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 Experiment Video

Updated: Jul 10, 2026

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

Detecting microcalcifications in digital mammograms using wavelet domain hidden Markov tree model.

Emma Regentova1, Lei Zhang, Jun Zheng

  • 1Dept. of Electr. & Comput. Eng., Nevada Univ., Las Vegas, NV 89154, USA. regent@ee.unlv.edu

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data.

Journal of personalized medicine·2023
Same author

DeepQuantify: deep learning and quantification system of white blood cells in light microscopy images of injured skeletal muscles.

Journal of medical imaging (Bellingham, Wash.)·2019
Same author

Co-expression analysis aids in the identification of genes in the cuticular wax pathway in maize.

The Plant journal : for cell and molecular biology·2018
Same author

Deacetylation of serine hydroxymethyl-transferase 2 by SIRT3 promotes colorectal carcinogenesis.

Nature communications·2018
Same author

lncRNA FEZF1‑AS1 contributes to cell proliferation, migration and invasion by sponging miR‑4443 in hepatocellular carcinoma.

Molecular medicine reports·2018
Same author

Letter by Yu et al Regarding Article, "Iodine Sign as a Novel Predictor of Hematoma Expansion and Poor Outcomes in Primary Intracerebral Hemorrhage Patients".

Stroke·2018

This study introduces a wavelet domain hidden Markov tree model (WHMT) for detecting microcalcification clusters in mammograms. The system achieved 100% true positive detection with only 2.9 false positives per case.

Area of Science:

  • Medical Imaging
  • Computer-Aided Diagnosis
  • Statistical Modeling

Background:

  • Digital mammography is crucial for early breast cancer detection.
  • Microcalcification clusters are important indicators of malignancy.
  • Accurate detection systems are needed to improve diagnostic accuracy.

Purpose of the Study:

  • To evaluate the performance of a wavelet domain hidden Markov tree model (WHMT) for microcalcification cluster detection.
  • To integrate this model into a computer-aided diagnostic prompting system.
  • To assess the system's accuracy using the mini-MIAS database.

Main Methods:

  • Gross-segmentation of mammograms to isolate the breast region.
  • Noise reduction techniques to eliminate pepper-type noise.

More Related Videos

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

Related Experiment Videos

Last Updated: Jul 10, 2026

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

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

  • Block-wise wavelet transform and likelihood calculations.
  • Image segmentation and postprocessing for microcalcification cluster identification.

    • Main Results:

    • The WHMT model was integrated into a computer-aided diagnostic system.
    • The system demonstrated high accuracy in detecting microcalcification clusters.
    • Achieved 100% true positive detection rate with 2.9 false positives per case on the mini-MIAS database.

    Conclusions:

    • The WHMT model shows significant promise for enhancing microcalcification cluster detection in digital mammograms.
    • The developed computer-aided diagnostic system is effective and efficient.
    • This approach can improve the reliability of breast cancer diagnosis.