Content-based ultrasound image retrieval using magnitude frequency spectrum

Jae Gon Son; Jong In Kwak; Sang Hyun Kim; Nam Chul Kim

doi:10.1117/12.428219

30 May 2001 Content-based ultrasound image retrieval using magnitude frequency spectrum

Jae Gon Son, Jong In Kwak, Sang Hyun Kim, Nam Chul Kim

Proceedings Volume 4325, Medical Imaging 2001: Ultrasonic Imaging and Signal Processing; (2001) https://doi.org/10.1117/12.428219
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

We propose an efficient method for content-based ultrasound image retrieval using magnitude frequency spectrum and implement an ultrasound image retrieval system based on the proposed method. The target images are ultrasound images of adult organs. A trained staff often acquires such images so that images of the same kind of organs are very similar, although their locations may not exactly coincide. Therefore, the magnitude frequency spectrum, which has a translation-invariant property, is used as a feature for content-based retrieval. A test image database is composed of real ultrasound images. As a retrieval result, a specified number of highly similar target images are retrieved from all the target images. If all the target images in the database are pre-classified into organs of the same kind, the retrieved images are selected among the images whose class is the same as that of the highest similarity image. Experimental results of the proposed method is superior to other methods. The proposed method especially yields further performance improvement by using the pre-classification. Moreover, it is found from the experimental results that the magnitude frequency spectrum method is robust to the speckle noise that usually exists in ultrasound images.

Citation Download Citation

Jae Gon Son, Jong In Kwak, Sang Hyun Kim, and Nam Chul Kim "Content-based ultrasound image retrieval using magnitude frequency spectrum", Proc. SPIE 4325, Medical Imaging 2001: Ultrasonic Imaging and Signal Processing, (30 May 2001); https://doi.org/10.1117/12.428219

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KEYWORDS

Image retrieval

Ultrasonography

Feature extraction

Databases

Wavelets

Speckle

Visualization

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