A framework for automatic creation of gold-standard rigid 3D–2D registration datasets

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• 作者：Hennadii Madan ; Franjo Pernuš ; Boštjan Likar…
• 关键词：Image guidance ; C ; arm ; Registration ; Gold standard ; Fiducial marker ; Endovascular
• 刊名：International Journal of Computer Assisted Radiology and Surgery
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：12
• 期：2
• 页码：263-275
• 全文大小：
• 刊物主题：Imaging / Radiology; Surgery; Health Informatics; Computer Imaging, Vision, Pattern Recognition and Graphics; Computer Science, general;
• 出版者：Springer International Publishing
• ISSN：1861-6429
• 卷排序：12

文摘

PurposeAdvanced image-guided medical procedures incorporate 2D intra-interventional information into pre-interventional 3D image and plan of the procedure through 3D/2D image registration (32R). To enter clinical use, and even for publication purposes, novel and existing 32R methods have to be rigorously validated. The performance of a 32R method can be estimated by comparing it to an accurate reference or gold standard method (usually based on fiducial markers) on the same set of images (gold standard dataset). Objective validation and comparison of methods are possible only if evaluation methodology is standardized, and the gold standard  dataset is made publicly available. Currently, very few such datasets exist and only one contains images of multiple patients acquired during a procedure. To encourage the creation of gold standard 32R datasets, we propose an automatic framework.