Jove
Visualize
Contact Us
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 Concept Videos

Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

287
The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
287
X-ray Imaging01:24

X-ray Imaging

5.9K
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...
5.9K
Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

380
Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...
380

You might also read

Related Articles

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

Sort by
Same author

The combinatorial innexin code of heterochannel electrical synapses governs synaptic function and is maintained by distinct cellular mechanisms.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Retraction notice to"Nitric oxide sensing by chlorophyll a" [Anal. Chim. Acta 985 (2017) 101-113].

Analytica chimica acta·2026
Same author

Distinct Molecular Mechanisms Regulate Feeding State-Dependent CO<sub>2</sub> Chemotaxis Plasticity During Different Life Stages in <i>Caenorhabditis elegans</i>.

bioRxiv : the preprint server for biology·2026
Same author

Computational study on QSAR modeling, molecular docking, and ADMET profiling of pyrazole-modified catalpol derivatives as prospective dual inhibitors of VEGFR-2/BRAF V600E.

Journal of computer-aided molecular design·2025
Same author

Protocol to annotate and automate single-cell instance segmentation on stimulated Raman histology using deep learning.

STAR protocols·2025
Same author

CNT as a robust delivery vehicle for anti-breast cancer drugs: A combined DFT and in-silico study.

Journal of molecular graphics & modelling·2025

Related Experiment Video

Updated: Aug 28, 2025

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
05:24

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

491

Fractal Dimension-Based Infection Detection in Chest X-ray Images.

Sujata Ghatak1,2, Satyajit Chakraborti2, Mousumi Gupta3

  • 1University of Engineering & Management, Kolkata, India.

Applied Biochemistry and Biotechnology
|September 21, 2022
PubMed
Summary

This study introduces a novel fractal dimension detection method for medical images using the box counting technique. The proposed approach enhances diagnostic accuracy by better extracting significant information from complex medical object shapes.

Keywords:
Biomedical imagesBox countingFractal dimensionMagnetic resonanceRegion of interestTexture analysis

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

43.0K
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.3K

Related Experiment Videos

Last Updated: Aug 28, 2025

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
05:24

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

491
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

43.0K
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.3K

Area of Science:

  • Medical Imaging
  • Fractal Geometry
  • Diagnostic Analysis

Background:

  • Accurate dimension detection in medical imaging is crucial for diagnosis but challenging due to fractal object shapes.
  • Fractal dimension detection methodologies offer advanced tools for investigating medical images.
  • Existing methods face challenges in extracting diagnostically significant information.

Purpose of the Study:

  • To propose a novel methodology for fractal dimension detection in medical images.
  • To evaluate the proposed method's effectiveness using the box counting technique.
  • To compare the novel approach against state-of-the-art methods for diagnostic imaging.

Main Methods:

  • A novel fractal dimension detection methodology based on the box counting technique is proposed.
  • The method evaluates fractal dimensions of medical images.
  • Performance is assessed by comparing with existing state-of-the-art approaches.

Main Results:

  • The proposed fractal dimension detection technique shows improved outcomes compared to other methods.
  • The algorithm effectively extracts diagnostically significant information from clinical images.
  • Results graphically validate the mathematical derivation of the box counting approach in terms of Hurst exponent.

Conclusions:

  • The novel box counting-based fractal dimension detection method is efficient for medical image analysis.
  • This technique offers a promising tool for improving medical diagnosis accuracy.
  • The study highlights the utility of fractal geometry in medical image investigation.