Smoothing of ultrasound images using a new selective average filter

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Alex F. de Araújo (Author) FEUP; Christos E. Constantinou (Author) Other; João Manuel R. S. Tavares (Author) FEUP

Journal

Title: Expert Systems with Applications

Vol. 60

Pages: 96-106

ISSN: 0957-4174

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 13 Citations

ISI Web of Science

Scopus - 26 Citations

INSPEC

Scientific classification

CORDIS: Technological sciences

FOS: Engineering and technology

Other information

Authenticus ID: P-00K-GFZ

DOI: 10.1016/j.eswa.2016.04.034

Abstract (EN): Ultrasound images are strongly affected by speckle noise making visual and computational analysis of the structures more difficult. Usually, the interference caused by this kind of noise reduces the efficiency of extraction and interpretation of the structural features of interest. In order to overcome this problem, a new method of selective smoothing based on average filtering and the radiation intensity of the image pixels is proposed. The main idea of this new method is to identify the pixels belonging to the borders of the structures of interest in the image, and then apply a reduced smoothing to these pixels, whilst applying more intense smoothing to the remaining pixels. Experimental tests were conducted using synthetic ultrasound images with speckle noisy added and real ultrasound images from the female pelvic cavity. The new smoothing method is able to perform selective smoothing in the input images, enhancing the transitions between the different structures presented. The results achieved are promising, as the evaluation analysis performed shows that the developed method is more efficient in removing speckle noise from the ultrasound images compared to other current methods. This improvement is because it is able to adapt the filtering process according to the image contents, thus avoiding the loss of any relevant structural features in the input images.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11