Cervical optical coherence tomography image classification based on contrastive self-supervised texture learning.
Journal:
Medical physics
Published Date:
Jun 1, 2022
Abstract
BACKGROUND: Cervical cancer (CC) seriously affects the health of the female reproductive system. Optical coherence tomography (OCT) emerged as a noninvasive, high-resolution imaging technology for cervical disease detection. However, OCT image annotation is knowledge-intensive and time-consuming, which impedes the training process of deep-learning-based classification models.