Enhancing Breast Ultrasound Images: A Phantom Study
TL;DR: This work was to increase radiologist's efficiency on interpreting the results of portable ultrasound machine using Computer-Aided Detection (CAD) algorithm and improve the efficiency of interpretation and enhanced visualization, decrease interpreting time while increase SNR.
About: This article is published in Biophysical Journal.The article was published on 2012-01-31 and is currently open access. It has received 2 citations till now. The article focuses on the topics: Breast imaging & Breast ultrasound.
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29 May 2012
TL;DR: In this article, a computer aided detection (CADD) algorithm was proposed to automatically extract Cystic Masses from Ultrasound Phantom images and improve the efficiency of interpretation using Computer-Aided Detection.
Abstract: The aim of this work is to automatically extract Cystic Masses from Ultrasound Phantom images and improve the efficiency of interpretation using Computer-Aided Detection. To make it a general algorithm, 6 most popular ultrasound machines were selected and following parameters were swept: modes of operation, transducer, frequency and contrast, while making phantom images. Ultrasound images were acquired using a quality multi tissue Ultrasound Phantom in B-Mode. Gamma corrections, contrast stretching, filtering and morphological Image Processing were among the steps that were applied to find the output image. Two experienced radiologists marked final images. Statistical analysis of results showed a sensitivity of 99% and accuracy of 98% for proposed framework. As a side result based on the actual depth of each image, processing time were also decreased.
3 citations
24 Jul 2012
TL;DR: It was shown that the same procedure can be use for cystic and solid breast masses with small changes and sensitivity and accuracy showed 100% and accuracy of 99% for proposed work.
Abstract: This study is focused on automatic detection of tumors in Ultrasound breast images in order to help medical doctors in interpretation of such images using Computer-Aided Detection. In this way a set of 6 most popular ultrasound machines were selected and images were captured with sweeping: modes of operation, transducer, frequency and contrast. A multi purpose multi tissue Ultrasound Phantom was used to make a complete set of ultrasound images in B-Mode. Pre-processing steps such as gamma corrections, contrast stretching and filtering accompanied by morphological Image Processing were among the steps that were applied to find the final image. All output images were reviewed and marked by two experienced radiologists. Statistical analysis showed a sensitivity of 100% and accuracy of 99% for proposed work. It also showed that the same procedure can be use for cystic and solid breast masses with small changes.