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Texture-based Deformable Snake Segmentation of the Liver

Texture-based Deformable Snake Segmentation of the Liver. Aaron Mintz Daniela Stan Raicu, PhD Jacob Furst, PhD. Overview. Objectives and Incentives Tested Texture Methods Tested Snake Deformations Numerical Evaluation Future Work. Motivations. Important Diagnostic Aid to Radiologist

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Texture-based Deformable Snake Segmentation of the Liver

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  1. Texture-based Deformable Snake Segmentation of the Liver Aaron Mintz Daniela Stan Raicu, PhD Jacob Furst, PhD

  2. Overview • Objectives and Incentives • Tested Texture Methods • Tested Snake Deformations • Numerical Evaluation • Future Work

  3. Motivations • Important Diagnostic Aid to Radiologist • Liver Cancer: Extremely Deadly • Hypothesis: Texture vs. Intensity-based snake deformation • Pixel-to-Pixel area information • Results Show up to 48% Increase in Segmentation Accuracy (Gabor)

  4. Process and Methods

  5. Data Archive • Original Computed-Tomography Scans • 25 Individual Patients • Greatly Varying Patient Sets • DICOM Format • Binary Ground Truth • 2916 Image-Ground Pairs

  6. Image Pre-processing: Gabor Filter • Gabor Filter • Gaussian x Sinusoid • Various Parameters • Aspect Ratio • Standard Deviation • Wavelength • Orientation

  7. Image Pre-processing: Haralick Feature Extraction • Locally-Calculated Process • Bin Large Range of Intensity Values • Window-Based Quantification of Intensity-Value Co-Occurrence • Numerical Analysis of Each Corresponding Matrix to Derive Features • 9 Features Calculated

  8. Image Pre-processing: Markov Random Fields • Also Locally-Calculated • Estimate “Markovianity” of Windowed Regions • Orientation-based Texture Model

  9. Snake Constraints • Limited Input • Too Many Corresponding Filters/Features per Image Pixel • Principle Components Analysis • Equivalent Number of Principle Components Returned

  10. Snake Input • All Principle Components Evaluated Individually • Gradient Value Edge Map • Second Gradient Edge Map • Automatic Initial Curve Point Selection

  11. Snake Segmentation Methods • Traditional Vector Field Model • Gradient Vector Flow (GVF) • Level-Set Evolution

  12. Snake Segmentation Methods (cont.) • Balance of Energy Equation • Disadvantages of GVF, Level-Set

  13. Metrics and Results • Computationally Difficult to Evaluate Meaningfully • Straightforward Measurement of Accuracy • 3-Dimensional Analysis • Volumetric Overlap • Average Distance • Root-Mean-Square Distance • Hausdorff Distance

  14. Results • Effectiveness of Texture Heavily Dependent on Region of Liver Depicted Gabor Statistics Across 20-Patient Dataset

  15. Future Work • Expanding Base of Co-Occurrence and Markov Comparison • Attempt Combined Principle Components Analysis • Combined Approach – New Automatic Initial Point Selection

  16. Credits • Carl Philips • Dr. Raicu, Dr. Furst • Chenyang Xu, Jerry L. Prince, Chunming Li

  17. Questions?

  18. Entropy: Energy: Contrast: Sum Average: Variance: Correlation: Maximum Probability: Inverse Difference Moment: Cluster Tendency: Haralick Features

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