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Abstract：
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 Drishti, 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 Drishti. 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.
摘要：
三维可视化和分割越来越广泛地应用于物理,生物和医学科学，促进先进的调查方法。然而,在主流3D可视化平台的范围内,分段体积或结果的集成和再现仍然受到兼容性约束的阻碍。这些障碍不仅挑战了结果的复制，而且阻碍了交叉验证3D可视化输出准确性的过程。为了解决这个差距，我们开发了一种在Drishti的开源框架内实现的创新的重新可视化方法，三维可视化软件。利用四个动物样本和三个主流3D可视化平台作为案例研究，我们的方法证明了分段结果到Drishti的无缝可转移性。此功能有效地促进了身份验证的新途径，并增强了对分段数据的审查。通过促进这种互操作性，我们的方法强调了在不同科学领域的准确性验证和合作研究工作方面取得重大进展的潜力.
