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 90.01$\pm$1.23 and a mean absolute error of 2.72$\pm$0.58 mm for MD. The results demonstrate the potential of EaMtNet as a reliable clinical-aided tool for medical image analysis

Artificial intelligence of cultivating the communication ability of college students majoring in accounting in the context of the Internet

With the impact of the development of artificial intelligence on the accounting industry, the society puts forward new requirements for the professional quality of accountants, especially the communication ability. This change leads to the communication ability of accounting students can not meet the changing needs of social development. In order to study this difference, this paper, in the form of Web information analysis and questionnaire survey, analyse the problems existing in the cultivation of communication ability of college students majoring in accounting in the era of artificial intelligence from three aspects - market demand, talent cultivation and cultivation subject, and puts forward some targeted suggestions on the curriculum and teaching content of colleges and universities according to the industry and market demand, so as to cultivate the students’ communication ability Cultivate modern accounting professionals to meet the needs of the market

Design of Nanoparticle-Based Carriers for Targeted Drug Delivery

Nanoparticles have shown promise as both drug delivery vehicles and direct antitumor systems, but they must be properly designed in order to maximize efficacy. Computational modeling is often used both to design new nanoparticles and to better understand existing ones. Modeled processes include the release of drugs at the tumor site and the physical interaction between the nanoparticle and cancer cells. In this paper, we provide an overview of three different targeted drug delivery methods (passive targeting, active targeting, and physical targeting) and compare methods of action, advantages, limitations, and the current stages of research. For the most commonly used nanoparticle carriers, fabrication methods are also reviewed. This is followed by a review of computational simulations and models on nanoparticle-based drug delivery