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OVERCOMING PARTIAL VOLUME EFFECTS IN MR TISSUE ANALYSIS

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Simple intensity histogram analyses of brain tissue ... Conspicuous MS lesions/lesion interiors have high intensity in both PD and T2 images. ... – PowerPoint PPT presentation

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Title: OVERCOMING PARTIAL VOLUME EFFECTS IN MR TISSUE ANALYSIS


1
OVERCOMING PARTIAL VOLUME EFFECTS IN MR TISSUE
ANALYSIS
  • M.S. Atkins and Z. Tauber
  • School of Computing Science, Simon Fraser
    University, Burnaby, B.C., Canada

2
Introduction
  • Simple intensity histogram analyses of brain
    tissue
  • in dual-echo PD and T2-weighted MR brain images
  • often fail because of partial volume effects.
  • We overcome these effects for multiple
    sclerosis
  • (MS) lesions in MR images with thick (5mm) slices
  • in order to automatically identify them, noting
    that
  • Conspicuous MS lesions have high intensities in
    both PD and T2 images 1.
  • Lesion borders having partial volume effects are
    darker in both spectra.

3
Intensity Histograms
PD Histogram
T2 Histogram
4
Method Stage 1 Preprocessing
  • Initially we enhance the contrast of the brain
  • tissues in all the MR head images by
  • performing the following operations
  • Correct for RF-Inhomogeneity using Sleds method
    2.
  • Isolate the brain tissue from the head skull
    using Atkins method 3.
  • Scale the brain pixels to the range of 0-255.

5
PD-T2 signal analysis
  • We present a typical slice of the brain MRI
  • PD Image (slice 17) T2 Image (slice 17)
    PD/T2 Scatter Plot
  • The scatter plot shown here represents all the
  • tissues in the brain slice.

6
PD-T2 lesion signal analysis
  • Manual segmentation of the MS lesions in the
  • MR images has a characteristic PD-T2 plot
  • PD Lesions (slice 17) T2 Lesions (slice 17)
    PD/T2 Scatter Plot
  • Hence, we assume that lesion pixels form a wide
    line in PD-T2 feature space.

7
PD-T2 Scatter Plot Analysis
  • Conspicuous MS lesions/lesion interiors have high
    intensity in both PD and T2 images.
  • Subtle MS lesions/lesion boundaries have average
    intensity in both PD and T2 images.
  • All lesion intensities however, in a single
    slice, lie on a line of specific width in the
    PD-T2 feature space.
  • The subtle parts of the MS lesion pixels have the
    same intensity in both PD and T2 images as some
    of the other brain tissues (mostly gray matter).
  • The conspicuous MS lesion pixels are the only
    pixels that have high intensity in both PD and T2
    images.

8
Conspicuous MS lesions
  • To obtain only the conspicuous MS lesion pixels,
    a fairly simple intensity thresholding is applied
    to both PD and T2 images.
  • Only points that pass the threshold in both PD
    and T2 images are considered conspicuous.

PD image after threshold
PD-T2 scatter plot after threshold
9
Hough Transform for Line Normal Parameterization
y
  • ? xi cos ? yi sin ?
  • 0 ? 2? , -N ? N
  • ? r (xi / r cos ? yi / r sin ?)
  • r cos (? - ?)
  • Hough Transform
  • - Create an accumulation array for the ?-?
    parameter space.
  • - Every pixel in the image adds 1 to the
    accumulator array cells under the
    parameterization curve.

d
(xi,yi)
?
r
?
F
0
x
?
?
10
Line Detection
  • Given the PD-T2 scatter plot of only the
    conspicuous pixels, a Hough transform for line
    detection (using normal parameterization) is
    applied to the scatter plot image.
  • The peak point in the Hough transform space is
    selected using a
    Gaussian filter.
  • The peak point corresponds to the
    detected line parameters.

Hough Transform
11
Line Detection (Continued)
  • The Hough transform image represents many 1-pixel
    thin lines in many directions and positions
    constrained by the wide line that covers all the
    lesion pixels in PD-T2 space.
  • The peak point in the Hough transform space
    represents the parameters of the average thin
    line inside the wide line, which is also the
    center line of the wide line.
  • The thickness of the wide line is determined by
    summing the pixels along the peak line gradient
    (i.e. the same x coordinate) in Hough transform
    space until the sum equals nearly 100 of the
    number of pixels in the PD-T2 scatter plot of the
    conspicuous lesions.

12
Line Mask
  • A line mask is automatically generated based on
    the allocated peak parameters.
  • Only points with intensities in both PD and T2
    images that are covered by the line mask are
    allowed to be tested for being subtle lesions.
  • Line Mask Image Allowable PD-T2 points
    Subtle tissues under mask

13
Conspicuous Lesions Postprocessing
  • Thresholding doesnt eliminate all
    non-conspicuous pixels. However, typically most
    other pixels are isolated in the thresholded
    images.
  • Very small pixel blobs are therefore eliminated
    from the conspicuous lesions images.
  • Note The Hough transform is robust with respect
    to the extra non-conspicuous pixels.

14
Subtle Points Detection Criteria
  • The following criteria are defined for the
  • allowable pixels to be considered subtle lesions
  • Shorter pixel distance to a conspicuous pixel is
    a better indication that its a subtle pixel.
  • Larger number of conspicuous pixels in the
    neighborhood indicates higher likelihood of being
    a subtle pixel.
  • Higher intensity of a conspicuous pixel in both
    PD and T2 images in the neighborhood indicates a
    subtle pixel.

15
Subtle Points Detection
  • Applying a Gaussian smoothing filter with a
    cutoff of about 4 pixels to the conspicuous
    lesions images produces an image with subtle
    lesion pixel values appropriate to the criteria
    required.
  • The resulting image is then further
    processed to remove all points that dont
    have the PD-T2 intensities allowable
    to represent a subtle lesion.

Possible Subtle Lesions
16
Lesion Detection
  • The conspicuous lesions image is combined
    together with the subtle lesions image.
  • The Radiologist can interactively threshold the
    result image to the required probability of the
    detected subtle lesion being a real MS
    lesion, and thereby obtain an image of
    only the lesions.
  • Alternatively the threshold can be
    automatic.

Thresholded lesion pixels
17
Conclusions
  • For brain MRI where we can assume the lesion
    pixels intensities lie under a line in PD-T2
    space, an automated thresholding method along
    with a Hough transform can be applied in order to
    automatically detect MS lesions and overcome the
    partial volume effect of the subtle lesions
    adjacent to conspicuous lesions.
  • Spatial information can then be used to refine
    the tissue segmentation further, as in 4.

18
Future Work
  • Investigate the sensitivity of our method to the
    assumption that there is low variability in
    lesion tissue material.
  • Discover the exact reason why it is not always
    the case that the MS lesions pixels PD-T2
    intensities lie under a line.
  • References
  • 1 M.S. Atkins et al. ISMRM 97, 649.
  • 2 J. Sled et al. IEEE Transaction on Medical
    Imaging, 17(1), 87-97, 1998.
  • 3 M.S. Atkins and B. Mackiewich, IEEE
    Transaction on Medical Imaging, 17(1), 98-107,
    1998.
  • 4 K.Krishnan and M.S. Atkins, Proceedings in
    SPIE 98, 33381106-1116.
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