Anan Nugroho, Risanuri Hidayat, Hanung A. Nugroho, Johan Debayle
Purpose: Utilization of computer-aided diagnosis (CAD) on radiological ultrasound (US) imaging has increased tremendously. The prominent CAD applications are found in breast and thyroid cancer investigation. To make appropriate clinical recommendations, it is important to accurately segment the cancerous object called a lesion. Segmentation is a crucial step but undoubtedly a challenging problem due to various perturbations, e.g., speckle noise, intensity inhomogeneity, and low contrast. Approach: We present a combinatorial framework for US image segmentation using a bilateral filter (BF) and hybrid region-edge-based active contour (AC) model. The BF is adopted to smooth images while preserving edges. Then the hybrid model of region and edge-based AC is applied along the scales in a global-to-local manner to capture the lesion areas. The framework was tested in segmenting 258 US images of breast and thyroid, which were validated by manual ground truths. Results: The proposed framework is accessed quantitatively based on the overlapping values of the Dice coefficient, which reaches 90.05 ± 5.81%. The evaluation with and without the BF shows that the enhancement procedure improves the framework well. Conclusions: The high performance of the proposed method in our experimental results indicates its potential for practical implementations in CAD radiological US systems. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.
Universitas Gadjah Mada, Department of Electrical and Information Engineering, Yogyakarta, Indonesia; Universitas Negeri Semarang, Department of Electrical Engineering, Semarang, Indonesia; MINES Saint-Étienne, SPIN/LGF CNRS UMR 5307, Saint-Étienne Cedex 2, France
