Title :
Microcalcification enhancement in ultrasound images from a concave Automatic Breast Ultrasound Scanner
Author :
Zhuang, Bohan ; Chen, T. ; Leung, Clement ; Chan, Kap Luk ; Dixon, J. ; Dickie, K. ; Pelissier, L.
Author_Institution :
Ultrasonix Med. Corp., Richmond, BC, Canada
Abstract :
In this paper, we have proposed a tensor-based filtering method to enhance the SNR of hyperechoic spots in human breast ultrasound images while suppressing the speckle noise. The breast images were acquired by an Automatic Breast Ultrasound Scanner (ABUS), which offers high spatial resolution and the fast full breast exam capability. The enhanced images were then gone through a pattern recognition kernel to distinguish the small hyperechoic spots against large tissue boundaries. The isolated hyperechoic spots were finally merged back to the original image. We believe the proposed method can facilitate the detection and analyzing of microcalcifications (MC) in the noisy ultrasound images. This could offer a non-invasive alternative solution for the mammography in breast cancer diagnosis.
Keywords :
biological organs; biological tissues; biomedical ultrasonics; image enhancement; image recognition; medical image processing; speckle; tensors; automatic breast ultrasound scanner; breast cancer diagnosis; human breast ultrasound image; hyperechoic spot SNR enhancement; image enhancement; mammography; microcalcification analysis; microcalcification detection; microcalcification enhancement; noisy ultrasound image; pattern recognition kernel; signal-to-noise ration enhancement; spatial resolution; speckle noise suppression; tensor-based filtering method; tissue boundary; Breast; Image reconstruction; Kernel; Noise; Speckle; Tensile stress; Ultrasonic imaging; Automatic Breast Ultrasound Scanner; Microcalcification; Tensor-based analysis;
Conference_Titel :
Ultrasonics Symposium (IUS), 2012 IEEE International
Conference_Location :
Dresden
Print_ISBN :
978-1-4673-4561-3
DOI :
10.1109/ULTSYM.2012.0417