The goal of the project is to determine whether the 3rd Molar and the mandibular canal are in contact with each other in CT images.
Data Class: 0(Not exist), 1(No contact), 2(Simple contact), 3(More involve)

Initially, vanila classification, which receives images as input, achieved an accuracy of less than 50%, and the DL classification learning pipeline was subdivided into three stages to increase accuracy;

Learning PIPELINE:

• stage1: the 3rd Molar Binary classification
  • 0 or 1,2,3
  • Check for the 3rd Molar and create an attention feature map to be used as input in stage3.
• stage2: Canal Line detection & inpainting
• stage3: Multi-output classification
  • 1 or 2 or 3ß

[Figure] stage1:

stage2:
stage1 output: attention feature map