Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Vector Algebra: Method of Components

Vector Algebra: Method of Components

It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...

Gradient Vectors and Their Applications

Gradient Vectors and Their Applications

Every point on a topographical map corresponds to a particular elevation, so the landscape can be modeled as a surface whose height depends on horizontal position. From any given location, a hiker may face infinitely many directions, but only one direction produces the fastest possible increase in elevation. This unique route is called the direction of steepest ascent, and in multivariable calculus, it is represented by the gradient vector of the elevation function.The gradient vector points...

Conservative Vector Fields

Conservative Vector Fields

A conservative vector field describes a force or field in which the work done between two points depends only on the initial and final positions. For a ball moving in Earth’s gravitational field, gravity performs work determined by the difference in height, regardless of whether the ball moves vertically or follows a curved trajectory.A vector field is conservative if it can be expressed as the gradient of a scalar potential function, f. In two dimensions, this is written...

Vector Algebra: Graphical Method

Vector Algebra: Graphical Method

Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...

Significance of the Gradient Vector

Significance of the Gradient Vector

A surface defined by a function of two variables can be understood by examining how it changes along specific directions. When one variable is held constant, the surface reduces to a curve that reflects variation in the other variable. For example, fixing one variable and moving parallel to a coordinate axis produces a cross-sectional curve. The slope of this curve at a given point represents how the function changes in that particular direction, providing a measure of local steepness.By...

Classification of Signals

Classification of Signals

In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population.

Journal of translational medicine·2020

Same author

Low-Energy Shockwave Treatment Promotes Endothelial Progenitor Cell Homing to the Stenotic Pig Kidney.

Cell transplantation·2020

Same author

Transplanted senescent renal scattered tubular-like cells induce injury in the mouse kidney.

American journal of physiology. Renal physiology·2020

Same author

Mesenchymal Stem Cell-Derived Extracellular Vesicles Induce Regulatory T Cells to Ameliorate Chronic Kidney Injury.

Hypertension (Dallas, Tex. : 1979)·2020

Same author

miR-34a regulates adipogenesis in porcine intramuscular adipocytes by targeting ACSL4.

BMC genetics·2020

Same author

Design and synthesis of novel 2-arylbenzimidazoles as selective mutant isocitrate dehydrogenase 2 R140Q inhibitors.

Bioorganic & medicinal chemistry letters·2020

Search research articles

Related Experiment Video

Updated: Jun 26, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

A vectorial image classification method based on neighborhood weighted Gaussian mixture model.

Hui Tang¹, Jean-Louis Dillenseger, Li Min Luo

¹LIST, Southeast University, 210096, Nan Jing, China. corinna@seu.edu.cn

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 24, 2009

Summary

This summary is machine-generated.

This study introduces a novel neighborhood weighted Gaussian mixture model for CT uroscan analysis. The enhanced method improves anatomical structure classification by reducing noise and partial volume effects.

Related Experiment Videos

Last Updated: Jun 26, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Area of Science:

Medical Imaging
Computer Vision
Image Analysis

Background:

CT uroscans involve multiple time-spaced acquisitions, creating a vectorial volume with rich anatomical information.
Accurate segmentation of anatomical structures in these volumes is crucial for diagnosis.
Partial Volume Effect (PVE) and noise in CT data complicate traditional classification methods like Gaussian Mixture Models (GMM).

Purpose of the Study:

To develop an improved classification method for vectorial CT uroscan data.
To address limitations of standard GMMs in handling PVE and noise.
To enhance the accuracy of anatomical structure outlining in medical imaging.

Main Methods:

Registration of time-spaced CT uroscan acquisitions to form a vectorial volume.
Application of a novel neighborhood weighted Gaussian mixture model for multi-dimensional classification.
Utilizing the Expectation Maximization algorithm for model optimization.

Main Results:

The proposed neighborhood weighted GMM achieved superior classification accuracy compared to standard GMMs.
The method demonstrated reduced sensitivity to noise and improved handling of inhomogeneous regions.
Enhanced outlining of anatomical structures within the vectorial CT uroscan data was observed.

Conclusions:

The neighborhood weighted Gaussian mixture model offers a robust solution for classifying complex CT uroscan data.
This approach effectively mitigates the challenges posed by PVE and noise in medical image analysis.
The findings suggest potential for improved diagnostic accuracy in CT uroscan interpretation.