Enhancing AI Diagnostics: Autonomous Lesion Masking via Semi-Supervised Deep Learning

arXiv:2404.12450v1 Announce Type: cross
Abstract: This study presents an unsupervised domain adaptation method aimed at autonomously generating image masks outlining regions of interest (ROIs) for differentiating breast lesions in breast ultrasound (US) imaging. Our semi-supervised learning approach utilizes a primitive model trained on a small public breast US dataset with true annotations. This model is then iteratively refined for the domain adaptation task, generating pseudo-masks for our private, unannotated breast US dataset. The dataset, twice the size of the public …

abstract arxiv autonomous cs.ai cs.cv cs.lg dataset deep learning diagnostics domain domain adaptation image imaging masking masks public semi-supervised semi-supervised learning small study supervised learning type unsupervised via