回归本源:使用基于图像的统计形状模型重建大型复杂颅骨缺损。

IF 3.5 3区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Systems Pub Date : 2024-05-23 DOI:10.1007/s10916-024-02066-y
Jianning Li, David G Ellis, Antonio Pepe, Christina Gsaxner, Michele R Aizenberg, Jens Kleesiek, Jan Egger
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引用次数: 0

摘要

即使对于专业设计人员来说,为巨大而复杂的颅骨缺损设计植入体也是一项极具挑战性的任务。目前,设计过程自动化的工作主要集中在卷积神经网络(CNN)上,它在重建合成缺陷方面取得了最先进的成果。然而,现有的基于卷积神经网络的方法很难应用到颅骨整形的临床实践中,因为它们在大型复杂颅骨缺损上的表现仍不能令人满意。在本文中,我们提出了一种统计形状模型(SSM),该模型直接建立在以二元体素占位网格表示的头骨分割掩模上,并在多个颅骨植入物设计数据集上对其进行了评估。结果表明,虽然基于 CNN 的方法在合成缺陷上优于 SSM,但在大型、复杂和真实世界的缺陷上却不如 SSM。根据经验丰富的神经外科医生的评估,SSM 生成的植入物在经过少量手动修正后可用于临床。数据集和 SSM 模型可通过 https://github.com/Jianningli/ssm 公开获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model.

Designing implants for large and complex cranial defects is a challenging task, even for professional designers. Current efforts on automating the design process focused mainly on convolutional neural networks (CNN), which have produced state-of-the-art results on reconstructing synthetic defects. However, existing CNN-based methods have been difficult to translate to clinical practice in cranioplasty, as their performance on large and complex cranial defects remains unsatisfactory. In this paper, we present a statistical shape model (SSM) built directly on the segmentation masks of the skulls represented as binary voxel occupancy grids and evaluate it on several cranial implant design datasets. Results show that, while CNN-based approaches outperform the SSM on synthetic defects, they are inferior to SSM when it comes to large, complex and real-world defects. Experienced neurosurgeons evaluate the implants generated by the SSM to be feasible for clinical use after minor manual corrections. Datasets and the SSM model are publicly available at https://github.com/Jianningli/ssm .

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来源期刊
Journal of Medical Systems
Journal of Medical Systems 医学-卫生保健
CiteScore
11.60
自引率
1.90%
发文量
83
审稿时长
4.8 months
期刊介绍: Journal of Medical Systems provides a forum for the presentation and discussion of the increasingly extensive applications of new systems techniques and methods in hospital clinic and physician''s office administration; pathology radiology and pharmaceutical delivery systems; medical records storage and retrieval; and ancillary patient-support systems. The journal publishes informative articles essays and studies across the entire scale of medical systems from large hospital programs to novel small-scale medical services. Education is an integral part of this amalgamation of sciences and selected articles are published in this area. Since existing medical systems are constantly being modified to fit particular circumstances and to solve specific problems the journal includes a special section devoted to status reports on current installations.
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