System and method for constructing elements of interest (EoI)-focused panoramas of an oral complex

1. A method for constructing a panorama of teeth arch with elements of interest (EoI) visually emphasized for an accurate diagnostic-treatment approach, said method comprising the steps of:

extracting a teeth arch from a volumetric image;

unfolding the extracted teeth arch into a panoramic ribbon;

assigning a higher weight to at least a point in the panoramic ribbon, wherein the at least one point is inside or proximal to an element of interest; and

applying a weighted summation in a direction perpendicular to the teeth arch resulting in the panorama with the (EoI) visually emphasized.

2. The method of claim 1 , wherein the panorama is at least one of a general panorama or split panorama.

3. The method of claim 1 , wherein the teeth arch is extracted using segmentations of at least one of a teeth or anatomy.

4. The method of claim 1 , wherein the panoramic ribbon is a curved sub-volume passing along the teeth arch.

5. The method of claim 1 , further comprising the step of applying a transformation grid to the extracted teeth arch image for unfolding the extracted teeth arch image into the panoramic ribbon.

6. The method of claim 1 , further comprising tilting of the ribbon to maximize perceptibility of a frontal teeth apex.

7. The method of claim 1 , wherein the higher weights are assigned to a plurality of points, each point arbitrarily chosen on the panoramic ribbon.

8. The method of claim 7 , wherein the arbitrarily chosen points are evenly spaced along the length of the panoramic ribbon.

9. The method of claim 1 , wherein the elements of interest are at least one of a bone, tooth, teeth, or mandibular canals.

10. The method of claim 1 , wherein weights are assigned highest to points inside or most proximal to elements of interest with a pre-defined highest value, wherein segmentation of at least one of an anatomy or teeth are applied to assign the weights.

11. The method of claim 1 , further comprising the step of obtaining at least one of a two-dimensional (2D) or three-dimensional (3D) teeth segmentation masks and numbering from an original Cone Beam Computed Tomography (CBCT) scan.

12. The method of claim 11 , further comprising the step of retrieving a three-dimensional bounding box inferred from a two-dimensional panoramic instance from the ribbon; and submit the three-dimensional bounding box as the element of interest for a three-dimensional teeth segmentation mask and numbering from the original CBCT scan.

13. The method of claim 1 , further comprising the step of projecting a two-dimensional (2D) and three-dimensional (3D) teeth segmentation masks onto the panorama; calculating Intersection over Union (IoU) for 2D masks and the projected 3D masks; and selecting the best 3D projections for every 2D instance on the panoramic image.

14. A method for constructing a panorama of teeth arch with elements of interest (EoI) visually emphasized for an accurate diagnostic-treatment approach, said method comprising the steps of:

unfolding an extracted teeth arch into a panoramic ribbon; and

assigning a higher weight to at least one point in the panoramic ribbon, wherein higher weights are assigned for points inside or proximal to an EoI resulting in the panorama with the EoI visually emphasized in a non-distorting manner.

15. A system for constructing an Element of Interest (EoI)-focused panorama emphasized for an accurate diagnostic-treatment approach, said system comprising:

a processor;

a non-transitory storage element coupled to the processor;

encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the system to:

extract a teeth arch from a volumetric image;

unfold the extracted teeth arch into a panoramic ribbon;

assign higher weights to at least a point in the panoramic ribbon, wherein higher weights are assigned for points inside or proximal to an EoI; and

applying a weighted summation in a direction perpendicular to the teeth arch, resulting in the panorama with the EoI visually emphasized for an accurate diagnostic-treatment approach.

16. The system of 15 , wherein the EoI is pre-defined by an end-user, wherein a plurality of EoI's are ranked in terms of weight by the end-user.

17. The system of claim 15 , further comprising an instance segmentation module to generate a two-dimensional segmentation mask from a generated panorama to impose on the three-dimensional panoramic ribbon to retrieve inferred three-dimensional bounding box from the two-dimensional panoramic instance.

18. The system of claim 17 , further comprising submitting the three-dimensional bonding box to a three-dimensional segmentation module for generating a three-dimensional segmentation mask for segmentation and numbering in original three-dimensional CBCT fine scale.

19. The system of claim 15 , further comprising selecting a two-dimensional instance for each or either a three-dimensional UNet or three-dimensional Region Based Convolutional Neural Network (R-CNN) and selecting a best three-dimensional projection for every two-dimensional instance on the panoramic image.

20. A system for constructing an Elements of Interest (EoI)-focused panorama for an accurate diagnostic-treatment approach, said system comprising:

an instance segmentation module;

a processor;

a non-transitory storage element coupled to the processor;

encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the system to:

extract a teeth arch from a volumetric image;

form a study image from the extracted teeth arch;

unfold the study image into a panoramic ribbon;

tilt the panoramic ribbon for maximal frontal teeth exposure;

assign higher weight to at least a point in the panoramic ribbon, wherein the point is weighted higher for points inside or proximal to an EoI resulting in the panorama with the EoI emphasized; and

apply the instance segmentation module to accurately provide a segmentation mask and numbering with the EoI visually emphasized for an accurate diagnostic-treatment approach.

21. The system of claim 20 , wherein the instance segmentation module is a 3D-R-CNN instance segmentation module.

22. The system of claim 20 , wherein the segmentation is for at least one of a tooth, teeth, mandible, mandibular canal, root, root canal, pulp chamber for each tooth, maxilla, or sinuses.