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首页> 外文期刊>Medical image analysis >Capturing intraoperative deformations: research experience at Brigham and Women's Hospital.
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Capturing intraoperative deformations: research experience at Brigham and Women's Hospital.

机译：捕获术中变形：在百翰医院和妇女医院的研究经验。

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During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patient's brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and Women's Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy.
机译：在神经外科手术过程中，神经外科医师的目标是在保持健康的脑组织的同时，尽可能多地切除病变组织。在过去的十年中，传统手术室的能力有限，无法使外科医生可视化关键的健康大脑结构和肿瘤边缘，这导致了复杂的术中成像技术的发展，以增强可视化。但是，由于患者放置而引起的僵硬运动以及由于外科手术而发生的非刚性变形都破坏了用于计划手术的术前数据与患者大脑的术中配置之间的对应关系。在其他介入疗法中，例如在肝脏的冷冻消融或前列腺活检中，也面临着类似的挑战。我们已经开发出用于对关键解剖结构的运动进行建模的算法和系统实现，从而使我们能够根据体积图像序列来估计关键解剖结构的变形，并以与手术决策兼容的速率准备术前和术中图像的更新融合可视化图像。本文通过开发和应用新颖的算法来捕获术中变形以支持影像引导治疗的过程，回顾了百翰姆妇女医院的经验。

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