Whole Slide Imaging in DICOM - PowerPoint PPT Presentation

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Whole Slide Imaging in DICOM

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Title: Whole Slide Imaging in DICOM


1
Whole Slide Imaging in DICOM
  • Harry Solomon
  • GE Healthcare

2
WSI Supplements
  • Two DICOM Supplements developed by WG-26
    Anatomic Pathology
  • Supplement 145 Whole Slide Imaging
  • Adopted August 2010
  • Supplement 122 Specimen Module
  • Adopted June 2008

3
The Whole Slide Problem
  • Need image resolution comparable to optical
    microscope
  • Need image access as rapid as microscope (pan,
    zoom, focus)

Yukako Yagi UPMC
4
Digital slides are huge
  • Sample size 20mm x 15mm
  • Resolution of .25 µm/pixel (40X objective)
  • 80,000 x 60,000 pixels 4.8 Gp
  • 24-bit color 14.4 GB / slide
  • 401 compression only 360 MB / typical slide
  • Unless
  • Larger specimen
  • Higher resolution (100X objective)
  • Multiple focal planes
  • Multi-spectral imaging (16-bit / band)
  • And
  • A typical study may be 10 slides

5
Sup 145 Tiling and Multi-frame encoding
  • Whole Slide Image divided into tiles
  • Each tile encoded into a frame of multi-frame
    image object
  • Per-frame header givesspatial location for each
    tile X, Y, and Z (focal plane)

Multiple focal planes
Multi-frame image object
6
Z-planes (focal planes)
  • Z-planes are identified as nominal physical
    height of image focal plane above reference
    surface (µm)
  • Z-plane information is used for relative spatial
    positioning of image planes, and nominal
    inter-plane distance
  • An image plane may track variable specimen
    thickness / surface contour, but only one Z-value
    used

? Z
Cover slip
? Z
Specimen
Slide substrate (glass)
7
Z planes may track curved surface
  • Z plane 1
  • Z plane 2
  • Z plane 3
  • Z plane 4

Tile 1
Tile 2
Tile 3
Tile 4
Tile 5
Tile 6
Tile 7
Tile 8
Viktor Sebestyén Varga 3DHISTECH Ltd.
8
Total Pixel Matrix
Total Pixel Matrix Origin
  • Total pixel matrix origin at top left hand corner
    of imaged volume
  • Frame (tile) rows and columns align with total
    pixel matrix rows and columns
  • Frames limited to 216 columns and rows each
  • Total pixel matrix limited to 232 columns and
    rows

Columns ?
Rows
?
Frame Pixel Matrix Origin
Total pixel matrix coordinates used for frame
location and for annotation
9
Sparse tiling
  • Slides may have substantial area with no specimen
  • Empty tiles may be absent from multi-frame image

10
Access Navigation and Zoom
  • Need to rapidly access
  • High resolution image of small areas
  • Facilitated by tilling
  • Low resolution image of whole slide
  • For overview and navigation
  • Intermediate resolutions
  • Smooth zooming
  • Lower resolution images may bepre-computed
  • Hierarchical pyramid
  • May add 33 to size of data

11
Tiling and multi-frame at all hierarchical levels
Single frame image
Thumbnail Image
Multi-frame image (single object)
Intermediate Image
Multi-frame image (single object)may include
multipleZ-planes, color planes
Baseline Image
All image objects typically in 1 DICOM Series
12
Localizer image flavor
  • Thumbnail image (single frame) plus navigation
    links to each frame at each resolution
  • Each tile of other resolution images has its
    corresponding area identified in thumbnail
  • Full description of target tiles
  • Object Unique ID and frame number
  • Resolution
  • Z-plane, color
  • Multiple target frames can overlap
  • Different resolution, Z-plane, color, etc.
  • Presentation and any interactive behavior is not
    defined in standard

13
Optical paths
Illumination Method
Illumination
Filters
Lens
Lens
Filters
Sensor
  • Each combination of light source, lenses,
    illumination method, detected wavelengths, etc.
    used in a scan is an optical path
  • Three primary mandatory attributes
  • Illumination color or wavelength
  • Illumination method (e.g., transmission,
    epifluorescence , darkfield, differential
    interference contrast)
  • Detection color
  • Additional optional attributes for lenses,
    filters, prisms, etc.
  • Examples
  • Full spectrum light, transmission, RGB color
    sensors
  • UV excitation, epifluorescence, 535 nm emission
    filter, monochrome sensor

14
Multi-spectral imaging
  • Typical color image stored with RGB or YBR
    photometric interpretation
  • 3 color values / pixel
  • Multi-spectral image stored with MONOCHROME
    photometric interpretation
  • 1 color value / pixel / color plane
  • Multiple color planes may be stored in single
    image object
  • Each frame references its optical path in
    per-frame header

3 x 8-bit RGB
n x 16-bit multi-spectral
15
Standard DICOM mechanisms for annotation of WSI
  • Color Presentation State
  • Displayed Area Selection relative to WSI total
    matrix
  • Graphic and text annotation with sub-pixel
    location resolution, even with 8M columns or rows
  • Segmentation
  • Can be created pixel-by-pixel against selected
    frames of original image
  • 1-bit/source-pixel, or 8-bits/source-pixel
  • Display of segmentation implicitly invokes
    blending with source image
  • Structured Reporting
  • Captures measurements, clinical observations,
    analyses, and findings
  • Real World Value Mapping
  • Specifies a mapping of the stored pixel values of
    images into some real world value in defined
    units
  • Allows quantitative methods with monochrome
    images (original or derived)

16
Anatomic Pathology Imaging Workflow
Slide preparation
Workstation
Gross specimen accessioning
Whole Slide Scanner
Surgical or biopsy procedure
17
Sup 122 Specimen Module
  • Support for pathology lab workflow,
    specimen-based imaging
  • Gross specimens, blocks, vials, slides
  • Image-guided biopsy samples
  • Specimen Module at image level of hierarchy
  • Identification, processing history (especially
    stains applied)
  • Modality Worklist can convey Specimen Module
  • Enables automated slide scanning devices to fully
    populate image header
  • Processing history can be used to set up
    acquisition (based on stain)
  • Modality Performed Procedure Step identifies
    imaged specimen
  • Allows LIS/APLIS to track images for specimens

18
Specimen Imaging Information Model
Disambiguates specimen and container Container is
target of image Container may have more than one
specimen Specimens have a physical derivation
(preparation) from parent specimens When more
than one specimen in an imaged container, each
specimen is distinguished (e.g., by position or
color-coding)
Basic DICOM Information Model
19
Enabling Transformation to Digital Pathology
  • Supplements 145 and 122 establish the foundation
    for a true market for digital imaging in anatomic
    pathology
  • Comparable in importance to the introduction of
    DICOM to radiology in 1993
  • Enables quantitation and collaboration
  • In the next 5-10 years, we should expect a
    profound transformation of pathology from a
    highly manual process to a digital workflow
  • The use of the DICOM Standard across radiology,
    pathology, surgery, and radiation therapy opens
    the door to truly integrated data from screening
    to biopsy to diagnosis to treatment
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