Beyond pixel: Superpixel-based MRI segmentation through traditional machine learning and graph convolutional network.
Zakia KhatunHalldór JónssonMariella TsirilakiNicola MaffulliFrancesco OlivaPauline DavalFrancesco TortorellaPaolo GargiuloPublished in: Computer methods and programs in biomedicine (2024)
Our proposed pipeline demonstrates the efficacy of employing superpixel generation as a coarse segmentation technique for the final tendon segmentation. Whether utilizing RF, SVM-based superpixel classification, or GCN-based classification for tendon segmentation, our system consistently achieves commendable AUC scores, especially the non-graph-based approach. Given the limited dataset, our graph-based method did not perform as well as non-graph-based superpixel classifications; however, the results obtained provide valuable insights into how well the models can distinguish between tendons and non-tendons. This opens up opportunities for further exploration and improvement.