DICOMwebToolComparison.ipynb

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      "name": "python3",
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/dclunie/ProjectWeek/blob/master/DICOMwebToolComparison.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# DICOMweb for pathology"
      ],
      "metadata": {
        "id": "7Q88iRPZ1w68"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0HRPQ1dq1tFK"
      },
      "outputs": [],
      "source": [
        "!pip install dicomweb-client[gcp]\n",
        "!pip install wsidicom\n",
        "!pip install dicomslide"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Authentification via Google Colab\n",
        "from google.colab import auth\n",
        "auth.authenticate_user()"
      ],
      "metadata": {
        "id": "PZCROkHo1oGL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## dicomweb_client\n",
        "- implements QIDO-RS, WADO-RS and STOW-RS endpoints as defined by the DICOMweb standard: see [conformance statement](https://dicomweb-client.readthedocs.io/en/latest/conformance.html)\n",
        "- provides a DICOMwebClient and a DICOMfileClient"
      ],
      "metadata": {
        "id": "XeARRx9H1Nw0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from dicomweb_client.api import DICOMwebClient\n",
        "from dicomweb_client.ext.gcp.session_utils import create_session_from_gcp_credentials\n",
        "from dicomweb_client.ext.gcp.uri import GoogleCloudHealthcareURL"
      ],
      "metadata": {
        "id": "toNENfbP0DhR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "session = create_session_from_gcp_credentials()\n",
        "\n",
        "dicom_server_url = GoogleCloudHealthcareURL(\n",
        "    project_id='idc-external-031',\n",
        "    location='us-central1',\n",
        "    dataset_id='projectweek40',\n",
        "    dicom_store_id='projectweek40-store'\n",
        ")\n",
        "\n",
        "dw_client = DICOMwebClient(\n",
        "    url=str(dicom_server_url),\n",
        "    session=session\n",
        ")"
      ],
      "metadata": {
        "id": "mK3SwFix0GHl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Example use to search for studies:\n",
        "all_studies = dw_client.search_for_series()\n",
        "print(all_studies)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VOGezAGb09QP",
        "outputId": "12c3907c-3ff4-49f6-f6a7-3c043f9dcfd7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[{'00080020': {'vr': 'DA', 'Value': ['20100520']}, '00080030': {'vr': 'TM', 'Value': ['145936']}, '00080050': {'vr': 'SH', 'Value': ['TCGA-05-4244']}, '00080060': {'vr': 'CS', 'Value': ['SM']}, '00080090': {'vr': 'PN', 'Value': [{'Alphabetic': '^^^^'}]}, '00080201': {'vr': 'SH', 'Value': ['+0000']}, '0008103E': {'vr': 'LO', 'Value': ['Frozen HE TP BS1']}, '00100010': {'vr': 'PN', 'Value': [{'Alphabetic': 'TCGA-05-4244'}]}, '00100020': {'vr': 'LO', 'Value': ['TCGA-05-4244']}, '00100030': {'vr': 'DA'}, '00100040': {'vr': 'CS'}, '0020000D': {'vr': 'UI', 'Value': ['2.25.317753984268209060558780446660059290395']}, '0020000E': {'vr': 'UI', 'Value': ['1.3.6.1.4.1.5962.99.1.1068263875.756580321.1637450836419.2.0']}, '00200010': {'vr': 'SH', 'Value': ['TCGA-05-4244']}}, {'00080020': {'vr': 'DA', 'Value': ['20220603']}, '00080030': {'vr': 'TM', 'Value': ['002016']}, '00080050': {'vr': 'SH', 'Value': ['TCGA-05-4244']}, '00080060': {'vr': 'CS', 'Value': ['SM']}, '00080090': {'vr': 'PN', 'Value': [{'Alphabetic': '^^^^'}]}, '00080201': {'vr': 'SH', 'Value': ['+0000']}, '0008103E': {'vr': 'LO', 'Value': ['FFPE HE TP DX1']}, '00100010': {'vr': 'PN', 'Value': [{'Alphabetic': 