Thank you Dr. Buser for the article. I found it very informative and I 
definitely liked the inclusion of the supplemental videos.

On Monday, August 31, 2020 at 5:23:44 PM UTC-7 [email protected] wrote:

> Eric,
>
> Just adding to Murat's excellent advice here: the quadratic edge collapse 
> function in Meshlab is very useful for reducing file size of 3D objects. 
> For my work, I specify a target of 500,000 faces and that gives me a good 
> balance between not losing too much information in the object, but reducing 
> the object to a manageable file size for downstream analysis (e.g., reading 
> into R via geomorph, or the IDAV landmark editor program).
>
> Some colleagues and I put together a workflow for processing and analyzing 
> CT data using the programs Fiji and 3D Slicer, both of which are 
> open-source and cross platform. The workflow is built around working with 
> CT data, but includes step-by-step instruction for cleaning up and 
> exporting 3D models in 3D Slicer (Steps 7b, 7c, and 7d), as well as video 
> tutorials in the supplemental materials that demonstrate 3D model 
> simplification and file conversion using Meshlab (Supplementary Video S3), 
> which may be useful in your work. The workflow is available for free from 
> the open access journal, Integrative Organismal Biology here 
> <https://academic.oup.com/iob/article/2/1/obaa009/5818881> (
> https://doi.org/10.1093/iob/obaa009).  
>
> I hope that helps and best of luck,
> Thaddaeus Buser
>
>
>
> On Friday, August 28, 2020 at 8:42:29 PM UTC-7 [email protected] wrote:
>
>> Eric,
>>
>> These are all excellent questions to ponder about, particularly when you 
>> are starting with 3D digitization and morphometrics. Questions you ask 
>> require validation. The first one, stitching of individual mesh elements to 
>> form a 3D object, is the hardest one to quantify, because it requires an 
>> independently acquired image of the same object at a high-resolution 
>> (preferably with a modality like tomography) so that you can treat that as 
>> a gold reference. Or you might consider scanning an object of known 
>> dimensions (e.g., sphere, cube), and then you can compare your results from 
>> geometric estimates (of volume, area) to the digitized one. From there it 
>> is somewhat easy to generate heatmaps that will  let you visualize the 
>> difference between your gold-reference and your digitization. Once you 
>> establish this flow, you can then experiment with your different algorithms 
>> of stitching and/or data acquisition. 
>>
>> The approach in the second part of the question is the same, but it is 
>> easier because that point your original mesh would be the reference. Then 
>> you can experiment with de-noising, smoothing, and remeshing steps and keep 
>> comparing those to your original mesh to understand the effects of it. I am 
>> not entirely sure if there is strict order applying the filters, it is more 
>> about the end result really. I think for stereophotogrammetry steps more 
>> like fuse, repair, clean. Whether you need remeshing or smoothing (or both) 
>> will be dependent on your downstream pipeline (e.g., if the tool you are 
>> using expecting fairly uniformly distributed polygons to create semi 
>> landmark, you will probably need to remesh). 
>>
>> Again these are all empirical test, and you shouldn't take anybody 
>> (including mine) as gospel to follow strictly, the idea is to experiment 
>> and see the results for your particular data. Meshlab is very powerful for 
>> this, but some of these (particularly some of the clean up tasks) can be 
>> accomplished fairly easily in 3D Slicer using as well. For a conceptually 
>> similar exercise on the effect of decimation to mesh geometry you can take 
>> a look at this tutorial from our recent workshop. 
>>
>> https://github.com/SlicerMorph/S_2020/blob/master/Day_4/Surface_Toolbox/Mesh_edits.md
>>
>> HTH,
>> M
>>
>> On Friday, August 28, 2020 at 5:27:25 PM UTC-7 [email protected] wrote:
>>
>>> Hello everyone,
>>>
>>> I'm just starting out in 3D GM and I'm really stuck when it comes to 
>>> figuring out a workflow for producing 3D surface meshes that are de-noised 
>>> without losing topological integrity, making them suitable for analysis.
>>>
>>> I've been using a NextEngine Ultra HD laser scanner for producing scans. 
>>> I've then been moving the scans into Meshlab to to do everything else, from 
>>> aligning and fusing to repairing and smoothing. I've come to view the 
>>> number of filters in Meshlab to be both a blessing and a curse. I've also 
>>> looked into MeshMixer, but everything seems to be black-boxed, and that 
>>> make me a little uneasy.
>>>
>>> I'm also confused as to the order of steps. Should I fuse my scans and 
>>> then clean and repair, or vice versa? What is the best way to de-noise? 
>>> Should I smooth or remesh? In what order should I be applying filters?
>>>
>>> I'm hoping that someone here might be able to suggest a workflow to 
>>> guide me through the process or direct me to some publications that can 
>>> answer all of my questions. Also feel free to suggest some other 3D mesh 
>>> applications that I'm likely not aware of.
>>>
>>> Any advice would be greatly appreciated. Thanks everyone!
>>>
>>> Best,
>>> Eric
>>>
>>

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