The utilization of artificial intelligence has had a profound impact on diverse areas within the medical field day by day. Specifically, the identification and management of gliomas, a specific category of brain tumor...
ISBN:
(纸本)9798400708138
The utilization of artificial intelligence has had a profound impact on diverse areas within the medical field day by day. Specifically, the identification and management of gliomas, a specific category of brain tumors characterized by a challenging prognosis, heavily depend on the computer-assisted analysis of magnetic resonance imaging (MRI) scans. In the present study, we introduce a novel approach based on neural architecture search (NAS) for accurately segmenting brain tumors utilizing multimodal volumetric MRI scans. Our method employs three classes of candidate operations for different cells, with each operation having a learnable probabilistic parameter. By iteratively updating the operation weights and other network parameters, we discover optimal structure for the encoder and decoder cells. Additionally, we introduce an attention module connection to the automatic search, complementing the connection between the encoder cells and decoder cells for brain MRI processing. Through extensive experiments conducted on the BraTS 2019 dataset, we validate the effectiveness and scalability of our proposed algorithm. Our approach not only relieves the burden of manual architecture design but also achieves competitive performance in terms of brain tumor segmentation.
This is the first paper on symmetry classification for ordinary differential equations(ODEs)based on Wu’s *** carry out symmetry classification of two ODEs,named the generalizations of the Kummer-Schwarz equations wh...
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This is the first paper on symmetry classification for ordinary differential equations(ODEs)based on Wu’s *** carry out symmetry classification of two ODEs,named the generalizations of the Kummer-Schwarz equations which involving arbitrary ***,Lie algorithm is used to give the determining equations of symmetry for the given equations,which involving arbitrary ***,differential form Wu’s method is used to decompose determining equations into a union of a series of zero sets of differential characteristic sets,which are easy to be solved *** branch of the decomposition yields a class of symmetries and associated *** algorithm makes the classification become direct and *** Dimitrov Bozhkov,and Pammela Ramos da Conceição have used the Lie algorithm to give the symmetry classifications of the equations talked in this paper in *** this paper,we can find that the differential form Wu’s method for symmetry classification of ODEs with arbitrary function(parameter)is effective,and is an alternative method.
Cardiac image segmentation is critical for medical diagnosis and treatment planning. Traditional approaches often face accuracy challenges. In this study, we propose a deep learning-based method that incorporates arch...
ISBN:
(纸本)9798400708138
Cardiac image segmentation is critical for medical diagnosis and treatment planning. Traditional approaches often face accuracy challenges. In this study, we propose a deep learning-based method that incorporates architectural improvements and optimization techniques to overcome these limitations. Our method integrates skip connections, a spatial attention mechanism, and label smoothing for enhanced segmentation performance. Experimental results on the CAMUS dataset show that our approach surpasses baseline models, achieving superior segmentation accuracy. Specifically, our method increases the mean Intersection over Union (mIoU) from 0.8141 (U-Net) to 0.8428 (Residual Attention U-Net) and the mean Dice score from 0.8948 (U-Net) to 0.9127 (Residual Attention U-Net). The proposed method has potential applications in medical diagnosis, disease prevention, and treatment planning, emphasizing its practical significance in cardiac image segmentation.
The 3-dimensional(3D)modeling of crop canopies is fundamental for studying functional-structural plant *** studies often fail to capture the structural characteristics of crop canopies,such as organ overlapping and re...
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The 3-dimensional(3D)modeling of crop canopies is fundamental for studying functional-structural plant *** studies often fail to capture the structural characteristics of crop canopies,such as organ overlapping and resource *** address this issue,we propose a 3D maize modeling method based on computational *** initial 3D maize canopy is created using the t-distribution method to reflect characteristics of the plant architecture.
In this paper, a compact and highly selective stacked filtering dense dielectric patch (DDP) antenna (DDPA) is proposed. By placing a pair of thin DDP with high dielectric constant along the y axis on the DDP with low...
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Most existing unbiased learning-to-rank (ULTR) approaches are based on the user examination hypothesis, which assumes that users will click a result only if it is both relevant and observed (typically modeled by posit...
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The aim of cross-modal image-text retrieval is to heighten comprehension and to create robust associations between visual and textual content. This process entails a mutual querying and synchronization across various ...
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In order to reconfigure its structure from the static state in the vision odd ball task, so as to realize the intention recognition based on the characteristics of the brain functional network. The thesis proposes the...
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The identification of drug-protein interactions (DTIs) is a critical step in drug development and repositioning. However, detecting these interactions using scientific methods presents a formidable challenge. Existing...
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In large-scale networks, the state space is exploding and changing dynamically. This leads to difficulties in collecting and analyzing situational awareness data, so we construct an adaptive situational awareness mode...
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