'TCGA-05-4244'}]}, '00100020': {'vr': 'LO', 'Value': ['TCGA-05-4244']}, '00100030': {'vr': 'DA'}, '00100040': {'vr': 'CS'}, '0020000D': {'vr': 'UI', 'Value': ['2.25.317753984268209060558780446660059290395']}, '0020000E': {'vr': 'UI', 'Value': ['1.3.6.1.4.1.5962.99.1.1042652702.25371455.1637425225246.2.0']}, '00200010': {'vr': 'SH', 'Value': ['TCGA-05-4244']}}, {'00080020': {'vr': 'DA', 'Value': ['20180109']}, '00080030': {'vr': 'TM', 'Value': ['061405']}, '00080050': {'vr': 'SH', 'Value': ['01BR042']}, '00080060': {'vr': 'CS', 'Value': ['SM']}, '00080090': {'vr': 'PN', 'Value': [{'Alphabetic': '^^^^'}]}, '00080201': {'vr': 'SH', 'Value': ['+0000']}, '0008103E': {'vr': 'LO', 'Value': ['HE tumor_tissue']}, '00100010': {'vr': 'PN', 'Value': [{'Alphabetic': '01BR042'}]}, '00100020': {'vr': 'LO', 'Value': ['01BR042']}, '00100030': {'vr': 'DA'}, '00100040': {'vr': 'CS', 'Value': ['F']}, '0020000D': {'vr': 'UI', 'Value': ['2.25.337229215004309374109998000508745240467']}, '0020000E': {'vr': 'UI', 'Value': ['1.3.6.1.4.1.5962.99.1.130466504.695540300.1640808006344.2.0']}, '00200010': {'vr': 'SH', 'Value': ['01BR042']}}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##wsidicom\n",
        "- [Documentation](https://pypi.org/project/wsidicom/) and [Code](https://github.com/imi-bigpicture/wsidicom)\n",
        "- wsidicom wraps dicomweb_client's `DICOMwebClient` in the class `WsiDicomWebClient`, so access to all functionality of dicomweb_client is still possible.\n",
        "- An instance of the `WsiDicomWebClient` can be created from scratch providing the DICOM server URL and authentification. Alternatively, a `DICOMwebClient` instance can be used to create a `WsiDicomWebClient`. The entrypoint to all remaining wsidicom functionality is the function [`WsiDicom.open_web()`](https://github.com/imi-bigpicture/wsidicom/blob/bc2edb5b0f01c810b60bae1cd8c236ab1ee446cb/wsidicom/wsidicom.py#L108).\n",
        "- Code for DICOMweb functionality additional to dicomweb_client's `DICOMwebClient` can be found in [wsidicom_web_client.py](https://github.com/imi-bigpicture/wsidicom/blob/f5c5312cc8159f02867233f07350882c5de68d43/wsidicom/web/wsidicom_web_client.py), [wsidicom_web_image_data.py](https://github.com/imi-bigpicture/wsidicom/blob/f5c5312cc8159f02867233f07350882c5de68d43/wsidicom/web/wsidicom_web_image_data.py) and [wsidicom_web_source.py](https://github.com/imi-bigpicture/wsidicom/blob/f5c5312cc8159f02867233f07350882c5de68d43/wsidicom/web/wsidicom_web_source.py).\n",
        "- seems to load pixel data into memory and holds them there.\n"
      ],
      "metadata": {
        "id": "kjRNHDYqscQE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from wsidicom import WsiDicom, WsiDicomWebClient"
      ],
      "metadata": {
        "id": "tLu_qRIn2AOz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Set-up wsidicom client from dw_client\n",
        "wsidicom_client = WsiDicomWebClient(dw_client)"
      ],
      "metadata": {
        "id": "SoGtNMqb2cEM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Entry point to WsiDicom object\n",
        "slide = WsiDicom.open_web(wsidicom_client,\n",
        "                  study_uid='2.25.317753984268209060558780446660059290395',\n",
        "                  series_uids='1.3.6.1.4.1.5962.99.1.1042652702.25371455.1637425225246.2.0'\n",
        "                  )"
      ],
      "metadata": {
        "id": "lC41BFQv4F9q"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "*Snippet from documentation:* **A WSI DICOM pyramid is in wsidicom represented by a hierarchy of objects of different classes**, starting from bottom (Note: apparently similar to openslide):\n",
