Gland Ring Morphometry for Prostate Cancer Prognosis in Multispectral Immunofluorescence Images

  • Richard Scott
  • Faisal M. Khan
  • Jack Zeineh
  • Michael Donovan
  • Gerardo Fernandez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)


Morphometric features characterizing the fusion and fragmentation of the glandular architecture of advanced prostate cancer have not previously been based upon the automated segmentation of discrete gland rings, due in part to the difficulty of extracting these structures from the H&E stained tissues. We present a novel approach for segmenting gland rings in multi-spectral immunofluorescence (IF) images and demonstrate the utility of the resultant features in predicting cancer recurrence in a cohort of 1956 images of prostate biopsies and prostatectomies from 679 patients. The proposed approach is evaluated for prediction of actual clinical outcomes of interest to physicians in comparison with previously published gland-unit features, yielding a concordance index (CI) of 0.67. This compares favorably to the CI of 0.66 obtained using a semi-automated segmentation of the corresponding H&E images from the same patients. This work presents the first algorithms for segmentation of gland rings lacking a central lumen, and for separation of touching epithelial units, and introduces new gland adjacency features for predicting prostate cancer clinical progression across both biopsy and prostatectomy images.


Gleason prostate segmentation watershed Voronoi gland 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Richard Scott
    • 1
  • Faisal M. Khan
    • 1
  • Jack Zeineh
    • 1
  • Michael Donovan
    • 1
  • Gerardo Fernandez
    • 1
  1. 1.Icahn School of Medicine at Mount SinaiNew YorkUSA

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