Semi-automated Segmentation of a Glioblastoma Multiforme on Brain MR Images for Radiotherapy Planning

DOI Web Site PubMed 4 Citations 29 References

Bibliographic Information

Other Title
  • 放射線治療計画のための頭部ＭＲ画像における膠芽腫の半自動抽出
  • ホウシャセン チリョウ ケイカク ノ タメ ノ トウブ MR ガゾウ ニ オケル コウガ シュ ノ ハンジドウ チュウシュツ

Search this article

Description

We propose a computerized method for semi-automated segmentation of the gross tumor volume (GTV) of a glioblastoma multiforme (GBM) on brain MR images for radiotherapy planning (RTP). Three-dimensional (3D) MR images of 28 cases with a GBM were used in this study. First, a sphere volume of interest (VOI) including the GBM was selected by clicking a part of the GBM region in the 3D image. Then, the sphere VOI was transformed to a two-dimensional (2D) image by use of a spiral-scanning technique. We employed active contour models (ACM) to delineate an optimal outline of the GBM in the transformed 2D image. After inverse transform of the optimal outline to the 3D space, a morphological filter was applied to smooth the shape of the 3D segmented region. For evaluation of our computerized method, we compared the computer output with manually segmented regions, which were obtained by a therapeutic radiologist using a manual tracking method. In evaluating our segmentation method, we employed the Jaccard similarity coefficient (JSC) and the true segmentation coefficient (TSC) in volumes between the computer output and the manually segmented region. The mean and standard deviation of JSC and TSC were 74.2±9.8% and 84.1±7.1%, respectively. Our segmentation method provided a relatively accurate outline for GBM and would be useful for radiotherapy planning.

Journal

Citations (4)*help

See more

References(29)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top