Images now come in different forms -color, near-infrared, depth, etc. -due to the development of special and powerful cameras in computer vision and computational photography. Their cross-modal correspondence establishment is however left behind. We address this challenging dense matching problem considering structure variation possibly existing in these image sets and introduce new model and solution.Our main contribution includes designing the descriptor named robust selective normalized cross correlation (RSNCC) to establish dense pixel correspondence in input images and proposing its mathematical parameterization to make optimization tractable. A computationally robust framework including global and local matching phases is also established. We build a multi-modal dataset including natural images with labeled sparse correspondence. Our method will benefit image and vision applications that require accurate image alignment.
BackgroundThis study aims to establish a radiomics analysis system for the diagnosis and clinical behaviour prediction of hepatocellular carcinoma (HCC) based on multi-parametric ultrasound imaging.MethodsA total of 177 patients with focal liver lesions (FLLs) were included in the study. Every patient underwent multi-modal ultrasound examination, including B-mode ultrasound (BMUS), shear wave elastography (SWE), and shear wave viscosity (SWV) imaging. The radiomics analysis system was built on sparse representation theory (SRT) and support vector machine (SVM) for asymmetric data. Through the sparse regulation from the SRT, the proposed radiomics system can effectively avoid over-fitting issues that occur in regular radiomics analysis. The purpose of the proposed system includes differential diagnosis between benign and malignant FLLs, pathologic diagnosis of HCC, and clinical prognostic prediction. Three biomarkers, including programmed cell death protein 1 (PD-1), antigen Ki-67 (Ki-67) and microvascular invasion (MVI), were included and analysed. We calculated the accuracy (ACC), sensitivity (SENS), specificity (SPEC) and area under the receiver operating characteristic curve (AUC) to evaluate the performance of the radiomics models.ResultsA total of 2560 features were extracted from the multi-modal ultrasound images for each patient. Five radiomics models were built, and leave-one-out cross-validation (LOOCV) was used to evaluate the models. In LOOCV, the AUC was 0.94 for benign and malignant classification (95% confidence interval [CI]: 0.88 to 0.98), 0.97 for malignant subtyping (95% CI: 0.93 to 0.99), 0.97 for PD-1 prediction (95% CI: 0.89 to 0.98), 0.94 for Ki-67 prediction (95% CI: 0.87 to 0.97), and 0.98 for MVI prediction (95% CI: 0.93 to 0.99). The performance of each model improved when the viscosity modality was included.ConclusionsRadiomics analysis based on multi-modal ultrasound images could aid in comprehensive liver tumor evaluations, including diagnosis, differential diagnosis, and clinical prognosis.
The effects of production system on welfare traits, growth performance and meat quality of ducks were explored. A total of 120 newly hatched ducklings were randomly assigned to three groups: i) floor-reared system (FRS); ii) welfare-reared system (WRS) and iii) net-reared system (NRS) (n = 8 ducklings/pen, 5 pens/group). In the FRS, ducks were reared on sawdust bedding that was changed every 2 -3 days. The WRS was similar to the FRS, the difference being the addition of environmental enrichment devices such as perches, coloured balloons and ribbons. In the NRS, ducks were reared on plastic nets on a bamboo bed, and their droppings were cleaned daily with water. After 35 d, welfare traits, growth performance and meat quality of the ducks were measured. Moving and playing durations of WRS ducks were longer than FRS and NRS ducks. Bathing and feather pecking durations of NRS ducks were longer than FRS and WRS ducks. Duck feather quality was greater and gait defects were reduced in NRS system compared with FRS and WRS systems. Fluctuating asymmetry (FA) was not affected by the production system. Growth performance was not significantly different between FRS and WRS systems. Average daily weight gain of FRS ducks was higher than in NRS ducks. Feed conversion ratio of FRS ducks was lower than in NRS ducks. There was no difference in acidity, conductivity of pectoralis and leg muscle, and drip loss among the production systems. The conclusion was that NRS proved to be the best production system on welfare traits, while WRS and FRS were the best production systems on growth performance. ______________________________________________________________________________________
In this study, a short-term memory test was used to investigate the temporal course and neural mechanism of directed forgetting under different memory loads. Within each trial, two memory items with high or low load were presented sequentially, followed by a cue indicating whether the presented items should be remembered. After an interval, subjects were asked to respond to the probe stimuli. The ERPs locked to the cues showed that (a) the effect of cue type was initially observed during the P2 (160-240 ms) time window, with more positive ERPs for remembering relative to forgetting cues; (b) load effects were observed during the N2-P3 (250-500 ms) time window, with more positive ERPs for the high-load than low-load condition; (c) the cue effect was also observed during the N2-P3 time window, with more negative ERPs for forgetting versus remembering cues. These results demonstrated that directed forgetting involves two stages: task-relevance identification and information discarding. The cue effects during the N2 epoch supported the view that directed forgetting is an active process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.