宫颈癌早期自动检测的预处理
Preprocessing for Automating Early Detection of Cervical Cancer
摘要：
子宫颈癌是世界范围内女性最常见的癌症之一。大多数宫颈癌病例可以通过旨在检测癌前病变的筛查计划来预防。在数字阴道镜检查期间，阴道镜图像或宫颈照片以原始形式采集。它们包含镜面反射，表现为白光严重饱和的亮点，由于子宫颈表面不均匀存在水分而发生。宫颈区域占据原始宫颈照片图像的大约一半。图像的其他部分包含不相关的信息，例如设备、帧、文本和非宫颈组织。这种不相关的信息会混淆子宫颈内组织的自动识别。因此，我们专注于颈部边界，以便我们在相关图像区域上具有几何边界。我们的新技术消除了SR，确定感兴趣的区域，并使宫颈造影准备分割算法。
英文摘要：
Uterine Cervical Cancer is one of the most common forms of cancer in women worldwide. Most cases of cervical cancer can be prevented through screening programs aimed at detecting precancerous lesions. During Digital Colposcopy, colposcopic images or cervigrams are acquired in raw form. They contain specular reflections which appear as bright spots heavily saturated with white light and occur due to the presence of moisture on the uneven cervix surface and. The cervix region occupies about half of the raw cervigram image. Other parts of the image contain irrelevant information, such as equipment, frames, text and non-cervix tissues. This irrelevant information can confuse automatic identification of the tissues within the cervix. Therefore we focus on the cervical borders, so that we have a geometric boundary on the relevant image area. Our novel technique eliminates the SR, identifies the region of interest and makes the cervigram ready for segmentation algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
