锥束计算机断层结构分析可以帮助鉴别牙源性和非牙源性上颌鼻窦炎。

IF 1.7 Q3 DENTISTRY, ORAL SURGERY & MEDICINE
Andre Luiz Ferreira Costa, Karolina Aparecida Castilho Fardim, Isabela Teixeira Ribeiro, Maria Aparecida Neves Jardini, Paulo Henrique Braz-Silva, Kaan Orhan, Sérgio Lúcio Pereira de Castro Lopes
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引用次数: 0

摘要

目的:本研究旨在评估锥形束计算机断层扫描(CBCT)图像的纹理分析(TA)作为鉴别牙源性和非牙源性上颌鼻窦炎(OS和NOS)的定量工具。材料与方法:对诊断为OS (N=20)和NOS (N=20)的40例患者的CBCT图像进行评价。通过在病变图像上手动放置感兴趣区域,提取灰度共生矩阵(GLCM)参数和灰度运行长度矩阵纹理(GLRLM)参数。使用GLCM计算了7个纹理参数,使用GLRLM计算了4个纹理参数。组间比较采用Mann-Whitney检验,方差齐性采用Levene检验(α=5%)。结论:TA可以通过对比、相关、差矩逆等参数对CBCT图像进行OS与NOS的定量区分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Cone-beam computed tomography texture analysis can help differentiate odontogenic and non-odontogenic maxillary sinusitis.

Cone-beam computed tomography texture analysis can help differentiate odontogenic and non-odontogenic maxillary sinusitis.

Cone-beam computed tomography texture analysis can help differentiate odontogenic and non-odontogenic maxillary sinusitis.

Cone-beam computed tomography texture analysis can help differentiate odontogenic and non-odontogenic maxillary sinusitis.

Purpose: This study aimed to assess texture analysis (TA) of cone-beam computed tomography (CBCT) images as a quantitative tool for the differential diagnosis of odontogenic and non-odontogenic maxillary sinusitis (OS and NOS, respectively).

Materials and methods: CBCT images of 40 patients diagnosed with OS (N=20) and NOS (N=20) were evaluated. The gray level co-occurrence (GLCM) matrix parameters, and gray level run length matrix texture (GLRLM) parameters were extracted using manually placed regions of interest on lesion images. Seven texture parameters were calculated using GLCM and 4 parameters using GLRLM. The Mann-Whitney test was used for comparisons between the groups, and the Levene test was performed to confirm the homogeneity of variance (α=5%).

Results: The results showed statistically significant differences (P<0.05) between the OS and NOS patients regarding 3 TA parameters. NOS patients presented higher values for contrast, while OS patients presented higher values for correlation and inverse difference moment. Greater textural homogeneity was observed in the OS patients than in the NOS patients, with statistically significant differences in standard deviations between the groups for correlation, sum of squares, sum of entropy, and entropy.

Conclusion: TA enabled quantitative differentiation between OS and NOS on CBCT images by using the parameters of contrast, correlation, and inverse difference moment.

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来源期刊
Imaging Science in Dentistry
Imaging Science in Dentistry DENTISTRY, ORAL SURGERY & MEDICINE-
CiteScore
2.90
自引率
11.10%
发文量
42
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