{
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  "Title": "White Matter Normalization for Magnetic Resonance Images",
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  "Authors@R": "c(\nperson(given = \"R. Taki\",\nfamily = \"Shinohara\",\nemail = \"russell.shinohara@pennmedicine.upenn.edu\",\nrole = c(\"aut\")),\nperson(given = \"John\",\nfamily = \"Muschelli\",\nemail = \"muschellij2@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-6469-1750\"))\n)",
  "Description": "Shinohara (2014) <doi:10.1016/j.nicl.2014.08.008>\nintroduced 'WhiteStripe', an intensity-based normalization of\nT1 and T2 images, where normal appearing white matter performs\nwell, but requires segmentation. This method performs white\nmatter mean and standard deviation estimates on data that has\nbeen rigidly-registered to the 'MNI' template and uses\nhistogram-based methods.",
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  "Date/Publication": "2025-07-23 14:18:32 UTC",
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    "whitestripe_norm",
    "ws_img_data"
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      "title": "Smoothed histogram of image",
      "object": "smoothed_histogram",
      "class": [
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      "class": [
        "histogram"
      ],
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      "title": "Histogram of VOI of T2 template image",
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      "tojson": false
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      ],
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      "table": false,
      "tojson": true
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    {
      "page": "download_img_data",
      "title": "Download T1 and T2 data",
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      "page": "get.deriv.smooth.hist",
      "title": "Gets nth derivative of smoothed histogram",
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    },
    {
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      "title": "Get First Peak",
      "topics": [
        "get.first.mode"
      ]
    },
    {
      "page": "get.largest.mode",
      "title": "Grab largest peak",
      "topics": [
        "get.largest.mode"
      ]
    },
    {
      "page": "get.last.mode",
      "title": "Get Last Peak",
      "topics": [
        "get.last.mode"
      ]
    },
    {
      "page": "make_img_voi",
      "title": "Make Image VOI",
      "topics": [
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      ]
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      "title": "Smoothed histogram of image",
      "topics": [
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    },
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      "title": "Histogram smoothing for whitestripe",
      "topics": [
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