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Head and neck lymph node region delineation with image registration.

Teng CC, Shapiro LG, Kalet IJ - Biomed Eng Online (2010)

Bottom Line: We are also proposing a method that could help us identify the reference models which could potentially produce the best results.The computer generated lymph node regions are evaluated quantitatively and qualitatively.Although not conforming to clinical criteria, the results suggest the technique has promise.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Technology, Brigham Young University, Provo, UT, USA. ccteng@byu.edu

ABSTRACT

Background: The success of radiation therapy depends critically on accurately delineating the target volume, which is the region of known or suspected disease in a patient. Methods that can compute a contour set defining a target volume on a set of patient images will contribute greatly to the success of radiation therapy and dramatically reduce the workload of radiation oncologists, who currently draw the target by hand on the images using simple computer drawing tools. The most challenging part of this process is to estimate where there is microscopic spread of disease.

Methods: Given a set of reference CT images with "gold standard" lymph node regions drawn by the experts, we are proposing an image registration based method that could automatically contour the cervical lymph code levels for patients receiving radiation therapy. We are also proposing a method that could help us identify the reference models which could potentially produce the best results.

Results: The computer generated lymph node regions are evaluated quantitatively and qualitatively.

Conclusions: Although not conforming to clinical criteria, the results suggest the technique has promise.

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Sample result of lymph node region projection: (a) level IA, (b)(c) level IB, (d)(e) level II, (f)(g) level III, and (h)(i) level V. Each color region corresponds to a lymph node region.
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Figure 7: Sample result of lymph node region projection: (a) level IA, (b)(c) level IB, (d)(e) level II, (f)(g) level III, and (h)(i) level V. Each color region corresponds to a lymph node region.

Mentions: Figure 7 shows an example of the projected lymph node region contour based on the result of the image registration. The projected 3D lymph node regions are shown at the lower left 3D view. They are also overlaid on the target CT images in axial, sagittal, and coronal views. The radiation oncologists can make adjustments to the suggested contours as needed.


Head and neck lymph node region delineation with image registration.

Teng CC, Shapiro LG, Kalet IJ - Biomed Eng Online (2010)

Sample result of lymph node region projection: (a) level IA, (b)(c) level IB, (d)(e) level II, (f)(g) level III, and (h)(i) level V. Each color region corresponds to a lymph node region.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2902481&req=5

Figure 7: Sample result of lymph node region projection: (a) level IA, (b)(c) level IB, (d)(e) level II, (f)(g) level III, and (h)(i) level V. Each color region corresponds to a lymph node region.
Mentions: Figure 7 shows an example of the projected lymph node region contour based on the result of the image registration. The projected 3D lymph node regions are shown at the lower left 3D view. They are also overlaid on the target CT images in axial, sagittal, and coronal views. The radiation oncologists can make adjustments to the suggested contours as needed.

Bottom Line: We are also proposing a method that could help us identify the reference models which could potentially produce the best results.The computer generated lymph node regions are evaluated quantitatively and qualitatively.Although not conforming to clinical criteria, the results suggest the technique has promise.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Technology, Brigham Young University, Provo, UT, USA. ccteng@byu.edu

ABSTRACT

Background: The success of radiation therapy depends critically on accurately delineating the target volume, which is the region of known or suspected disease in a patient. Methods that can compute a contour set defining a target volume on a set of patient images will contribute greatly to the success of radiation therapy and dramatically reduce the workload of radiation oncologists, who currently draw the target by hand on the images using simple computer drawing tools. The most challenging part of this process is to estimate where there is microscopic spread of disease.

Methods: Given a set of reference CT images with "gold standard" lymph node regions drawn by the experts, we are proposing an image registration based method that could automatically contour the cervical lymph code levels for patients receiving radiation therapy. We are also proposing a method that could help us identify the reference models which could potentially produce the best results.

Results: The computer generated lymph node regions are evaluated quantitatively and qualitatively.

Conclusions: Although not conforming to clinical criteria, the results suggest the technique has promise.

Show MeSH