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 Videos

Advanced technique in breast thermography analysis.

E Y K Ng1, E C Kee, U Rajendra Acharya

  • 1College of Engineering, School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|February 7, 2007
PubMed
Summary

This study introduces an advanced technique combining statistical methods and Artificial Neural Networks (ANN) for accurate breast cancer diagnosis using thermography. The novel approach enhances diagnostic capabilities by analyzing complex thermal imaging data.

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

LymphUs: A multicenter open-access database of lymph node ultrasound images in patients with papillary thyroid carcinoma for clinical and artificial intelligence research.

Data in brief·2026
Same author

Ultrasound-based Detection and Malignancy Prediction of Breast Lesions Eligible for Biopsy: A Multi-center Clinical-scenario Study Using Nomograms, Large Language Models, and Radiologist Evaluation.

Academic radiology·2026
Same author

MM-GradCAM: an improved multimodal GradCAM method with 1D and 2D ECG data for detection of cardiac arrhythmia.

Scientific reports·2026
Same author

Automated Alzheimer's disease detection using active learning model with reinforcement learning and scope loss function.

Npj mental health research·2025
Same author

Early detection of colorectal cancer using a hybrid model with enhanced image quality and optimized classification.

Physical and engineering sciences in medicine·2025
Same author

Novel Deep Learning Model for Glaucoma Detection Using Fusion of Fundus and Optical Coherence Tomography Images.

Sensors (Basel, Switzerland)·2025

Area of Science:

  • Medical Imaging
  • Biostatistics
  • Artificial Intelligence

Background:

  • Thermography is a non-invasive medical imaging technique.
  • Accurate breast cancer diagnosis remains a critical clinical challenge.
  • Integrating biostatistical methods with Artificial Neural Networks (ANN) offers potential for improved diagnostic accuracy.

Purpose of the Study:

  • To investigate the efficacy of a novel Advanced Technique for breast cancer diagnosis using thermography.
  • To establish a highly accurate diagnostic system by analyzing thermograms with biostatistical methods and ANN.
  • To evaluate the performance of the proposed technique in classifying healthy versus cancerous cases.

Main Methods:

  • The Advanced Technique integrates Linear Regression (LR), Radial Basis Function Network (RBFN), and Receiver Operating Characteristics (ROC) analysis.

Related Experiment Videos

  • LR is used to identify correlations between thermographic variables and breast health status, guiding feature selection for the ANN.
  • RBFN is employed for classification, trained to predict cancerous or healthy outcomes from thermographic data, with ROC used for performance evaluation.

    • Main Results:

    • The study demonstrates the potential of the Advanced Technique in analyzing complex thermographic data for breast cancer diagnosis.
    • RBFN shows promise for accurate classification, offering advantages in training speed and decision-making compared to other neural network architectures.
    • ROC analysis provides a quantitative measure of the diagnostic performance, including accuracy, sensitivity, and specificity.

    Conclusions:

    • The proposed Advanced Technique offers a novel and integrative approach to breast cancer diagnosis using thermography.
    • Combining biostatistical analysis with RBFN and ROC evaluation can lead to enhanced diagnostic accuracy and reliability.
    • This methodology holds potential for improving early detection and clinical decision-making in breast cancer screening.