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Feature extraction plays an important role in the whole process of liver characterization. Because the ultrasonic scanner in use can be adjusted by different clinicians to produce optimal images, the ultrasound images captured sometimes can be greatly influenced by machine settings and further impact the classification result. In this paper, some(More)
In this paper, we present an experiment to extract liver features using two-dimensional phase congruency, which is invariant to changes in intensity or contrast, to try to avoid the influence of machine settings. The effectiveness of our method was tested on three classes of liver images and shows the potential for physicians to quantify liver pathology in(More)
Diagnostic ultrasound is one of useful and noninvasive tools for clinical medicine. However, due to its qualitative, subjective and experience-based nature, ultrasound images can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a novel method is proposed to extract the liver features using the joint features(More)
Three-dimensional fuzzy logic controller (3-D FLC) is a novel FLC developed for spatially-distributed parameter systems. In this paper, we are concerned with data-based 3-D FLC design. A table look-up scheme is employed to design 3-D FLC in terms of input-out pairs. The design is composed of five steps, including division of data space, generation of fuzzy(More)
The problem of fine-grained object recognition is very challenging due to the subtle visual differences between different object categories. In this paper we propose a taskdriven progressive part localization (TPPL) approach for finegrained object recognition. Most existing methods follow a two-step approach which first detects salient object parts to(More)
Amplitude-integrated EEG (aEEG) is becoming increasingly useful in the monitoring of clinically ill neonates. Manual interpretation of aEEG signals may result in subjectivity, so an effective method for automatic interpretation of aEEG tracings is urgently needed. To catch the main characteristics of aEEG signals, five featureswere calculated, inwhich(More)