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An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm...
Imbalanced data is an inevitable problem in many real world problems, including bleeding detection from endoscopic videos with a fewer clinically significant examples outnumbered by normal examples. In this paper, we have presented a comprehensive analysis of six different classifier performance for different class distribution of training dataset. We have addressed two questions: 1. Is there any...
This paper presents a novel technique for detecting bleeding regions in capsule endoscopy images. The proposed algorithm extracts color features from image-regions by calculating mean, standard deviation, skew and energy from the first order histogram of the RGB planes separately. Through the use of RGB color space, three times more number of features can be obtained than while using a grayscale image...
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