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Related Experiment Video

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An automated mammogram classification system using modified support vector machine.

Aderonke Anthonia Kayode1, Noah Oluwatobi Akande1, Adekanmi Adeyinka Adegun1

  • 1Computer Science Department, Landmark University, Omu-Aran, Kwara State, Nigeria.

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Summary

This study developed a computer-aided diagnosis (CADx) system for mammograms, achieving 100% accuracy in detecting abnormalities and high accuracy in classifying them as benign or malignant, aiding radiologists in breast cancer diagnosis.

Keywords:
CADx systemsGLCMcancer diagnosisdiagnostic errorsradiologists

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Oncology

Background:

  • Breast cancer is a significant public health concern, necessitating accurate and timely diagnosis.
  • Manual mammogram interpretation by radiologists is time-consuming and prone to errors.
  • Computer-aided diagnosis (CADx) systems offer a potential solution to improve diagnostic efficiency and accuracy.

Purpose of the Study:

  • To develop and evaluate a CADx system for automated breast cancer detection and classification from mammograms.
  • To assess the system's performance in distinguishing between normal, benign, and malignant mammographic findings.

Main Methods:

  • Utilized mammograms from the Mammographic Image Analysis Society database.
  • Extracted 15 textural features using gray level co-occurrence matrix at various angles and distances.
  • Employed a two-stage support vector machine for classification of mammograms.

Main Results:

  • Achieved 100% sensitivity and specificity in detecting any abnormality (normal vs. abnormal).
  • Classified abnormalities with 94.4% sensitivity and 91.3% specificity for benign/malignant distinction.
  • Demonstrated high positive predictive value (89.5%) and negative predictive value (95.5%).

Conclusions:

  • Automated CADx systems show significant potential in assisting radiologists with breast cancer diagnosis.
  • The proposed system can enhance the accuracy and efficiency of mammogram interpretation.
  • CADx systems represent a valuable tool for improving breast cancer detection rates and patient outcomes.