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Registration of Breast Surface Data Before and After Surgical Intervention

机译:外科手术前后乳房表面数据的记录

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Surgery planing of breast cancer interventions is gaining importance among physicians, who recognize value in discussing the possible aesthetic outcomes of surgery with patients. Research is been propelled to create patient-specific breast models, but breast image registration algorithms are still limited, particularly for the purpose of matching pre- and post-surgical data of patient's breast surfaces. Yet, this is a fundamental task to learn prediction models of breast healing process after surgery. In this paper, a coarse-to-fine registration strategy is proposed to match breast surface data acquired before and after surgery. Methods are evaluated in their ability to register surfaces in an anatomical reliable way, and results suggest proper alignment adequated to be used as input to train deformable models.
机译:乳腺癌干预的手术计划在医生中变得越来越重要,他们认识到在与患者讨论手术可能产生的美学结果方面的价值。推进了研究以创建患者特定的乳房模型,但是乳房图像配准算法仍然受到限制,特别是为了匹配患者的乳房表面的术前和术后数据。然而,这是学习手术后乳房愈合过程的预测模型的一项基本任务。在本文中,提出了一种从粗到细的配准策略,以匹配手术前后获取的乳房表面数据。对方法以解剖学上可靠的方式注册表面的能力进行了评估,结果表明适当的对齐方式足以用作训练可变形模型的输入。

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