Segmentation of 3D Medical Objects by Deformable M-reps

 [Last update: by tracton@radonc.unc.edu]

© Copyright UNC, 2000

Papers

The concepts and methods for this segmentation technique are described in the paper

Pizer SM, Fletcher PT, Fridman Y, Fritsch DS, Gash AG, Glotzer JM, Joshi S, Thall A, Tracton G, Yushkevich P, Chaney EL, (2000). Deformable M-Reps for 3D Medical Image Segmentation. Submitted for publication to MedIA. [Adobe Acrobat Reader PDF format]

Further geometric and proabilistic theory on m-reps can be found in

Pizer SM, Fritsch DS, Yushkevich P, Johnson V, Chaney EL (1999). Segmentation, Registration, and Measurement of Shape Variation via Image Object Shape. IEEE Transactions on Medical Imaging, 18 (10): 851-865.  [Adobe Acrobat Reader PDF format]

Additional Results

These are results beyond those which can be found in the first paper.

Most movies are under construction. Our goal is to finish converting results to AVI movies by 3-Nov-2000 and to Realplayer movies shortly after.

About movie players for AVI and RealPlayer .

Kidney Results

We are displaying results on kidney images from 6 patients, named kidney 0 through kidney 5. The model was built on kidney 0 and used to segment the other five.

  1. Movie of the model deformation (segmentation) sequence to extract a kidney from a 3D CT data set:

    The kidney model, a single figure modeling the kidney parenchyma plus the renal pelvis:
  2. Movies of image slices vs. segmented kidneys for results which segmented successfully fully automatically after hand placement of model.

    Stage of Progress

    Kidney 2

    Kidney 3

    Kidney 4

    During hand placement,
    user has full control

    RP()
    RP()
    AVI()
    AVI()
    After hand placement

    RP()
    RP()
    AVI()
    AVI()

    After all m-rep stages:
    similarity transform,
    atom deformation

    RP()
    RP()
    AVI()
    AVI()

    After the boundary displacement,
    i.e., at the end of the segmentation

     

  3. Movies of image slices vs. segmented kidneys for results which converged incompletely under automatic operation after hand placement of model

    Stage of Progress

    Kidney 1

    Kidney 5

    After hand placement

    After all m-rep stages:
    similarity transform,
    boundary displacement

    After repeating automatic segmentation
    with the previous automatic result as the model
            

Cerebral Ventricle Results

TBD

Forming a model

TBD