Medical Image Segmentation Using a Robust Edge-stop Function with 2×2 Window Patch

Edge-based active contour models using robust edge-stop functions (ESFs) have shown their effectiveness in segmenting medical images. The ESFs utilize classification scores from machine learning algorithms which are sensitives to the feature vector. The number of features influences the speed of the algorithms. Previous studies utilize image patch 3×3 which consists of 9 components in the feature vector and leads to a long computational time. This paper investigates the use of a simple feature vector for the ESFs. An image patch of 2×2 is selected and applied to a classification algorithm, namely the k-nearest neighbors (k-NN). Experimental results indicate that the feature leads to similar in accuracy but faster in computational speed.

[1]  V. Caselles,et al.  A geometric model for active contours in image processing , 1993 .

[2]  J. Sethian,et al.  FRONTS PROPAGATING WITH CURVATURE DEPENDENT SPEED: ALGORITHMS BASED ON HAMILTON-JACOB1 FORMULATIONS , 2003 .

[3]  Chunming Li,et al.  A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application to MRI , 2011, IEEE Transactions on Image Processing.

[4]  David G. Stork,et al.  Pattern Classification , 1973 .

[5]  Hua Zhang,et al.  Image Segmentation Using Active Contours With Normally Biased GVF External Force , 2010, IEEE Signal Processing Letters.

[6]  Bart De Dobbelaer,et al.  Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification , 2010, Medical Image Anal..

[7]  Sim Heng Ong,et al.  Region Growing for Medical Image Segmentation Using a Modified Multiple-seed Approach on a Multi-core CPU Computer , 2014 .

[8]  R. Rautmann.  Approximation Methods for Navier-Stokes Problems , 1980 .

[9]  Sim Heng Ong,et al.  Robust Edge-Stop Functions for Edge-Based Active Contour Models in Medical Image Segmentation , 2016, IEEE Signal Processing Letters.

[10]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[11]  P. Sivakumar,et al.  A REVIEW ON IMAGE SEGMENTATION TECHNIQUES , 2016 .

[12]  Tinsu Pan,et al.  Fundamentals of Medical Imaging , 2010, The Journal of Nuclear Medicine.

[13]  Aman Mittal,et al.  A Review on Image Segmentation Techniques , 2016 .

[14]  Zhou-Ping Yin,et al.  The Fast Multilevel Fuzzy Edge Detection of Blurry Images , 2007, IEEE Signal Processing Letters.

[15]  Scott T. Acton,et al.  Region Based Segmentation in Presence of Intensity Inhomogeneity Using Legendre Polynomials , 2015, IEEE Signal Processing Letters.

[16]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[17]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[19]  A. Dervieux,et al.  A finite element method for the simulation of a Rayleigh-Taylor instability , 1980 .