AIMC Topic: Algorithms

Clear Filters Showing 7841 to 7850 of 28713 articles

An innovative breast cancer detection framework using multiscale dilated densenet with attention mechanism.

Network (Bristol, England)
Cancer-related deadly diseases affect both developed and underdeveloped nations worldwide. Effective network learning is crucial to more reliably identify and categorize breast carcinoma in vast and unbalanced image datasets. The absence of early can...

Topological information embedded convolutional neural network-based lotus effect optimization for path improvisation of the mobile anchors in wireless sensor networks.

Network (Bristol, England)
Wireless sensor networks (WSNs) rely on mobile anchor nodes (MANs) for network connectivity, data aggregation, and location information. However, MANs' mobility can disrupt energy consumption and network performance. Effective path improvisation algo...

An Intuitionistic Fuzzy C-Means and Local Information-Based DCT Filtering for Fast Brain MRI Segmentation.

Journal of imaging informatics in medicine
Structural and photometric anomalies in the brain magnetic resonance images (MRIs) affect the segmentation performance. Moreover, a sudden change in intensity between two boundaries of the brain tissues makes it prone to data uncertainty, resulting i...

Effect of MR head coil geometry on deep-learning-based MR image reconstruction.

Magnetic resonance in medicine
PURPOSE: To investigate whether parallel imaging-imposed geometric coil constraints can be relaxed when using a deep learning (DL)-based image reconstruction method as opposed to a traditional non-DL method.

DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain.

NMR in biomedicine
Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susc...

On the Kolmogorov neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we show that the Kolmogorov two hidden layer neural network model with a continuous, discontinuous bounded and unbounded activation function in the second hidden layer can precisely represent continuous, discontinuous bounded and all u...

Model-free robust motion control for biological optical microscopy using time-delay estimation with an adaptive RBFNN compensator.

ISA transactions
The field of large numerical aperture microscopy has witnessed significant advancements in spatial and temporal resolution, as well as improvements in optical microscope imaging quality. However, these advancements have concurrently raised the demand...

Lesion attention guided neural network for contrast-enhanced mammography-based biomarker status prediction in breast cancer.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate identification of molecular biomarker statuses is crucial in cancer diagnosis, treatment, and prognosis. Studies have demonstrated that medical images could be utilized for non-invasive prediction of biomarker statu...

Advancing musculoskeletal tumor diagnosis: Automated segmentation and predictive classification using deep learning and radiomics.

Computers in biology and medicine
OBJECTIVES: Musculoskeletal (MSK) tumors, given their high mortality rate and heterogeneity, necessitate precise examination and diagnosis to guide clinical treatment effectively. Magnetic resonance imaging (MRI) is pivotal in detecting MSK tumors, a...