Bee Colony ◽  
Experimental Works ◽  
Continuous Optimization Problems ◽  
Client Side ◽  
New Algorithms

In this study, a software library called CONTOPT-JS has been developed for solving continuous optimization problems. By using this JavaScript language based library, fully client-side web applications can be developed. In the library, Artificial Bee Colony, Differential Evolution, Particle Swarm Optimization and Evolution Strategies metaheuristics exist and new algorithms and new problems can be added because of its modular design. Using the CONTOPT-JS library, experimental works have been conducted on some standard optimization benchmark functions and Sensor Deployment application area and the obtained results have been presented.

scholarly journals Comparative study of contact repulsion in control and mutant macrophages using a novel interaction detection

2020 ◽  
Author(s):  
JA Solís-Lemus ◽  
BJ Sánchez-Sánchez ◽  
S Marcotti ◽  
M Burki ◽  
B Stramer ◽  
...  
Keyword(s):  
Cell Shape ◽  
Cell Tracking ◽  
Statistical Significance ◽  
Specific Protein ◽  
Cell Segmentation ◽  
Wild Type ◽  
Detection Mechanism ◽  
Interaction Detection ◽  
Motion Characteristics ◽  
Mutant Cells

AbstractThis paper compares the contact-repulsion movement of mutant and wild-type macrophages using a novel interaction detection mechanism. The migrating macrophages are observed in Drosophila embryos. The study is carried out by a framework called macrosight, which analyses the movement and interaction of migrating macrophages. The framework incorporates a segmentation and tracking algorithm into analysing motion characteristics of cells after contact. In this particular study, the interactions between cells is characterised in the case of control embryos and Shot3 mutants, where the cells have been altered to suppress a specific protein, looking to understand what drives the movement. Statistical significance between control and mutant cells was found when comparing the direction of motion after contact in specific conditions. Such discoveries provide insights for future developments in combining biological experiments to computational analysis. Cell Segmentation, Cell Tracking, Macrophages, Cell Shape, Contact Analysis

scholarly journals A novel cell segmentation method for developing embryos using machine learning

2018 ◽  
Author(s):  
Rikifumi Ota ◽  
Takahiro Ide ◽  
Tatsuo Michiue
Keyword(s):  
Machine Learning ◽  
Cell Shape ◽  
State Of The Art ◽  
Cell Segmentation ◽  
Segmentation Method ◽  
Convolutional Network ◽  
Fully Convolutional Network ◽  
Segmented Image ◽  
Novel Method ◽  
Better Than

AbstractCell segmentation is crucial in the study of morphogenesis in developing embryos, but it is limited in its accuracy. In this study we provide a novel method for cell segmentation using machine-learning, termed Cell Segmenter using Machine Learning (CSML). CSML performed better than state-of-the-art methods, such as RACE and watershed, in the segmentation of ectodermal cells in the Xenopus embryo. CSML required only one whole embryo image for training a Fully Convolutional Network classifier, and it took 20 seconds per each image to return a segmented image. To validate its accuracy, we compared it to other methods in assessing several indicators of cell shape. We also examined the generality by measuring its performance in segmenting independent images. Our data demonstrates the superiority of CSML, and we expect this application to significantly improve efficiency in cell shape studies.

scholarly journals Managing 3D Collections Data: Developing Systems and Metadata for 3D Digitization at Scale

2018 ◽  
Vol 2 ◽  
pp. e26704
Author(s):  
Jon Blundell
Keyword(s):  
Modular Design ◽  
3D Models ◽  
Public Access ◽  
Data Repository ◽  
Metadata Model ◽  
3D Data ◽  
Data Stewardship ◽  
Scan Data ◽  
Complex Relationships ◽  
3D Digitization

As 3D digitization becomes more common in collections documentation and research, there is a growing need for tools which address the special needs of 3D data stewardship. Systems are needed to manage both the scan data collected during digitization activities, as well as the 3D models generated from that data. These systems need to be able to preserve and make transparent the complex relationships inherent in the data created from 3D digitization activities. They need to connect digital surrogates back to the objects they represent as well as provide an easy way to discover and retrieve that data for research, conservation, and public access. At the core of such systems there needs to be metadata models that can account for the intricacies and specific needs of managing 3D data. This year, the Smithsonian Institution will be deploying new infrastructure which does just that, based on a metadata model developed by a cross disciplinary working group comprised of content experts from across the institution. The platform, which not only manages scan data, but also automates the processing and delivery of 3D digitized content, is open source and is built around modular design principles for easier adoption. This talk builds upon last year’s SPNHC presentation “Automating 3D collection capture: Developing systems for 3D digitization at scale” as it addresses the information systems and infrastructure needed to support the management and delivery of 3D data at scale. We will cover the basic functionality of the Smithsonian’s 3D data repository, how it facilitates data administration, the workflows involved in managing and processing data, and how it connects to the larger Smithsonian infrastructure. As part of this, we will explore the metadata model behind the system and how the model can support greater usability and transparency when sharing and working with 3D scan data.

Requirements for a Universal Image Analysis Tool in Dentistry and Oral and Maxillofacial Surgery

2010 ◽  
pp. 79-89 ◽  
Author(s):  
Thomas Hierl ◽  
Heike Huempfner-Hierl ◽  
Daniel Kruber ◽  
Thomas Gaebler ◽  
Alexander Hemprich ◽  
...  
Keyword(s):  
Image Analysis ◽  
Maxillofacial Surgery ◽  
Image Data ◽  
Oral And Maxillofacial Surgery ◽  
Data Sets ◽  
Analysis Tool ◽  
3D Image ◽  
Modular Software ◽  
3D Data ◽  
Visualization Toolkit

This chapter discusses the requirements of an image analysis tool designed for dentistry and oral and maxillofacial surgery focussing on 3D-image data. As software for the analysis of all the different types of medical 3D-data is not available, a model software based on VTK (visualization toolkit) is presented. VTK is a free modular software which can be tailored to individual demands. First, the most important types of image data are shown, then the operations needed to handle the data sets. Metric analysis is covered in-depth as it forms the basis of orthodontic and surgery planning. Finally typical examples of different fields of dentistry are given.

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