Hi, On behalf of SlicerMorph team, I wanted to point out to a new paper that come out of our group that extends the ALPACA pipeline by supporting multiple-templates. It is open-access and is available here: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0278035
Single template-based LMing method like ALPACA works very well typically in single-species context where morphological disparity among samples is not high, but may be of limited utility in studies with multiple species, or multiple developmental time points. Multi-template ALPACA (MALPACA) overcomes this by using multiple templates during the registrations. There are couple benefits of this approach, some of which has been discussed recently in the forum in context of measurement errors: 1. You increase the accuracy of the final estimate of LM positions. 2. You avoid the risk of "biasing" your automated landmark outcome to your template choice. 3. With multiple estimates of LM positions for each sample, you can implement a post-hoc quality-control analysis. Along with MALPACA, ALPACA now has a "template selection" tab, which uses the point clouds derived from the 3D models and kmeans clustering to suggest samples from your study population to be used as templates. User specifies the grouping structure, as well as how many templates to be selected per group. (Note that any ALPACA analysis assumes that as input, user provides 3D models that are identical in content without missing or extraneous parts.) The method is available as part of the latest SlicerMorph extension. Paper provides a detailed step-by-step instruction both for template selection and MALPACA. An online version of this tutorial can also be found at https://github.com/SlicerMorph/Tutorials/tree/main/MALPACA, which will serve as the most up-to-date documentation. ALPACA proper has got a few updates as well: 1. The default output format is now JSON as opposed to legacy FCSV (you can change it to FCSV using the settings under Advanced settings tab. However we encourage you to use JSON format for better compatibility with Slicer and future-proofing your datasets. You can use SlicerMorphR package to import JSON files into R with its read.markups.json function. 2. Batch mode now supports replication of analysis using the same settings/templates, which can be useful in context of symmetry analyses. 3. ALPACA now can optionally use bayesian CPD for deformable registration phase, which increases the speed about 10X, which is useful for multi-template estimations as well as replications. Please look at the BCPD repo (https://github.com/ohirose/bcpd) for installation instructions on your OS. Finally, a new stable version (v5.2.1) of 3D Slicer is now available at, with lots of new features and bug fixes. All the changes to SlicerMorph listed above are only available for the latest stable. To benefit from them, please make sure to update your Slicer installation to the current stable available at: https://download.slicer.org. You can file bug reports or problems you encountered at https://download.slicer.org. Best wishes, M -- You received this message because you are subscribed to the Google Groups "Morphmet" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/morphmet2/0958edd7-811c-48ca-a280-1b2e2cbe4fadn%40googlegroups.com.
