Amniotic Fluid Segmentation by Pixel Classification in B-Mode Ultrasound Image for Computer Assisted Diagnosis
作者： Desiana Wulaning Ayu , Sri Hartati , Aina Musdholifah
DOI: 10.1007/978-981-15-0399-3_5
关键词:
摘要: B-mode ultrasound imaging segmentation is facing a challenge in the artifacts such as speckle noise, blurry edges, low contrast, and unexpected shadow. This study proposed model considering local information from each pixel based upon its neighborhood information. The features used are statistical texture (mean intensity, deviation standard, skewness, entropy, property) taken 3 × 5 window. Random forest was to classify into three regions: amniotic fluid, uterus, fetal body. An evaluation carried out by calculating comparison between ground truth area results of model. experimental showed that has an average accuracy 81.45% window 85.86% on 50 tested images.
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