SlicerMorph: An open and extensible platform to retrieve, visualize and analyze 3D morphology

Abstract

Large scale digitization projects such as #ScanAllFishes and oVert are generating high-resolution microCT scans of vertebrates by the thousands. Data from these projects are shared with the community using aggregate 3D specimen repositories like MorphoSource through various open licenses. MorphoSource currently hosts tens of thousands of 3D scans of eukaryotes. Along with the data from similarly scoped projects such as 10kPhenomes, DigiMorph and many others, soon hundreds of thousands of specimens that represent biodiversity of extinct and extant organisms will be conveniently available to researchers. We anticipate an explosion of quantitative research in organismal biology with the convergence of available data and the methodologies to analyze them.Though the data are available, the road from a series of images to analysis is fraught with challenges for most biologists. It involves tedious tasks of data format conversions, preserving spatial scale of the data accurately, 3D visualization and segmentations, acquiring measurements and annotations. When scientists use commercial software with proprietary formats, a roadblock for data exchange, collaboration, and reproducibility is erected that hurts the efforts of the scientific community to broaden participation in research. Another relevant concern is that ultimate derivative data from individual research projects (e.g., 3D models of segmentation) are shared in formats that do not preserve the correct spatial scale of the data.In this paper, we present our effort to tackle challenges biologists face when conducting 3D specimen-based research. We developed SlicerMorph as an extension of 3D Slicer, a biomedical visualization and analysis ecosystem with extensive visualization and segmentation capabilities built on proven python-scriptable open-source libraries such as Visualization Toolkit and Insight Toolkit. In addition to the core functionalities of Slicer, SlicerMorph provides users with modules to conveniently retrieve open-access 3D models or import users own 3D volumes, to annotate 3D curve and patch-based landmarks, generate canonical templates, conduct geometric morphometric analyses of 3D organismal form using both landmark-driven and landmark-free approaches, and create 3D animations from their results. We highlight how these individual modules can be tied together to establish complete workflow(s) from image sequence to morphospace. Our software development efforts were supplemented with short courses and workshops that cover the fundamentals of 3D imaging and morphometric analyses as it applies to study of organismal form and shape in evolutionary biology, and extensive links to the existing tutorials are provided as supplemental material.Our goal is to establish a community of organismal biologists centered around Slicer and SlicerMorph to facilitate easy exchange of data and results and collaborations using 3D specimens. Our proposition to our colleagues is that using a common open platform supported by a large user and developer community ensures the longevity and sustainability of the tools beyond the initial development effort.

Computational anatomy and geometric shape analysis enables analysis of complex craniofacial phenotypes in zebrafish

“…To explore differences between bmp1a and wildtype fish, we first ran a Generalized Procrustes Analysis on the 372 pseudo-landmark points using the GPA module in SlicerMorph (Rolfe et al, 2021). Procrustes ANOVA on principal components is used to assess the significance of PCA results using the geomorph package in R (Adams and Otárola-Castillo, 2013).…”

“…Pseudo-landmarks are geometrically constructed points. SlicerMorph's PseudoLMGenerator provides a convenient interface to estimate a dense point-cloud from a mesh, using its geometry (Rolfe et al, 2021; Figure 1). For bilaterally symmetric structures, PseudoLMGenerator allows users to define the axis of symmetry around which pseudo-landmarks are symmetrically reflected, allowing for asymmetry analyses.…”

“…To place pseudo-landmark points on each of our specimens, we first created 3D models of from our ct volumes using the Segment Editor module of 3D Slicer (Fedorov et al, 2012). To generate a set of pseudo-landmark points on our atlas model, we used the PseudoLMGenerator module in the SlicerMorph extension of 3D Slicer which uses the original mesh geometry and a sagittal plane as the axis of symmetry, to generate a dense point cloud (Rolfe et al, 2021). One author (KMD) then went through the pseudo-landmarks and removed points that were on both jaws and the pectoral girdle using the MarkupEditor tool in 3D Slicer (Rolfe et al, 2021; Figure 1).…”

“…To generate a set of pseudo-landmark points on our atlas model, we used the PseudoLMGenerator module in the SlicerMorph extension of 3D Slicer which uses the original mesh geometry and a sagittal plane as the axis of symmetry, to generate a dense point cloud (Rolfe et al, 2021). One author (KMD) then went through the pseudo-landmarks and removed points that were on both jaws and the pectoral girdle using the MarkupEditor tool in 3D Slicer (Rolfe et al, 2021; Figure 1). Both of these structures are highly prone to plastic post-mortem deformation due to handling and preservation, as such they represent confounding non-biological variation.…”

“…We also ran separate principal components analyses on both the symmetric and asymmetric components of variation from the symmetry analysis using the geomprph package in R (Adams and Otárola-Castillo, 2013). Visualizations were created in the SlicerMorph extension of 3D Slicer (Rolfe et al, 2021) and using ggplot in R (Wickham, 2016).…”