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Ultrasonography

Ultrasonography

Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...

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Summary

This summary is machine-generated.

This study benchmarks deep learning models for breast lesion classification in ultrasound images. EfficientNet achieved the highest accuracy (97.65%), demonstrating its clinical potential for breast cancer diagnosis.

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Area of Science:

Medical Imaging
Artificial Intelligence
Oncology

Background:

Accurate breast lesion classification in ultrasound images is challenging due to image quality and variability.
Computer-aided diagnosis systems using deep learning can aid breast cancer diagnosis and reduce observer variability.

Purpose of the Study:

To benchmark six state-of-the-art convolutional neural networks for breast lesion classification in ultrasound images.
To evaluate the impact of segmentation information on classification performance.
To identify optimal deep learning models for clinical application.

Main Methods:

Compared GoogLeNet, InceptionV3, ResNet, DenseNet, MobileNetV2, and EfficientNet on multi-center BUS datasets (BUSI, UDIAT).
Tested five input data variations, including segmentation information, for each network.
Evaluated performance using precision, sensitivity, F1-score, accuracy, and AUC.

Main Results:

The lesion with a thin border of background input data yielded the best performance across models.
EfficientNet achieved the highest accuracy (97.65%) and AUC (96.30%) with this input variation.
The study provides a standardized evaluation for comparing deep learning models in this domain.

Conclusions:

Deep neural networks show significant potential for clinical breast lesion classification.
EfficientNet is a promising model choice for breast ultrasound image analysis.
Standardized benchmarks are crucial for advancing AI in medical imaging.