Tumor Segmentation in Intraoperative Fluorescence Images Based on Transfer Learning and Convolutional Neural Networks.

To the best of our knowledge, this study explores tumor segmentation on intraoperative fluorescent images for the first time. The results show that compared to traditional methods, deep learning has significant advantages in improving segmentation performance. Transfer learning enables deep learning models to perform better on small-sample fluorescence image data compared to end-to-end training. This discovery provides strong support for surgeons to obtain more reliable and accurate image segmentation results during surgery.