Jove
Visualize
Contact Us

Related Concept Videos

X-ray Imaging01:24

X-ray Imaging

7.7K
German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
7.7K

You might also read

Related Articles

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

Sort by
Same author

A novel retina-based human identification algorithm based on geometrical shape features using a hierarchical matching structure.

Computer methods and programs in biomedicine·2017
Same author

Seizure-specific wavelet (Seizlet) design for epileptic seizure detection using CorrEntropy ellipse features based on seizure modulus maximas patterns.

Journal of neuroscience methods·2016
Same author

Real-time seizure prediction using RLS filtering and interpolated histogram feature based on hybrid optimization algorithm of Bayesian classifier and Hunting search.

Computer methods and programs in biomedicine·2016
Same author

Optimal query-based relevance feedback in medical image retrieval using score fusion-based classification.

Journal of digital imaging·2014
Same author

An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

Journal of medical systems·2014
Same author

Clavulanic acid production estimation based on color and structural features of Streptomyces clavuligerus bacteria using self-organizing map and genetic algorithm.

Computer methods and programs in biomedicine·2014
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: May 1, 2026

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

1.3K

Medical X-ray Image Hierarchical Classification Using a Merging and Splitting Scheme in Feature Space.

Nooshin Jafari Fesharaki1, Hossein Pourghassem1

  • 1Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran.

Journal of Medical Signals and Sensors
|March 28, 2014
PubMed
Summary

This study introduces a new hierarchical classification for medical X-ray images, improving content-based image retrieval. The method uses shape and texture features, achieving 93.6% accuracy in classifying 18 image types.

Keywords:
Hierarchical classificationmerging and splitting schemeorthogonal forward selectionshape and texture features

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.6K

Related Experiment Videos

Last Updated: May 1, 2026

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

1.3K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.6K

Area of Science:

  • Medical Imaging
  • Computer Science
  • Artificial Intelligence

Background:

  • Medical X-ray images are produced daily in large volumes with significant variations.
  • Efficient classification is crucial for searching and retrieving these images, particularly in content-based medical image retrieval (CBMIR) systems.

Purpose of the Study:

  • To propose a novel hierarchical classification structure for medical X-ray images.
  • To enhance the performance of CBMIR systems through improved image classification.

Main Methods:

  • A hierarchical classification structure employing a merging and splitting scheme based on shape and texture features.
  • Utilizing an orthogonal forward selection algorithm with Mahalanobis class separability for feature selection and reduction.
  • Supervised merging and splitting applied at each level to form the hierarchical classification based on class complexity and inter-class distance.

Main Results:

  • The proposed structure achieved a classification accuracy rate of 93.6% for an 18-class problem on the IMAGECLEF 2005 database.
  • The hierarchical approach effectively groups similar classes initially and then refines them into distinct categories.
  • Feature optimization using orthogonal forward selection improved classification performance.

Conclusions:

  • The developed hierarchical classification structure is effective for medical X-ray image organization and retrieval.
  • The combination of merging/splitting schemes and advanced feature selection significantly enhances classification accuracy.
  • This approach offers a robust solution for managing and accessing large datasets of medical X-ray images.