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JOIG 2024 Vol.12(1): 23-31
doi: 10.18178/joig.12.1.23-31

A Geometric Flow Approach for Segmentation of Images with Inhomongeneous Intensity and Missing Boundaries

Paramjyoti Mohapatra 1, Richard Lartey 2, Weihong Guo 1,*, Michael Judkovich 1, and Xiaojuan Li 2
1. Department of Mathemaitcs, Applied Mathematics and Statistics, Case Western Reserve University, Cleveland, Ohio, USA
2. Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
Email: pxm417@case.edu (P.M.), wxg49@case.edu (W.G.), LARTEYR@ccf.org (R.L.), mxj309@case.edu (M.J.), lix6@ccf.org (X.L.)
*Corresponding author

Manuscript received September 8, 2023; revised October 15, 2023; accepted November 10, 2023; published February 6, 2024.

Abstract—Image segmentation is a complex mathematical problem, especially for images that contain intensity inhomogeneity and tightly packed objects with missing boundaries in between. For instance, Magnetic Resonance (MR) muscle images often contain both issues, making muscle segmentation especially difficult. In this paper we propose a novel intensity correction and a semi-automatic active contour-based segmentation approach. The approach uses a geometric flow that incorporates a Reproducing Kernel Hilbert Space (RKHS) edge detector and a geodesic distance penalty term from a set of markers and anti-markers. We test the proposed scheme on MR muscle segmentation and compare with some state-of-the-art methods. To help deal with the intensity inhomogeneity in this kind of image, a new approach to estimate the bias field using a fat fraction image, called Prior Bias-Corrected Fuzzy C-means (PBCFCM), is introduced. Numerical experiments show that the proposed scheme leads to significantly better results than compared ones. The average dice values of the proposed method are 92.5%, 85.3%, 85.3% for quadriceps, hamstrings and other muscle groups while other approaches are at least 10% worse.

Keywords—3D segmentation, active contour, missing boundary, semi-automatic, marker, anti-marker

Cite: Paramjyoti Mohapatra, Richard Lartey, Weihong Guo, Michael Judkovich, and Xiaojuan Li, "A Geometric Flow Approach for Segmentation of Images with Inhomongeneous Intensity and Missing Boundaries," Journal of Image and Graphics, Vol. 12, No. 1, pp. 23-31, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.