VitorUrel

Thanks for the answer. Certainly, when performing these subsequent segmentation steps, the biomodel will be better defined. The next biomodel that I do I will adopt this methodology and see the result. The work done with the liver and vena cava is impressive. Do you recommend me any material or video to go deeper into the practical use of segmentation techniques? Thank you very much. Regards, Vitor Urel.

In Brazil, many research groups and enthusiasts have contributed to develop face shield to combat the pandemic. I had the opportunity to participate in development and logistics in the Higia group (https://www.projetohigia.com.br), distributed more than 100 thousand units throughout the country. The 3D models were developed in partnership with doctors and health professionals and are available on the project website. Regards, Vitor Urel.

CT images are segmented by a difference of threshold values. Therefore, tissue that present less contrast to each other are more difficult to generate good results with automatic segmentation. As mentioned above, for bone biomodels, many of the software have good results, but even with them it is necessary to perform a computational modeling afterwards, to clean noise and unwanted parts that appear in the segmented biomodel. I have used the InVesalius software (https://invesalius.github.io) for many of the biomodels that I have created. I believe that to achieve High quality in the final result, dedication to the creation of the biomodel is still necessary. I hope I contributed to the discussion. Regards, Vitor Urel.