Adaptive Evolutionary Optimization of Deep Learning Architectures for Focused Liver Ultrasound Image Segmentation

Adaptive Evolutionary Optimization of Deep Learning Architectures for Focused Liver Ultrasound Image Segmentation

<b>Background:</b> Liver ultrasound segmentation is challenging due to low image quality and variability. While deep learning (DL) models have been widely applied for medical segmentation, generic pre-configured models may not meet the specific requirements for targeted areas in liver ul...

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Bibliographic Details
Main Authors: Ali Zifan, Katelyn Zhao, Madilyn Lee, Zihan Peng, Laura J. Roney, Sarayu Pai, Jake T. Weeks, Michael S. Middleton, Ahmed El Kaffas, Jeffrey B. Schwimmer, Claude B. Sirlin
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Diagnostics
Subjects:
ultrasound liver segmentation
deep learning optimization
evolutionary genetic algorithm
Online Access:https://www.mdpi.com/2075-4418/15/2/117
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