Hu Yuzhi, Limaye Ajay, Lu Jing
CT Lab, Department of Materials Physics, Research School of Physics, Australian National University, Canberra, ACT 2601, Australia.
National Computational Infrastructure, Building 143, Corner of Ward Road and Garran 7 Road, Ward Rd, Canberra, ACT 2601, Australia.
R Soc Open Sci. 2024 Jun 12;11(6):240375. doi: 10.1098/rsos.240375. eCollection 2024 Jun.
3D visualization and segmentation are increasingly widely used in physical, biological and medical science, facilitating advanced investigative methodologies. However, the integration and reproduction of segmented volumes or results across the spectrum of mainstream 3D visualization platforms remain hindered by compatibility constraints. These barriers not only challenge the replication of findings but also obstruct the process of cross-validating the accuracy of 3D visualization outputs. To address this gap, we developed an innovative revisualization method implemented within the open-source framework of , a 3D visualization software. Leveraging four animal samples alongside three mainstream 3D visualization platforms as case studies, our method demonstrates the seamless transferability of segmented results into . This capability effectively fosters a new avenue for authentication and enhanced scrutiny of segmented data. By facilitating this interoperability, our approach underscores the potential for significant advancements in accuracy validation and collaborative research efforts across diverse scientific domains.
三维可视化和分割在物理、生物和医学科学中应用越来越广泛，为先进的研究方法提供了便利。然而，主流三维可视化平台之间分割体积或结果的整合与再现仍受兼容性限制的阻碍。这些障碍不仅对研究结果的复制构成挑战，也阻碍了对三维可视化输出准确性进行交叉验证的过程。为弥补这一差距，我们在三维可视化软件的开源框架内开发了一种创新的再可视化方法。以四个动物样本和三个主流三维可视化平台作为案例研究，我们的方法展示了分割结果到该软件中的无缝可转移性。这种能力有效地为分割数据的验证和更严格审查开辟了一条新途径。通过促进这种互操作性，我们的方法凸显了在不同科学领域的准确性验证和合作研究方面取得重大进展的潜力。
