From medical imaging data to 3D printed anatomical models

被引：178

作者：

Bucking, Thore M. ^{[1
]}

Hill, Emma R. ^{[1
]}

Robertson, James L. ^{[1
]}

Maneas, Efthymios ^{[1
]}

Plumb, Andrew A. ^{[2
]}

Nikitichev, Daniil I. ^{[1
]}

机构：

[1] UCL, Dept Med Phys & Biomed Engn, London, England

[2] UCL, Ctr Med Imaging, London, England

来源：

PLOS ONE | 2017年 / 12卷 / 05期

关键词：

ULTRASOUND; SIMULATION; PHANTOMS;

D O I：

10.1371/journal.pone.0178540

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];

摘要：

Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. Advances in segmentation algorithms and increased availability of three-dimensional (3D) printers have made it possible to create cost-efficient patient-specific models without expert knowledge. We introduce a general workflow that can be used to convert volumetric medical imaging data (as generated by Computer Tomography (CT)) to 3D printed physical models. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. To lower the barrier to entry and provide the best options when aiming to 3D print an anatomical model from medical images, we provide an overview of relevant free and open-source image segmentation tools as well as 3D printing technologies. We demonstrate the utility of this streamlined workflow by creating models of ribs, liver, and lung using a Fused Deposition Modelling 3D printer.

引用

页数：10

共 23 条

[1]

3D-manufactured patient-specific models of congenital heart defects for communication in clinical practice: feasibility and acceptability [J].