PhysQSR: Improving Reasoning in Three Dimensions and Time With Image Processing and Physics

2015 ◽  
Author(s):  
Nathan Eloe ◽  
Jennifer Leopold
Keyword(s):  
Image Processing ◽  
Three Dimensions

The Fractal Interpolating Algorithm of 3D Terrain Surface Reconstruction

2015 ◽  
Vol 734 ◽  
pp. 526-529 ◽  
Author(s):  
Jian Xiong
Keyword(s):  
Image Processing ◽  
Brownian Motion ◽  
Fractional Brownian Motion ◽  
Surface Reconstruction ◽  
Three Dimensions ◽  
3D Terrain ◽  
Terrain Surface

Fractal is a science which studies very irregular and complicated natural shapes. It has been used widely in image processing. Firstly this thesis analyses the reasons that fractal can be used in 3D (Three Dimensions) terrain surface reconstruction. Then, it introduces fractional Brownian motion (fBm). On this basis, the thesis presents an interpolating algorithm to reconstruct 3D terrain surface. The algorithm uses fBm model to interpolate. It can be achieved simply and a good result is obtained.

Structure in three dimensions of H,K-ATPase by Electron Microscopy and image processing

1992 ◽  
Vol 50 (1) ◽  
pp. 444-445
Author(s):  
Manijeh Mohraz ◽  
Sonal Sathe ◽  
P.R. Smith
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Amino Acids ◽  
Plasma Membrane ◽  
Gastric Mucosa ◽  
Sequence Homology ◽  
Concentration Gradient ◽  
Atp Hydrolysis ◽  
Three Dimensions ◽  
Β Subunit

H,K-ATPase is an integral protein of the plasma membrane of parietal cells in the gastric mucosa. It is believed to constitute the pump responsible for secretion of acid into the stomach. It utilizes energy from ATP hydrolysis to transport H+ out of the cell and K+ into the cell against an H+ concentration gradient of one million-fold. The catalytic subunit (Mr 110,000) of H,K-ATPase shows striking sequence homology to those of other ion-transporting ATPases. The enzyme has a second subunit, a glycoprotein of ca 300 amino acids, which is homologous to the β subunit of the Na, K-ATPase.

scholarly journals Validation of a rapid, semiautomatic image analysis tool for measurement of gastric accommodation and emptying by magnetic resonance imaging

2015 ◽  
Vol 308 (8) ◽  
pp. G652-G663 ◽  
Author(s):  
Sreerup Banerjee ◽  
Sudeepa Dixit ◽  
Mark Fox ◽  
Anupam Pal
Keyword(s):  
Magnetic Resonance Imaging ◽  
Image Processing ◽  
Magnetic Resonance ◽  
Rapid Assessment ◽  
Processing System ◽  
Three Dimensions ◽  
Analysis Tool ◽  
Resonance Imaging ◽  
Gastric Accommodation ◽  
User Input

Magnetic resonance imaging (MRI) has advantages for the assessment of gastrointestinal structures and functions; however, processing MRI data is time consuming and this has limited uptake to a few specialist centers. This study introduces a semiautomatic image processing system for rapid analysis of gastrointestinal MRI. For assessment of simpler regions of interest (ROI) such as the stomach, the system generates virtual images along arbitrary planes that intersect the ROI edges in the original images. This generates seed points that are joined automatically to form contours on each adjacent two-dimensional image and reconstructed in three dimensions (3D). An alternative thresholding approach is available for rapid assessment of complex structures like the small intestine. For assessment of dynamic gastrointestinal function, such as gastric accommodation and emptying, the initial 3D reconstruction is used as reference to process adjacent image stacks automatically. This generates four-dimensional (4D) reconstructions of dynamic volume change over time. Compared with manual processing, this semiautomatic system reduced the user input required to analyze a MRI gastric emptying study (estimated 100 vs. 10,000 mouse clicks). This analysis was not subject to variation in volume measurements seen between three human observers. In conclusion, the image processing platform presented processed large volumes of MRI data, such as that produced by gastric accommodation and emptying studies, with minimal user input. 3D and 4D reconstructions of the stomach and, potentially, other gastrointestinal organs are produced faster and more accurately than manual methods. This system will facilitate the application of MRI in gastrointestinal research and clinical practice.