        "\n",
        "- `WsiDicomReader`, represents a WSI DICOM file reader, used for accessing WsiDicomFileImageData and WsiDataset.\n",
        "- `WsiDicomFileImageData`, represents the image data in one or several (in case of concatenation) WSI DICOM files.\n",
        "- `WsiDataset`, represents the image metadata in one or several (in case of concatenation) WSI DICOM files.\n",
        "- `WsiInstance`, represents image data and image metadata.\n",
        "Level, represents a group of instances with the same image size, i.e. of the same level.\n",
        "- `Pyramid`, represents a group of levels, i.e. the pyrimidal structure.\n",
        "Pyramids, represents a collection of pyramids, each with different image coordate system or extended depth of field.\n",
        "- `WsiDicom`, represents a collection of pyramids, labels and overviews.\n",
        "Labels and overviews are structured similarly to levels, but with somewhat different properties and restrictions. For DICOMWeb the WsiDicomFile* classes are replaced with WsiDicomWeb* classes.\n",
        "\n",
        "A Source is used to create WsiInstances, either from files (`WsiDicomFileSource`) or DICOMWeb (`WsiDicomWebSource`), and can be used to to Initiate a WsiDicom object. A source is easiest created with the `open()` and `open_web()` helper functions."
      ],
      "metadata": {
        "id": "RQOHyqRcFirq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## dicomslide\n",
        "- [Documentation](https://dicomslide.readthedocs.io/en/latest/introduction.html#design), [Code](https://github.com/ImagingDataCommons/dicomslide)\n",
        "- dicomslide directly leverages dicomweb_client to access DICOM WSI from a file system or via DICOMweb.\n",
        "- Entrypoint to remaining functionality is `dicomslide.find_slides()`.\n",
        "- does not load the entire images into memory, but dynamically retrieves only the image frames (tiles) that are needed for a requested image region.\n",
        "- For 2D color images, dicomslide also exposes an OpenSlide interface (`dicomslide.OpenSlide`), which is intended as an API wrapper around a `dicomslide.Slide` instance and to be used as a drop-in replacement for an `openslide.OpenSlide` instance"
      ],
      "metadata": {
        "id": "IugnFvD-zZy8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import dicomslide\n",
        "found_slides = dicomslide.find_slides(dw_client, study_instance_uid='2.25.317753984268209060558780446660059290395')\n",
        "print(found_slides)"
      ],
      "metadata": {
        "id": "x0qfaEhlNJki"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "*Snippet from documentation:* The dicomslide Python package contains several data structures that abstract whole slide images. The core data structure of the library is the **`dicomslide.Slide class`**, which represents a **collection of DICOM VL Whole Slide Microscopy Image instances that share the same Container Identifier and Frame of Reference UID, i.e., that were acquired for the same physical class slide and are spatially aligned**. The interface exposed by the dicomslide.Slide class abstracts the organization of tiled images that belong to the slide (`dicomslide.TiledImage`) and the associated total pixel matrices (`dicomslide.TotalPixelMatrix`), which form a multi-resolution image pyramid (`dicomslide.Pyramid`)."
      ],
      "metadata": {
        "id": "LFSeiMR5F9r4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)\n",
        "\n",
        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)"
      ],
      "metadata": {
        "id": "ykfi96JyEB9I"
      }
    }
  ]
}