64 research outputs found
Edge-aware Multi-task Network for Integrating Quantification Segmentation and Uncertainty Prediction of Liver Tumor on Multi-modality Non-contrast MRI
Simultaneous multi-index quantification, segmentation, and uncertainty
estimation of liver tumors on multi-modality non-contrast magnetic resonance
imaging (NCMRI) are crucial for accurate diagnosis. However, existing methods
lack an effective mechanism for multi-modality NCMRI fusion and accurate
boundary information capture, making these tasks challenging. To address these
issues, this paper proposes a unified framework, namely edge-aware multi-task
network (EaMtNet), to associate multi-index quantification, segmentation, and
uncertainty of liver tumors on the multi-modality NCMRI. The EaMtNet employs
two parallel CNN encoders and the Sobel filters to extract local features and
edge maps, respectively. The newly designed edge-aware feature aggregation
module (EaFA) is used for feature fusion and selection, making the network
edge-aware by capturing long-range dependency between feature and edge maps.
Multi-tasking leverages prediction discrepancy to estimate uncertainty and
improve segmentation and quantification performance. Extensive experiments are
performed on multi-modality NCMRI with 250 clinical subjects. The proposed
model outperforms the state-of-the-art by a large margin, achieving a dice
similarity coefficient of 90.011.23 and a mean absolute error of
2.720.58 mm for MD. The results demonstrate the potential of EaMtNet as a
reliable clinical-aided tool for medical image analysis
Usefulness of N-terminal pro-brain natriuretic peptide and C-reactive protein to predict ICU mortality in unselected medical ICU patients: a prospective, observational study
Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Patients with Sepsis: A Prospective Observational Study
A taxonomic study of diatom plants in Yading Nature Reserve of Sichuan
In August 2015, diatom diversity of the Yading Nature Reserve of Sichuan was investigated. Diatom samples were observed using light microscope and scanning electron microscope. Totally, 81 species (including varieties) were identified, belonging to 3 classes and 19 families and 31 genera, of which 2 species were newly recorded from China:Cocconeis placentula var. klinorahis Geitler and Psammothidium daonense (Lange-Bertalot) Lange-Bertalot. For two newly reported species, morphological characters, habits and the distributions were described in detail
LAND USE/ LAND COVER CHANGE MONITORING USING ALOS PALSAR DATA IN FUZHOU, CHINA: FINAL REPORT
Performance Guaranteed Control of Flywheel Energy Storage System for Pulsed Power Load Accommodation
A hybrid cleaning scheduling framework for operations and maintenance of photovoltaic systems
Dust deposition on the surface of photovoltaic (PV) modules is a nonnegligible factor that reduces a PV system's efficiency and reliability. Cleaning can remove dust, and the effect of cleaning on PV performance resembles that of maintenance. In this article, we propose a hybrid cleaning scheduling policy with periodic planning and dynamic adjustment for refining the operations and maintenance of PV systems. Specifically, the periodic planning stage aims for medium-term scheduling while the dynamic adjustment stage is tailed for short-term fine-tuning. In the former stage, we show that when the number of cleaning actions is fixed, a periodic cleaning strategy is optimal. Moreover, we derive the optimality condition under which the optimal cleaning interval can be determined. In the latter stage, based on the determined cleaning interval, we dynamically adjust the cleaning schedule with the forecast of meteorological parameters, PV power generation, and dust deposition in order to further minimize economic losses. In addition, we take the forecasting uncertainty into account and propose a new custom parameter called risk-taking tendency (RTT), which is able to quantify the risk preference of decision makers and analyze its influence on the scheduling policy. A case study is provided to illustrate the proposed strategy
Constructing Robust Liquid Marbles for Miniaturized Synthesis of Graphene/Ag Nanocomposite
Miniaturized
synthesis is attracting much attention due to many potential applications;
a challenge remains in exploring versatile microreactors capable of
producing pure products. In this study, we reported a kind of thermally
robust liquid marbles and their application for miniaturized synthesis
of graphene/Ag nanocomposite. The liquid marbles were constructed
by using superhydrophobic Fe<sub>3</sub>O<sub>4</sub>/C microsheets
as encapsulating agents. Results revealed that the morphology of the
encapsulating agent as well as the humidity of atmosphere strongly
affected the robustness of liquid marbles at elevated temperature.
The resulting graphene/Ag nanocomposite showed one of the best catalytic
characteristics for 4-nitroaniline reduction among the reported catalysts.
The findings of this study not only offer an alternative insight into
the stability of liquid marbles at elevated temperature but also provide
a facile strategy for miniaturized synthesis
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