Particle Shape Analysis Using Digital Image Processing

2019 ◽  
pp. 377-391
Author(s):  
Katia Tannous ◽  
Fillipe de Souza Silva
Keyword(s):  
Image Processing ◽  
Aspect Ratio ◽  
Digital Image Processing ◽  
Shape Analysis ◽  
Processing Technique ◽  
Solid Particles ◽  
Three Dimensions ◽  
Image Processing Technique ◽  
Prolate Spheroids

This chapter will discuss new software, Particles and Geometric Shapes Analyzer (APOGEO), aiming the determination of aspect ratio and sphericity of solid particles by image processing technique without any manual work. This software can quantify the major and minor axes correlating two or three dimensions of particles (e.g., biomass, mineral, pharmaceutical, and food products) to obtain their shape. The particles can be associated with different geometries, such as rectangular parallelepiped, cylinder, oblate and prolate spheroids, and irregular. The results are presented in histograms and tables, but also can be saved in a spreadsheet.

scholarly journals DeepSynth: Three-dimensional nuclear segmentation of biological images using neural networks trained with synthetic data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kenneth W. Dunn ◽  
Chichen Fu ◽  
David Joon Ho ◽  
Soonam Lee ◽  
Shuo Han ◽  
...  
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Deep Learning ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Training Data ◽  
Three Dimensions ◽  
Great Promise ◽  
Biological Images ◽  
Nuclear Segmentation

AbstractThe scale of biological microscopy has increased dramatically over the past ten years, with the development of new modalities supporting collection of high-resolution fluorescence image volumes spanning hundreds of microns if not millimeters. The size and complexity of these volumes is such that quantitative analysis requires automated methods of image processing to identify and characterize individual cells. For many workflows, this process starts with segmentation of nuclei that, due to their ubiquity, ease-of-labeling and relatively simple structure, make them appealing targets for automated detection of individual cells. However, in the context of large, three-dimensional image volumes, nuclei present many challenges to automated segmentation, such that conventional approaches are seldom effective and/or robust. Techniques based upon deep-learning have shown great promise, but enthusiasm for applying these techniques is tempered by the need to generate training data, an arduous task, particularly in three dimensions. Here we present results of a new technique of nuclear segmentation using neural networks trained on synthetic data. Comparisons with results obtained using commonly-used image processing packages demonstrate that DeepSynth provides the superior results associated with deep-learning techniques without the need for manual annotation.

scholarly journals A Segmentation Method of Skin MRI 3D High Resolution in vivo

2018 ◽  
Vol 2 (3) ◽  
pp. 255-261 ◽  
Author(s):  
ZEGOUR Rachida ◽  
Ahror BELAID ◽  
Douraied Ben Salem
Keyword(s):  
Image Processing ◽  
Water Content ◽  
Imaging Modality ◽  
Three Dimensions ◽  
Segmentation Method ◽  
Tissue Contrast ◽  
Fuzzy C Means Clustering ◽  
Fcm Clustering ◽  
Edge Based

