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Improvement method for cervical cancer detection: A comparative analysis.

Nur Ain Alias¹, Wan Azani Mustafa^1,2, Mohd Aminudin Jamlos³

¹Faculty of Electrical Engineering & Technology, Universiti Malaysia Perlis, UniCITI Alam Campus, Sungai Chuchuh, Padang Besar, 02100 Perlis, Malaysia.

Oncology Research

|June 12, 2023

Summary

This summary is machine-generated.

This study reviews automated cervical cancer detection methods, finding that thresholding and region boundary tracing effectively identifies cell nuclei in Pap smear images, improving diagnostic accuracy.

Keywords:

Cervical cancer detection images pap smear

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Area of Science:

Medical Imaging
Computational Pathology
Oncology

Background:

Cervical cancer is a significant global health issue, with manual diagnosis of Pap smear images leading to potential inaccuracies.
Automated detection methods are crucial for improving the accuracy and efficiency of cervical cancer diagnosis.

Purpose of the Study:

To review and evaluate various automated methods for cervical cancer detection, focusing on nucleus detection in Pap smear images.
To compare the performance of selected methods using the Herlev Dataset and identify the most effective techniques.

Main Methods:

A review of pre-processing techniques, nucleus detection frameworks, and performance analysis of selected methods was conducted.
Four methods based on reviewed techniques were experimentally evaluated using MATLAB on the Herlev Dataset.

Main Results:

Method 1 (Thresholding and Trace region boundaries) achieved high performance metrics: precision 1.0, sensitivity 98.77%, specificity 98.76%, and accuracy 98.77% for single cell types.
Average performance across methods included precision 0.99, sensitivity 90.71%, specificity 96.55%, and accuracy 92.91%.

Conclusions:

The reviewed methods, particularly Method 1, demonstrate superior performance in nucleus detection compared to existing approaches.
This study highlights the value of established detection techniques and provides a foundation for developing advanced cervical cancer diagnostic solutions.