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首页> 外文会议>Image Processing pt.3; Progress in Biomedical Optics and Imaging; vol.8,no.31; Proceedings of SPIE-The International Society for Optical Engineering; vol.6512 pt.3 >Comparative Performance Analysis of Cervix ROI Extraction and Specular Reflection Removal Algorithms for Uterine Cervix Image Analysis
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Comparative Performance Analysis of Cervix ROI Extraction and Specular Reflection Removal Algorithms for Uterine Cervix Image Analysis

机译：宫颈子宫颈图像分析的子宫颈ROI提取和镜面反射去除算法的比较性能分析

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摘要

Cervicography is a technique for visual screening of uterine cervix images for cervical cancer. One of our research goals is the automated detection in these images of acetowhite (AW) lesions, which are sometimes correlated with cervical cancer. These lesions are characterized by the whitening of regions along the squamocolumnar junction on the cervix when treated with 5% acetic acid. Image preprocessing is required prior to invoking AW detection algorithms on cervicographic images for two reasons: (1) to remove Specular Reflections (SR) caused by camera flash, and (2) to isolate the cervix region-of-interest (ROI) from image regions that are irrelevant to the analysis. These image regions may contain medical instruments, film markup, or other non-cervix anatomy or regions, such as vaginal walls. We have qualitatively and quantitatively evaluated the performance of alternative preprocessing algorithms on a test set of 120 images. For cervix ROI detection, all approaches use a common feature set, but with varying combinations of feature weights, normalization, and clustering methods. For SR detection, while one approach uses a Gaussian Mixture Model on an intensity/saturation feature set, a second approach uses Otsu thresholding on a top-hat transformed input image. Empirical results are analyzed to derive conclusions on the performance of each approach.
机译：子宫颈造影术是一种用于宫颈癌子宫颈图像可视化检查的技术。我们的研究目标之一是在这些图像中自动检测乙酰白（AW）病变，这些病变有时与宫颈癌相关。这些病变的特征是当用5％乙酸处理时沿子宫颈鳞状交界处的区域变白。在子宫颈图像上调用AW检测算法之前，需要进行图像预处理，这有两个原因：（1）消除由照相机闪光灯引起的镜面反射（SR），以及（2）从图像中分离出子宫颈感兴趣区域（ROI）与分析无关的区域。这些图像区域可能包含医疗器械，胶片标记或其他非子宫颈解剖结构或区域，例如阴道壁。我们已经定性和定量地评估了120张图像测试集上替代预处理算法的性能。对于子宫颈ROI的检测，所有方法都使用共同的功能集，但功能权重，规范化和聚类方法的组合有所不同。对于SR检测，虽然一种方法在强度/饱和度特征集上使用高斯混合模型，但第二种方法在顶帽转换后的输入图像上使用Otsu阈值处理。分析经验结果以得出每种方法的性能结论。

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