When dealing with medical imaging, collecting and annotating data can be cumbersome and expensive. This is mainly related to the nature of data, often three-dimensional, and to the need for well-trained expert technicians. In maxillofacial imagery, recent works have been focused on the detection of the Inferior Alveolar Nerve (IAN), since its position is of great relevance for avoiding severe injuries during surgery operations such as third molar extraction or implant installation. In this work, we introduce a novel tool for analyzing and labeling the alveolar nerve from Cone Beam Computed Tomography (CBCT) 3D volumes. For a more detailed description of the tool, the full manuscript is available here
In the table below we reported some useful information about our tool.
|Supported operating systems||Windows|
|Output 1||Png images of all the slices (data and binary annotation mask)|
|Output 2||Numpy volumes (data and binary annotation volume)|
|Output 3||3D Coordinates using during the annotation (useful for refining the labels)|
|Additional features||load 2D annotations from DICOM files. manual annotation of the spline is still available.|
You can download the latest windows installer from the button below, or you can built your own version from the github repository.
If you use our tool, please cite our work in your manuscript.