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First of all, I would like to thank you for developing this fantastic facial landmark positioning tool. It is useful for countless situations and can be very helpful in the field of surgical planning.
I read the article (Paulsen et al., 2018) and studied the tool, in order to port it to the add-on I am developing, called OrtogOnBlender XP (OOB_XP), an evolution of OrtogOnBlender, which is widely used by surgeons in 32 countries in the most critical surgical planning conditions (orthognathic, rhinoplasty, facial prosthetics, etc.).
OOB_XP has a robust CT scan reconstruction system and also photogrammetry. Based on initial tests, I am able to use Deep-MVLM in the models generated by these two means, with a significant success factor for the intended approach.
I created an initial test button that exports the selected model and runs your code, later importing the points in positions consistent with the mesh in the Blender scene.
I took the liberty of naming the anatomical points according to Caple & Stephan (2016) (DOI: 10.1007/s00414-015-1292-1).
I am sending this message to thank you and to present the testing stage, with the table of points. I would like to know if you already had the names of the points or if these I presented are consistent.
A big hug, full of gratitude.
The text was updated successfully, but these errors were encountered:
Dear developers,
First of all, I would like to thank you for developing this fantastic facial landmark positioning tool. It is useful for countless situations and can be very helpful in the field of surgical planning.
I read the article (Paulsen et al., 2018) and studied the tool, in order to port it to the add-on I am developing, called OrtogOnBlender XP (OOB_XP), an evolution of OrtogOnBlender, which is widely used by surgeons in 32 countries in the most critical surgical planning conditions (orthognathic, rhinoplasty, facial prosthetics, etc.).
OOB_XP has a robust CT scan reconstruction system and also photogrammetry. Based on initial tests, I am able to use Deep-MVLM in the models generated by these two means, with a significant success factor for the intended approach.
I created an initial test button that exports the selected model and runs your code, later importing the points in positions consistent with the mesh in the Blender scene.
I took the liberty of naming the anatomical points according to Caple & Stephan (2016) (DOI: 10.1007/s00414-015-1292-1).
MV-CNN Points - Planilhas Google.pdf
I am sending this message to thank you and to present the testing stage, with the table of points. I would like to know if you already had the names of the points or if these I presented are consistent.
A big hug, full of gratitude.
The text was updated successfully, but these errors were encountered: