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A geometric method for the detection and correction of segmentation leaks of anatomical structures in volumetric medical images

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Patient-specific models of anatomical structures and pathologies generated from volumetric medical images play an increasingly central role in many aspects of patient care. A key task in generating these models is the segmentation of anatomical structures and pathologies of interest. Although numerous segmentation methods are available, they often produce erroneous delineations that require time-consuming modifications.

Methods

   We present a new geometry-based algorithm for the reliable detection and correction of segmentation errors in volumetric medical images. The method is applicable to anatomical structures consisting of a few 3D star-shaped components. First, it detects segmentation errors by casting rays from the initial segmentation interior to its outer surface. It then classifies the segmentation surface into correct and erroneous regions by minimizing an energy functional that incorporates first- and second-order properties of the rays lengths. Finally, it corrects the segmentation errors by computing new locations for the erroneous surface points by Laplace deformation so that the new surface has maximum smoothness with respect to the rays-length gradient magnitude.

Results

   Our evaluation on initial segmentations of 16 abdominal aortic aneurysm and 12 lung tumors in CT scans obtained by both adaptive region-growing and active contours level-set segmentation improved the volumetric overlap error by 66 and 70.5 % respectively, with respect to the ground-truth.

Conclusions

   The advantages of our method are that it is independent of the initial segmentation algorithm that covers a variety of anatomical structures and pathologies, that it does not require a shape prior, and that it requires minimal user interaction.

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Acknowledgments

The authors would like to thank Prof. Jacob Sosna, Chairman of the Department of Radiology at the Hadassah-University Medical Center, Jerusalem, Israel, and his staff for providing the CT scans and ground-truth delineations. This work was partially supported by KAMIN Grant 46217, Israeli Ministry of Trade and Industry.

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Authors and Affiliations

  1. Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Givat Ram Campus, 91904 , Jerusalem, Israel

    Achia Kronman & Leo Joskowicz

Authors
  1. Achia Kronman
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  2. Leo Joskowicz
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Correspondence to Leo Joskowicz.

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None of the authors has any conflict of interest. The authors have no personal financial or institutional interest in any of the materials, software or devices described in this article.

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Kronman, A., Joskowicz, L. A geometric method for the detection and correction of segmentation leaks of anatomical structures in volumetric medical images. Int J CARS 11, 369–380 (2016). https://doi.org/10.1007/s11548-015-1285-z

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  • DOI: https://doi.org/10.1007/s11548-015-1285-z

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