Improving Performance of Breast Lesion Classification Using a ResNet50 Model Optimized with a Novel Attention Mechanism
<b>Background:</b> The accurate classification between malignant and benign breast lesions detected on mammograms is a crucial but difficult challenge for reducing false-positive recall rates and improving the efficacy of breast cancer screening. <b>Objective:</b> This study...
Auteurs principaux: | Warid Islam, Meredith Jones, Rowzat Faiz, Negar Sadeghipour, Yuchen Qiu, Bin Zheng |
---|---|
Format: | Article |
Langue: | English |
Publié: |
MDPI AG
2022-09-01
|
Collection: | Tomography |
Sujets: | |
Accès en ligne: | https://www.mdpi.com/2379-139X/8/5/200 |
Documents similaires
-
FC-ResNet: A Multilingual Handwritten Signature Verification Model Using an Improved ResNet with CBAM
par: Yusnur Muhtar, et autres
Publié: (2023-07-01) -
A Hybrid Deep Learning Model for Enhanced Structural Damage Detection: Integrating ResNet50, GoogLeNet, and Attention Mechanisms
par: Vikash Singh, et autres
Publié: (2024-11-01) -
Chemical Process Fault Diagnosis Based on Improved ResNet Fusing CBAM and SPP
par: Xiaochen Yan, et autres
Publié: (2023-01-01) -
Diamond particle clarity detection method based on CBAM-ResNet50
par: Wenqian FEI, et autres
Publié: (2024-10-01) -
Adulteration Detection of Pork in Mutton Using Smart Phone with the CBAM-Invert-ResNet and Multiple Parts Feature Fusion
par: Zongxiu Bai, et autres
Publié: (2023-09-01)