Date of Award

12-2024

Degree Name

MS in Electrical Engineering

Department/Program

Electrical Engineering

College

College of Engineering

Advisor

Wayne Pilkington

Advisor Department

Electrical Engineering

Advisor College

College of Engineering

Abstract

This paper focuses on improving speckle reduction and denoising performance in ultrasound images by leveraging neural networks. A dataset of simulated ultrasound images was created using Field-II simulation software based on CT scan images, to create clean and noisy image pairs. Various Convolutional Neural Network models based on U-Net and generative adversarial networks were developed and tested. Peak Signal-to-Noise-Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) were used as metrics along with qualitative assessment. Results show that our tuned U-Net generator network outperformed traditional filtering such as Lee and BM3D.

Share

COinS