The effect of image resolution on convolutional neural networks in breast ultrasound

The effect of image resolution on convolutional neural networks in breast ultrasound

Purpose: The objective of this research was to investigate the efficacy of various parameter combinations of Convolutional Neural Networks (CNNs) models, namely MobileNet and DenseNet121, and different input image resolutions (REZs) ranging from 64×64 to 512×512 pixels, for diagnosing breast cancer....

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Bibliographic Details
Main Authors: Shuzhen Tang, Chen Jing, Yitao Jiang, Keen Yang, Zhibin Huang, Huaiyu Wu, Chen Cui, Siyuan Shi, Xiuqin Ye, Hongtian Tian, Di Song, Jinfeng Xu, Fajin Dong
Format: Article
Language:English
Published: Elsevier 2023-08-01
Series:Heliyon
Subjects:
Artificial intelligence
Convolutional neural networks
Breast cancer
Ultrasound
Image resolution
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023064617

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http://www.sciencedirect.com/science/article/pii/S2405844023064617

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