Robust Cortical Thickness Measurement with LOGISMOS-B

  • Ipek Oguz
  • Milan Sonka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)


Cortical thickness (CT) is an important morphometric measure that has implications for psychiatric and neurologic processes. We propose a novel approach for automatically computing CT in an accurate and robust manner using LOGISMOS-B: Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces for the Brain. LOGISMOS-B is a cortical surface segmentation method based on LOGISMOS graph segmentation and generalized gradient vector flows. We evaluate our method on two different datasets (n = 83 total). The results show that LOGISMOS-B is more accurate than the popular FreeSurfer (FS) method and provides more reliable thickness measurements across a variety of challenging images. LOGISMOS-B accurately recovers known CT patterns, both across cortical lobes and locally, such as between the banks of the central sulcus, in healthy subjects and MS patients. Manual landmarks indicate a signed surface distance of 0.081±0.447mm for WM and 0.018±0.498mm for LOGISMOS-B, compared to 0.263±0.452mm for WM and − 0.167±0.556mm for GM for FS, highlighting the surface placement accuracy of LOGISMOS-B. Finally, a regresion study shows that LOGISMOS-B provides strong correlation with age and plausible annual thinning rates across the cortex, with locally discerning thinning patterns, in agreement with the literature.


LOGISMOS cortical thickness optimal multi-surface segmentation cortical reconstruction generalized gradient vector flow 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ipek Oguz
    • 1
  • Milan Sonka
    • 1
  1. 1.Department of Electrical and Computer EngineeringThe University of IowaIowa CityUSA

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