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A region growing method for tumor volume segmentation on PET images for rectal and anal cancer patients
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Image of FIG. 1.
FIG. 1.

PET image of the Jaszczak deluxe flangeless ECT phantom showing the filled cylinders used for the determination.

Image of FIG. 2.
FIG. 2.

Flow diagram showing the steps required for the implementation of the CCRG algorithm.

Image of FIG. 3.
FIG. 3.

PET image for patient G. Uptake in the bladder affects the ability to segment the tumor volume on the image using the CCRG method. There were no clear minima between the bladder and tumor.

Image of FIG. 4.
FIG. 4.

PET image data from patient H. (a) A sagittal PET slice. (b) The PET slice magnified to identify the tumor region used to pick the seed pixel. (c) Segmented region from the CCRG technique. (d) PET image showing the (Tumor) and the bladder contours.

Image of FIG. 5.
FIG. 5.

The contoured target volume from the three segmented methods (, , CCRG) and the volume for all the patients. The patients are arranged according to the segmented volumes from the minimum value to the maximum value.

Image of FIG. 6.
FIG. 6.

The mean, minimum, and maximum SUV values in the three segmentation methods compared with the for all patients, arranged from the minimum mean SUV value to the maximum mean SUV value.

Image of FIG. 7.
FIG. 7.

Patient 9 outlined regions on a FDG-PET-CT sagittal slice (a) and axial slice (b) when contoured with (white) and without (black) the use of the CT image.


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Data describing the tumor site, histology, stage, and treatment course for the rectal and anal cancer patients used in this study.

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Segmented volume in cc for the three contouring methods and the volume for all the patients along with the absolute segmented volume difference compared to the volume for each patient.

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The absolute percentage mean difference, standard deviation, and range for the three segmentation methods used compared to the for all patients.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: A region growing method for tumor volume segmentation on PET images for rectal and anal cancer patients