Segmentation of nodular medulloblastoma using random walker and hierarchical normalized cuts

Lev Tchikindas, Rachel Sparks, Jennifer Baccon, David Ellison, Alexander R. Judkins, Anant Madabhushi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Medulloblastoma (MB) is the most common brain tumor in children. Recent studies have demonstrated a relationship between specific signaling pathway abnormalities, a tendency to more favorable outcomes, and a histopathological feature: nodular growth patterns. In this work we present a new segmentation scheme which requires minimal user interaction to segment nodules on MB histopathological sections. Our segmentation scheme consists of two steps: (1) color reduction using Hierarchical Normalized Cuts (HNCut), (2) Random Walker (RW) segmentation within the reduced HNCut color space. Across a cohort of 18 nodular MB images, our integrated HNCut and RW scheme yielded nodule segmentations with a Dice coefficient of 83:55 ± 12:4% and Predictive Positive Value (PPV) of 93:71 ± 9:0%.

Original languageEnglish (US)
Title of host publication2011 IEEE 37th Annual Northeast Bioengineering Conference, NEBEC 2011
DOIs
StatePublished - 2011
Event37th Annual Northeast Bioengineering Conference, NEBEC 2011 - Troy, NY, United States
Duration: Apr 1 2011Apr 3 2011

Publication series

Name2011 IEEE 37th Annual Northeast Bioengineering Conference, NEBEC 2011

Other

Other37th Annual Northeast Bioengineering Conference, NEBEC 2011
CountryUnited States
CityTroy, NY
Period4/1/114/3/11

All Science Journal Classification (ASJC) codes

  • Bioengineering

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