Background: In recent years, Magnetic Resonance Imaging (MRI) is used in clinical application as non-invasive medical modality, it is rarely used to study the anatomy physiological, and biochemical of the skin, in spite of its very attractive modality for skin imaging. It makes an ideal imaging modality of unique soft tissue contrast to study the skin water content and to differentiate between the different skin layers. However MRI provides a big data with high quality. The analysis of these data require computerized methods to help clinicians and to improve disease of diagnosis. Several image processing method have been extensively used to assist doctors in qualitative diagnosis, segmentation is one of the most methods used in medical image processing for many applications in order to understand medical data and extract useful information. The purpose of this study is to use the segmentation method to measure the hydration of skin using MRI modality. Methods: We will classify segmentation approaches for MRI data into three basics classes: Edge based segmentation, Region based segmentation, and Thresholding segmentation. Then we will briefly describe Fuzzy C-means Clustering method. Furthermore, we will give some related works used FCM algorithm with MRI images. Results: We have measured the hydration of the feet as a result of the FCM segmentation method, where the sample of the study was conducted on 35 healthy volunteers, who were scanned by MRI machine before applying moisturizer and one hour after. Conclusion: MRI is an attractive modality to study the skin water content, it makes an ideal observation of the different skin layers in vivo with three dimensions. However, the segmentation of MRI data by FCM clustering is a computerized method to help clinicians in order to measure skin hydration.  

scholarly journals Study of frequency pattern of coherent turbulent flow over ripples using image processing with implication in river restoration

2011 ◽  
Vol 8 (4) ◽  
pp. 7845-7871
Author(s):  
A. Keshavarzi ◽  
J. Ball ◽  
H. Nabavi
Keyword(s):  
Image Processing ◽  
Turbulent Flow ◽  
Flow Structure ◽  
Sampling Rate ◽  
Three Dimensions ◽  
Image Processing Technique ◽  
Frequency Pattern ◽  
Bed Form ◽  
Bursting Events ◽  
Sediment Particles

Abstract. River channel change and bed scourings are source of major environmental problem for fish and aquatic habitat. The bed form such as ripples and dunes is the result of an interaction between turbulent flow structure and sediment particles at the bed. The structure of turbulent flow over ripples is important to understand initiation of sediment entrainment and its transport. The focus of this study is the measurement and analysis of the dominant bursting events and the flow structure over ripples in the bed of a channel. Two types of ripples with sinusoidal and triangular forms were tested in this study. The velocities of flow over the ripples were measured in three dimensions using an Acoustic Doppler Velocimeter with a sampling rate of 50 Hz. These velocities were measured at different points within the flow depth from the bed and at different longitudinal positions along the flume. A CCD camera was used to capture 1500 sequential images from the bed and to monitor sediment movement at different positions along the bed. Application of image processing technique enabled us to compute the number of entrained and deposited particles over the ripples. From a quadrant decomposition of instantaneous velocity fluctuations close to the bed, it was found that bursting events downstream of the second ripple, in Quadrants 1 and 3, were dominant whereas upstream of the ripple, Quadrants 2 and 4 were dominant. More importantly consideration of these results indicates that the normalized occurrence probabilities of sweep events are in phase with the bed forms whereas those of ejection event are out of phase with the bed form. Therefore entrainment would be expected to occur upstream and deposition occurs downstream of the ripple. These expectations were confirmed by measurement of entrained and deposited sediment particles from the bed. These above information can be used in practical application for rivers where restoration is required.

scholarly journals Frequency pattern of turbulent flow and sediment entrainment over ripples using image processing

2012 ◽  
Vol 16 (1) ◽  
pp. 147-156 ◽  
Author(s):  
A. Keshavarzi ◽  
J. Ball ◽  
H. Nabavi
Keyword(s):  
Image Processing ◽  
Turbulent Flow ◽  
Flow Structure ◽  
Sampling Rate ◽  
Three Dimensions ◽  
Image Processing Technique ◽  
Bed Form ◽  
Bursting Events ◽  
Sediment Particles ◽  
Sediment Entrainment

