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This paper proposes a novel fully automatic diagnosis method for liver cirrhosis based on the reading of high-frequency ultrasound images. The proposed method determines the cirrhosis stage via a deep-learning neural network. First, we feed an ultrasound image into an autoencoder to generate the capsule-enhanced version of the image and binarize the enhanced image. Then, we employ a partition-clustering...
This paper proposes a novel method to extract and describe liver capsule contour in high-frequency ultrasound image for early diagnosis of HBV cirrhosis. The proposed method combines vertical gradient optimization and minimum of deflection error to approximate the outline of liver capsule using a number of reference points determined through interactive selection. We also propose a Continuity of Capsule...
3D facial landmarks play a significant role in many 3D facial studies. Due to the complex geometry of high resolution 3D human face, landmark detection remains to be a challenge problem. This paper proposes a novel method to detect landmarks automatically for high resolution 3D faces without learning or training, solely using geometric information. For high resolution 3D faces, geodesic remeshing...
This paper focuses on the multiple attribute decision making problems with the attribute values being preference orderings and interval numbers evaluations. For the attributes with preference orderings evaluations, the fuzzy preference relation between the alternatives are calculated and the their rankings values are further normalized by measuring their relative distances to the ideal point; For...
This paper focuses on the multiple attribute decision making problems with the attribute values being numeric, interval and linguistic evaluations. The decision matrix is normalized by calculating the grey relation coefficients of the interval and linguistic attribute values to their corresponding positive ideal ones. Furthermore, a mathematical programming model is set up to figure out the attribute...
This paper focuses on the multiple attribute decision making problems with the attribute values being numeric, uncertain fuzzy selected subset and linguistics variable evaluations. For the fuzzy selected subset attribute values, by calculating the fuzzy preference relation between them and the quantifier guided dominance degrees of them can be obtained as their single-point evaluations. For the linguistics...
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