An Edge-Based Selection Method for Improving Regions-of-Interest Localizations Obtained Using Multiple Deep Learning Object-Detection Models in Breast Ultrasound Images

An Edge-Based Selection Method for Improving Regions-of-Interest Localizations Obtained Using Multiple Deep Learning Object-Detection Models in Breast Ultrasound Images

Computer-aided diagnosis (CAD) systems can be used to process breast ultrasound (BUS) images with the goal of enhancing the capability of diagnosing breast cancer. Many CAD systems operate by analyzing the region-of-interest (ROI) that contains the tumor in the BUS image using conventional texture-b...

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Bibliographic Details
Main Authors: Mohammad I. Daoud, Aamer Al-Ali, Rami Alazrai, Mahasen S. Al-Najar, Baha A. Alsaify, Mostafa Z. Ali, Sahel Alouneh
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Sensors
Subjects:
medical ultrasound imaging
breast ultrasound images
computer-aided diagnosis
region-of-interest localization
deep learning object-detection models
deep learning edge-detection models
Online Access:https://www.mdpi.com/1424-8220/22/18/6721

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https://www.mdpi.com/1424-8220/22/18/6721

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