Abstract. River channel change and bed scourings are source of major environmental problem for fish and aquatic habitat. The bed form such as ripples and dunes is the result of an interaction between turbulent flow structure and sediment particles at the bed. The structure of turbulent flow over ripples is important to understand initiation of sediment entrainment and its transport. The focus of this study is the measurement and analysis of the dominant bursting events and the flow structure over ripples in the bed of a channel. Two types of ripples with sinusoidal and triangular forms were tested in this study. The velocities of flow over the ripples were measured in three dimensions using an Acoustic Doppler Velocimeter with a sampling rate of 50 Hz. These velocities were measured at different points within the flow depth from the bed and at different longitudinal positions along the flume. A CCD camera was used to capture 1500 sequential images from the bed and to monitor sediment movement at different positions along the bed. Application of image processing technique enabled us to compute the number of entrained and deposited particles over the ripples. From a quadrant decomposition of instantaneous velocity fluctuations close to the bed, it was found that bursting events downstream of the second ripple, in Quadrants 1 and 3, were dominant whereas upstream of the ripple, Quadrants 2 and 4 were dominant. More importantly consideration of these results indicates that the normalized occurrence probabilities of sweep events along the channel are in phase with the bed forms whereas those of ejection events are out of phase with the bed form. Therefore entrainment would be expected to occur upstream and deposition occurs downstream of the ripple. These expectations were confirmed by measurement of entrained and deposited sediment particles from the bed. These above information can be used in practical application for rivers where restoration is required.

scholarly journals Image processing techniques for high-resolution structure determination from badly ordered 2D crystals

2017 ◽  
Author(s):  
Nikhil Biyani ◽  
Sebastian Scherer ◽  
Ricardo D. Righetto ◽  
Julia Kowal ◽  
Mohamed Chami ◽  
...  
Keyword(s):  
Image Processing ◽  
High Resolution ◽  
3D Structure ◽  
Adenosine Monophosphate ◽  
Two Dimensions ◽  
Three Dimensions ◽  
Oxide Semiconductor ◽  
Electron Crystallography ◽  
Contrast Transfer Function ◽  
2D Crystals

Abstract2D electron crystallography can be used to study small membrane proteins in their native environment. Obtaining highly ordered 2D crystals is difficult and time-consuming. However, 2D crystals diffracting to only 10-12 Å can be prepared relatively conveniently in most cases. We have developed image-processing algorithms allowing to generate a high resolution 3D structure from cryo-electron crystallography images of badly ordered crystals. These include movie-mode unbending, refinement over sub-tiles of the images in order to locally refine the sample tilt geometry; implementation of different CTF correction schemes; and an iterative method to apply known constraints in the real and reciprocal space to approximate amplitudes and phases in the so-called missing cone regions. These algorithms applied to a dataset of the potassium channel MloK1 show significant resolution improvements to approximately 5Å.Abbreviations2Dtwo dimensions / dimensional3Dthree dimensions / dimensionalAmpamplitudecAMPcyclic adenosine monophosphateCCDcharge coupled devicesCMOScomplementary metal-oxide-semiconductorCNBDcyclic nucleotide-binding domaincryo-EMcryo-electron microscopyCTFcontrast transfer functionDEDdirect electron detectorDQEdetector quantum efficiencyEMelectron microscopeFOMfigure-of-meritPhaphaseSNRsignal-to-noise ratio

Particle Shape Analysis Using Digital Image Processing

2018 ◽  
pp. 1331-1343
Author(s):  
Katia Tannous ◽  
Fillipe de Souza Silva
Keyword(s):  
Image Processing ◽  
Aspect Ratio ◽  
Digital Image Processing ◽  
Shape Analysis ◽  
Processing Technique ◽  
Solid Particles ◽  
Three Dimensions ◽  
Image Processing Technique ◽  
Prolate Spheroids

This chapter will discuss new software, Particles and Geometric Shapes Analyzer (APOGEO), aiming the determination of aspect ratio and sphericity of solid particles by image processing technique without any manual work. This software can quantify the major and minor axes correlating two or three dimensions of particles (e.g.: biomass, mineral, pharmaceutical and food products) to obtain their shape. The particles can be associated with different geometries such as, rectangular parallelepiped, cylinder, oblate and prolate spheroids, and irregular. The results are presented in histograms and tables, but also can be saved in a spreadsheet.

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