Region growing segmentation of ultrasound images using gradients and local statistics

Isabela M. Mercado-Aguirre; Alberto Patiño-Vanegas; Sonia H. Contreras-Ortiz

doi:10.1117/12.2254518

13 March 2017 Region growing segmentation of ultrasound images using gradients and local statistics

Isabela M. Mercado-Aguirre, Alberto Patiño-Vanegas, Sonia H. Contreras-Ortiz

Proceedings Volume 10139, Medical Imaging 2017: Ultrasonic Imaging and Tomography; 101391E (2017) https://doi.org/10.1117/12.2254518
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

This paper describes a region growing segmentation algorithm for medical ultrasound images. The algorithm starts with anisotropic diffusion filtering to reduce speckle noise without blurring the edges. Then, region growing is performed starting from a seed point, using a merging criterion that compares intensity gradients to the noise level inside the region. Finally, the boundaries are smoothed using morphological closing. The algorithm was evaluated with two simulated images and eleven phantom images and converged in 10 of them with accurate region delimitation. Preliminary results show that the proposed method can be used for ultrasound image segmentation and does not require previous knowledge of the anatomy of the structures.

Citation Download Citation

Isabela M. Mercado-Aguirre, Alberto Patiño-Vanegas, and Sonia H. Contreras-Ortiz "Region growing segmentation of ultrasound images using gradients and local statistics", Proc. SPIE 10139, Medical Imaging 2017: Ultrasonic Imaging and Tomography, 101391E (13 March 2017); https://doi.org/10.1117/12.2254518

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