Optimized Double-Regional Filtering Algorithm on MRI Three-Dimensional Reconstructed Images for the Evaluation of Effects of Delivery on the Pelvis of Primiparas

Qiong Jin,Zhang Shen,Shansan Wu,Jun Lin,Haibing Wang,Mian Huang,Gustavo Ramirez

doi:10.1155/2021/7985624

Abstract

This study was to explore the denoising and segmentation effect of dual-domain image denoising (DDID) algorithm, and the Galois field (GF) and nonlocal means (NLM) algorithms were introduced for comparative analysis. 40 primiparas in the hospital from January 2018 to January 2020 were divided into an experimental group (caesarean section (CS), group E) and a control group (vaginal delivery (VD), group C). The peak signal-to-noise ratio (PSNR) and segmentation parameters of DDID algorithm were compared with GF algorithm and NLM algorithm. It was found that the DDID showed higher overall accuracy (OA) and lower false positive rate (FPR) and false negative rate (FNR). The PSNR of DDID was higher than the other two algorithms. GF algorithm showed the highest edge retention index (ERI). The incidence of pelvic organ prolapse (POP) in group E and group C was 9/20 (45%) and 5/20 (25%), respectively, with extreme difference ( P < 0.05 ). Evaluation of the effects of delivery on the pelvis of primiparas with MRI three-dimensional (3D) reconstructed images based on the optimized DDID showed a superior and stable denoising effect and good segmentation, so it was worthy of clinical promotion and application.

Highlights

VD affects the pelvic muscles, nerves, and connective tissues, which may be considered clinically as missing tissue Pelvic Floor (PF) support
Comparison on Segmentation Parameters of Pelvic MRI Images of Various Algorithms. e results of analyzing the pelvic MRI image segmentation parameters of different algorithms are shown in Figure 2 and Figure 3. e overall accuracy (OA), false positive rate (FPR), and false negative rate (FNR) of the dual-domain image denoising (DDID) algorithm were 0.805, 0.0372, and 0.0382, respectively; those of Galois field (GF) were 0.745, 0.0765, and 0.0745, respectively; and those of nonlocal means (NLM) were 0.727, 0.1240, Figure 1: MRI images of primiparas
edge retention index (ERI) of GF algorithm was the highest, and that of the other two algorithms was not different greatly. ere was no observable different for POP degree of 20 patients at the 9 months and 6 months (P > 0.05). e visual effects of the three MRI images after denoising by the DDID algorithm were obviously better than those of the GF and NLM algorithms, which was in consistence with the results of Ai and Ren [10]. e noise was removed completely by the DDID algorithm, and the image was relatively smooth, effectively avoiding the “blocking effect” in the image, which appeared in the MRI image after denoising by the NLM algorithm

Summary

Introduction

VD affects the pelvic muscles, nerves, and connective tissues, which may be considered clinically as missing tissue Pelvic Floor (PF) support. E environmental factors and VD can affect the pathogenesis of pelvic floor disorders. The possible factors affecting muscles, nerves, and connective tissues include tissue healing during postpartum recovery, menstrual period (the first 8 weeks after delivery), and PF function during postpartum strengthening (the rest duration of one year after delivery). Pregnancy and delivery are the main risk factors for PF disorders, and clinical manifestations only occur when the disease is serious. They are diagnosed with PF disorders based on objective findings, the most common symptoms include POP, stress urinary incontinence (SUI), and fecal urinary incontinence (FUI).

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Discussion

Conclusion