SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images

Understand

Radiological images such as computed tomography (CT) and X-rays render anatomy with intrinsic structures.

• Being able to reliably locate the same anatomical structure across varying images is a fundamental task in medical image analysis.
• In principle it is possible to use landmark detection or semantic segmentation for this task, but to work well these require large numbers of labeled data for each anatomical structure and sub-structure of interest.
• A more universal approach would learn the intrinsic structure from unlabeled images.