{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "@id": "https://anchorfact.org/kb/image-segmentation",
  "headline": "Image Segmentation: From U-Net to SAM",
  "description": "Image segmentation partitions images into meaningful regions — semantic (class per pixel), instance (object per pixel), or panoptic (both). U-Net dominates medical imaging; SAM enables general-purpose interactive segmentation.",
  "dateCreated": "2026-05-24T02:49:13.618Z",
  "dateModified": "2026-05-24",
  "author": {
    "@type": "Organization",
    "name": "AnchorFact"
  },
  "publisher": {
    "@type": "Organization",
    "name": "AnchorFact",
    "url": "https://anchorfact.org"
  },
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "anchorfact:confidence": "high",
  "anchorfact:generationMethod": "ai_assisted",
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "U-Net: Convolutional Networks for Biomedical Image Segmentation",
      "sameAs": "https://arxiv.org/abs/1505.04597"
    },
    {
      "@type": "CreativeWork",
      "name": "Segment Anything (SAM)",
      "sameAs": "https://arxiv.org/abs/2304.02643"
    }
  ]
}