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

Search research articles

Related Experiment Video

Updated: Jun 6, 2026

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

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

Published on: August 30, 2013

Breast lesion identification using feature fusion and multiresolution dual-tree complex wavelet transform.

Manvi Bohra^1,2, Kamred Udham Singh^3,4, Indrajeet Kumar⁵

¹Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun, Uttarakhand, India.

|June 5, 2026

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

Agro-waste amendments alleviate nickel stress: insights into growth, physiology, metabolites, bioaccumulation and health risk assessment in wheat under tropical ecosystems.

Physiology and molecular biology of plants : an international journal of functional plant biology·2026

Same author

Next generation risk assessment and new approach methodologies for sustainable management of heavy metal contaminated environments: A critical review.

Environmental pollution (Barking, Essex : 1987)·2026

Same author

Early Outcomes of Screwless Press-fit Acetabular Cups in Uncemented Total Hip Arthroplasty: A Prospective Study from Eastern India.

Journal of orthopaedic case reports·2026

Same author

Outcome of Surgical Treatment of Giant Cell Tumors of Bone Around the Knee Joint for Extended Curettage or Segmental Resection: A Retrospective Study.

Cureus·2025

Same author

Chronic Thigh Pain in an Adolescent: A Case Report and Literature Review of Desmoplastic Fibroma, A Rare Benign Tumor.

Journal of orthopaedic case reports·2025

Same author

Limb Reconstruction System for Infected Nonunion: A Retrospective Study.

Journal of orthopaedic case reports·2025

Same journal

From brain scans to classifiers: A systematic review of ML-based autism diagnostic frameworks.

Digital health·2026

Same journal

Multi-sensor fusion for differentiating swallows between healthy adults and patients with post-stroke dysphagia.

Digital health·2026

Same journal

The acceptability of wearable devices for promoting adolescent mental wellbeing: A systematic review.

Digital health·2026

Same journal

Exploring the determinants of engagement in the context of mHealth and social media among young people: A systematic literature review.

Digital health·2026

Same journal

Digital tools and biomarkers for cognitive screening: A systematic review.

Digital health·2026

Same journal

Digital twins in healthcare: A systematic review of current applications, frameworks, and future directions.

Digital health·2026

See all related articles

This summary is machine-generated.

This study introduces a computerized framework for breast cancer detection using multiresolution feature fusion and the Dual-Tree Complex Wavelet Transform (DT-CWT) on histopathological images, achieving high diagnostic accuracy.

Area of Science:

Medical Imaging
Computational Pathology
Biomedical Engineering

Background:

Breast cancer is a leading cause of death in women globally, necessitating advanced diagnostic tools.
Accurate and automated methods for breast lesion identification are crucial for timely intervention and improved patient outcomes.

Purpose of the Study:

To develop a robust computerized framework for the accurate identification of breast lesions.
To utilize multiresolution feature fusion based on the Dual-Tree Complex Wavelet Transform (DT-CWT) for enhanced breast cancer diagnosis.

Main Methods:

A dataset of 7909 histopathological images from BreakHis and 594 clinical samples was used.
Image preprocessing, two-level DT-CWT decomposition, and feature extraction (Law's texture, Gabor, statistical) were performed.

Keywords:

Convolutional Neural Network (CNN)Dual-Tree Complex Wavelet Transform (DT-CWT)breast cancer detection gabor features histopathological images law’s texture energy multiresolution feature fusion reverse biorthogonal wavelet

Related Experiment Videos

Last Updated: Jun 6, 2026

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

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

Published on: August 30, 2013

Fused features were classified using a dual-path convolutional neural network (CNN).

Main Results:

The Reverse Biorthogonal (Rbio-2.4) wavelet filter yielded the highest classification accuracy at 97.32%.
The proposed method demonstrated superior performance in precision, recall, F1 score, Matthews correlation coefficient, and Cohen's kappa.

Conclusions:

The DT-CWT-based feature fusion approach offers superior capability for precise breast lesion identification in histopathology.
The integration of wavelet analysis, handcrafted features, and CNN models shows significant potential for clinical breast cancer detection applications.