Probabilistic visual and electromagnetic data fusion for robust drift-free sequential mosaicking: application to fetoscopy.
Probabilistic visual and electromagnetic data fusion for robust drift-free sequential mosaicking: application to fetoscopy.
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DOI：
10.1117/1.jmi.5.2.021217
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发表时间：
2018-04
期刊：
影响因子：
--
通讯作者：
Ourselin S
中科院分区：
文献类型：
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作者：
Tella-Amo M;Peter L;Shakir DI;Deprest J;Stoyanov D;Iglesias JE;Vercauteren T;Ourselin S
双胎输血综合征最有效的治疗方法是激光光凝胎盘中共有的血管病变。由于血管连接的口径和胎儿镜视野的缩小，定位血管连接极具挑战性。因此，镶嵌技术有利于扩大场景，方便导航，并允许血管光凝决策。基于局部视觉的镶嵌算法由于使用成对变换而固有地随时间漂移。我们建议使用的电磁跟踪器（EMT）传感器安装在胎儿镜的尖端，以获得相机姿态测量，我们纳入一个概率框架，帧到帧的视觉信息，以实现全球一致的顺序马赛克。我们参数化的EMT测量约束的平面和相机构成的问题，以执行全局一致性，同时利用成对的图像关系，在一个顺序的方式，通过使用本地束调整。我们表明，我们的方法是无漂移和执行类似的国家的最先进的全球对齐技术，如光束法平差，虽然计算负担少得多。此外，我们提出了一个版本的捆绑调整，使用EMT信息。我们证明了对EMT噪声和视觉信息丢失的鲁棒性，并评估了合成，基于幻影和体外数据集的马赛克。
The most effective treatment for twin-to-twin transfusion syndrome is laser photocoagulation of the shared vascular anastomoses in the placenta. Vascular connections are extremely challenging to locate due to their caliber and the reduced field-of-view of the fetoscope. Therefore, mosaicking techniques are beneficial to expand the scene, facilitate navigation, and allow vessel photocoagulation decision-making. Local vision-based mosaicking algorithms inherently drift over time due to the use of pairwise transformations. We propose the use of an electromagnetic tracker (EMT) sensor mounted at the tip of the fetoscope to obtain camera pose measurements, which we incorporate into a probabilistic framework with frame-to-frame visual information to achieve globally consistent sequential mosaics. We parametrize the problem in terms of plane and camera poses constrained by EMT measurements to enforce global consistency while leveraging pairwise image relationships in a sequential fashion through the use of local bundle adjustment. We show that our approach is drift-free and performs similarly to state-of-the-art global alignment techniques like bundle adjustment albeit with much less computational burden. Additionally, we propose a version of bundle adjustment that uses EMT information. We demonstrate the robustness to EMT noise and loss of visual information and evaluate mosaics for synthetic, phantom-based and ex vivo datasets.