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Related Experiment Video

Updated: May 5, 2026

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

Real-Time microcalcification detection with SAAR algorithm.

Aleksandar Peulic¹, Zeljko Jovanovic², Marina Milosevic²

¹Department of Mathematics and Informatics, University of Kragujevac, Faculty of Science, Radoja Domanovica 12, Kragujevac, Serbia.

Technology and Health Care : Official Journal of the European Society for Engineering and Medicine

|May 4, 2026

Summary

This summary is machine-generated.

A new algorithm, Sigmoidal Slope Analysis and Aspect Ratio Evaluation (SAAR), offers efficient, real-time detection of microcalcifications in mammograms on edge devices, improving early breast cancer diagnosis.

Keywords:

Microcalcification detection adaptive approach edge device mammography sigmoid function

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

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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

Area of Science:

Medical Imaging
Artificial Intelligence
Biomedical Engineering

Background:

Mammography is crucial for breast cancer detection, but identifying microcalcifications is challenging.
High sensitivity and efficient processing are needed for accurate microcalcification detection.
Current methods may lack efficiency for real-time applications, especially on edge devices.

Purpose of the Study:

To develop and validate an efficient, edge-device-compatible algorithm for microcalcification detection in mammograms.
To enhance diagnostic efficiency through real-time processing for early breast cancer detection.
To support clinical and remote breast cancer screening settings.

Main Methods:

Developed the Sigmoidal Slope Analysis and Aspect Ratio Evaluation (SAAR) algorithm.
Employed a multi-step adaptive process with sigmoidal functions for contrast enhancement.
Utilized adaptive slope detection and region prioritization for microcalcification identification.

Main Results:

The SAAR algorithm demonstrated improved sensitivity compared to conventional methods on the MIAS database.
Designed for edge devices, enabling real-time processing with lower latency and enhanced privacy.
Successfully enhanced intensity contrast and prioritized regions of interest for accurate detection.

Conclusions:

SAAR integrated with edge devices offers a promising advancement in breast cancer detection.
The algorithm's adaptive nature and edge device compatibility provide a robust solution.
Enhanced efficiency and sensitivity in mammographic microcalcification detection are achieved.