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首页> 外文会议>International Conference on Computer Communication and Informatics >Computer Vision Based Vessel Seam Detection And Tracking In Fetoscopic Images
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Computer Vision Based Vessel Seam Detection And Tracking In Fetoscopic Images

机译：基于计算机视觉的血管镜图像中的接缝检测与跟踪

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In Twin to twin transfusion syndrome in monochrome twin pregnancies, fetus communicated through Arterio arteries, Veno Venus, Artery to Vein seam. During fetoscopic laser occlusion surgery, the identification of artery and vein separation hasthe misperception due to its color resemblance. In digital fetoscopic images the artery occurs in the bright red region, vein occurs in dark red region, Artery to vein communicative blood vessel and it is correlation regions are needed for surgery. Manually identification of these vessels is highly complicated when the laser beam is passed through the vessels. To overcome this problem, Color region based Vector Quantization method is proposed to identify the artery to vein junction. This method differentiate regions based on the colour resemblance. In this proposed method, Artery to artery (AA),Vein to Vein (VV),Artery to vein(AV) region based samples are taken to distinguish AV anastomos and coagulation. Various state of fetoscopic images are analysed based on different radiation conditions. Proposed method separates AA, VV & AV regions. Automated vessel detection and separation of different vessel regions were achieved using a system based on fetoscopic laser applied images. The automated system provides a clinically feasible and supportive method during fetus surgery. This method may be improved further for computer- or robot-assisted applications.
机译：在单色双胞胎妊娠中的双胞胎输血综合征，胎儿通过动脉动脉，静脉VEINU，动脉沟通静脉接缝。在胎儿激光闭塞手术期间，由于其颜色相似，动脉和静脉分离的鉴定具有误解。在数字胎面图像中，动脉发生在明亮的红色区域中，静脉发生在深红色区域，动脉到静脉交互血管，并且手术需要相关区域。当激光束穿过血管时，手动识别这些血管是高度复杂的。为了克服这个问题，提出了基于颜色的矢量量化方法以识别静脉结的动脉。该方法基于颜色相似区分区域。在这种提出的方​​法中，对动脉（AA）的动脉（AA），静脉（VV），动脉对静脉（AV）区的样品被采用以区分AV anaStomos和凝血。基于不同的辐射条件分析各种胎面图像状态。提出的方法分离AA，VV和AV区域。使用基于胎儿激光施加图像的系统实现了自动血管区域的自动血管检测和分离。自动化系统在胎儿手术期间提供临床可行和支持性的方法。对于计算机或机器人辅助应用，可以进一步提高该方法。

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