Diagnocat Products

STL / 3D segmentation

Automatic segmentation can convert a CBCT to 3D STL models used in digital dentistry.
Highly accurate automated segmentation of CBCT images with the possibility of splitting STL files. Creating 3D models with Diagnocat is a preliminary step for further planning, modeling in specialized software or printing of the model using a 3D printer.


Vizualization of the maxillofacial area for communication with the patient. Segmentation allows a doctor to vizualize anatomic features and improve the clinical presentation, and, most importantly, show this to the patient.

STL use cases

Who will benefit from this service?

Prosthodontists, implantologists, and dental technicians

Diagnocat AI creates models of the upper and lower jaws. These are digital analogs of the models that doctors traditionally work with. Digital teeth can be extracted from the model for further planning of guided implant surgery.


Segmentation of all anatomical components, including their volume, as STL files. The surgeon receives files for the upper and lower jaws, as well as individual files for each tooth. This facilitates planning of autotransplantation, bone grafting, augmentations, or designing individual implants or membranes. In this model, the bones of the cranial base are not divided into elements, but presented as a whole.


Diagnocat can segment teeth without the surrounding bone, which is suitable for modeling splints and aligners.
CBCT volumes with a sufficient field-of-view (FOV) enable segmentation of the pharyngeal and laryngeal airways and facial soft tissues.

Use cases


Task 1:

Demonstrate the existing condition to the patient and explain how to treat it.



When orthodontists and dentists explain the diagnosis using conventional jaw models, the patient often does not understand his condition, as the models look abstract and complex.



As an alternative to conventional jaw models, Diagnocat suggests using 3D segmentation. In this case, the patient can see his own face, teeth, and bones. The built-in viewer allows reducing the transparency of the soft tissue and demonstrate pathologies to the patient like in an anatomical atlas. A visual 3D model makes complex medical terms more accessible to the patients and helps convince them that the treatment is really necessary.

Task 2:

To reduce the time to develop a ClinCheck when placing aligners.



When placing aligners, it takes a long time for the orthodontist to take all the measurements in order to achieve maximum accuracy.



Diagnocat combines the intraoral scans and CBCT-generated segmentation. It can also use information about the cranial base structure when planning treatment.


Task 1:

Reduce the time of making a surgical template in third-party software. To place the implant correctly, it is recommended to make a surgical template based on a combination between an intraoral scan and cone beam tomography. For a successful surgery, it is important that the guide will be as accurate as possible.



In complex clinical cases, it is more difficult to ensure the accuracy of the intraoral scan and cone beam tomography.



Diagnocat easily aligns the intraoral scan and CBCT volume into a single coordinate system.

Task 2:

Explain the diagnosis and treatment plan to the patient.




The patient does not understand whether a bone augmentation is really needed, and is not ready to pay extra for it. 




The 3D model generated by Diagnocat displays the structure of the jaw, bones and teeth. 3D segmentation makes it possible to demonstrate the area with insufficient bone to the patient and explain why it is impossible to place an implant without an additional grafting procedure. In this case, Diagnocat is a communication tool that helps convince the patient to accept the chosen treatment.

Explore Diagnocat AI tools

Diagnocat presents a range of solutions tailored to the different needs of your dental practice.