Acta Optica Sinica, Volume. 45, Issue 3, 0317001(2025)
Deep Learning-Based Denoising Algorithm for Photoacoustic Endoscopy Targeting Time-Domain Data
Fig. 1. PAE/USE system diagram[16]. (a) Schematic diagram of the structure of the photoacoustic/ultrasonic endoscopic system; (b) experimental data collection of rabbit rectum in vivo
Fig. 2. Raw A-line data, results of noise reduction with 6-time averaging and 60-time averaging
Fig. 3. Simulated endoscopic system acquisition. (a) Acquisition method simulated by the simulated image; (b) original synthetic image; (c) image after adding noise to Fig. 3(a)
Fig. 6. Simulation data and denoising results of wavelet transform, singular value decomposition, UNet-2D, Wave-UNet, Aline-CNN, and Aline-UNet. (a) Original simulation image as the reference image; (b) simulation image after noise addition; (c) reconstructed image from denoised output using wavelet transform; (d) reconstructed image from denoised output using singular value decomposition; (e) reconstructed image from denoised output using UNet-2D; (f) reconstructed image from denoised output using Wave-UNet; (g) reconstructed image from denoised output using Aline-UNet; (h) reconstructed image from denoised output using Aline-CNN; (i) SSIM comparison result; (j) magnified image of the area indicated by arrows in S1‒S8; (k) average PSNR comparison result; (l) difference images between the areas indicated by arrows in R1‒R6
Fig. 7. Comparison of photoacoustic data denoising reconstruction results by Aline-CNN and Aline-UNet models. (a) Photoacoustic results of rectum collected once; (b) average results after six times; (c) average results after 60 times; (d) results of Aline-CNN model after denoising; (e) results of Aline-UNet model after denoising; (f) SSIM comparison results and corresponding PSNR comparison results within ROI 1 and ROI 2 regions images
Fig. 8. Comparison of ultrasonic data denoising reconstruction results by Aline-CNN and Aline-UNet models. (a) Ultrasonic results of rectal rectum collected once; (b) average results after 6 times; (c) average results after 60 times; (d) results of Aline-CNN model after denoising; (e) results of Aline-UNet model after denoising; (f) SSIM comparison results and corresponding PSNR comparison results within ROI 1 and ROI 2 regions images
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Minhao Li, Zhuojun Xie, Yang Tang, Jiaying Xiao. Deep Learning-Based Denoising Algorithm for Photoacoustic Endoscopy Targeting Time-Domain Data[J]. Acta Optica Sinica, 2025, 45(3): 0317001
Category: Medical optics and biotechnology
Received: Sep. 21, 2024
Accepted: Nov. 18, 2024
Published Online: Feb. 19, 2025
The Author Email: Xiao Jiaying (jiayingxiao@csu.edu.cn)
CSTR:32393.14.AOS241580