A Fast Level-Set Curve-Flow Formulation by Logarithmic Step-Size Control for Brain Ultrasound Image Segmentation

Abstract

Segmentation of different regions in intra-operative brain ultrasound (iBUS) images is often required for assisting the neuro-surgeon. Traditional level-set and active contour-based semi-automatic image segmentation approaches suffer from low accuracy and slow convergence. This paper presents a novel semi-automatic level-set approach for segmenting hyper-echoic (HE), hypo-echoic, and anechoic regions with minimal user intervention. Three HE regions longitudinal fissure, choroid plexus, and tumor and two anechoic regions, namely ventricle and resection cavity are segmented using a patch-based level-set approach. This method is a combination of three procedures: a) unidirectional level-set curve flow (ULSCF), b) bidirectional level-set curve flow (BLSCF) using a logarithmic patch size control, and c) cubic B-spline-based contour smoothing. The zero level-set curve is derived using a patch-based intensity thresholding method of the desired region. The imperfection on the blocky edges produced during the patch-based ULSCF, are minimized using the BLSCF step that uses a local region splitting approach. Slope and curvature discontinuities of the resulting boundaries after BLSCF are eliminated using cubic B-spline based contour smoothing. The proposed method outperforms other state-of-the-art level-set and active contour methods, and the desired result is obtained within reasonable time required for online monitoring during surgery.

Keywords

• Ultrasound guided surgery
• ultrasound image segmentation
• patch-based segmentation
• boundary correction
• contour smoothing