BM-BronchoLC

This work presents our procedure to build a rich bronchoscopy dataset named BM-BronchoLC from 106 lung cancer and 102 non-lung cancer patients. The dataset contains annotations for anatomical landmarks and lesions, which are conducted by senior doctors of the Bach Mai hospital, Vietnam. To validate the dataset quality, we investigate two typical AI backbone models for the image segmentation and classification task, i.e., Unet++ and ESFPNet, using both unitask and multitask settings. Preliminary results show the significant potential of the data in building AI models or real-time diagnostic accuracy. Further research will validate these promising developments and explore broader clinical applications in this evolving field.