AIMC Topic: Neural Networks, Computer

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Label2label: training a neural network to selectively restore cellular structures in fluorescence microscopy.

Journal of cell science
Immunofluorescence microscopy is routinely used to visualise the spatial distribution of proteins that dictates their cellular function. However, unspecific antibody binding often results in high cytosolic background signals, decreasing the image con...

Measurement of Body Surface Area for Psoriasis Using U-net Models.

Computational and mathematical methods in medicine
During the evaluation of body surface area (BSA), precise measurement of psoriasis is crucial for assessing disease severity and modulating treatment strategies. Physicians usually evaluate patients subjectively through direct visual evaluation. Howe...

Automatic Arrangement of Sports Dance Movement Based on Deep Learning.

Computational intelligence and neuroscience
Sports dance is a new form of sports that integrates sports, dance, music, and other elements. The core content of "dance" is an important carrier for athletes to display their body art. This article aims to study the automatic arrangement of sports ...

Classification of Citrus Diseases Using Optimization Deep Learning Approach.

Computational intelligence and neuroscience
Most plant diseases have apparent signs, and today's recognized method is for an expert plant pathologist to identify the disease by looking at infected plant leaves using a microscope. The fact is that manually diagnosing diseases is time consuming ...

Intrinsic Decomposition Method Combining Deep Convolutional Neural Network and Probability Graph Model.

Computational intelligence and neuroscience
With the rapid development of computer vision and artificial intelligence, people are increasingly demanding image decomposition. Many of the current methods do not decompose images well. In order to find the decomposition method with high accuracy a...

Investigation of Three-Dimensional Condensation Film Problem over an Inclined Rotating Disk Using a Nonlinear Autoregressive Exogenous Model.

Computational intelligence and neuroscience
This paper analyzed the three-dimensional (3D) condensation film problem over an inclined rotating disk. The mathematical model of the problem is governed by nonlinear partial differential equations (NPDE's), which are reduced to the system of nonlin...

Using machine learning as a surrogate model for agent-based simulations.

PloS one
In this proof-of-concept work, we evaluate the performance of multiple machine-learning methods as surrogate models for use in the analysis of agent-based models (ABMs). Analysing agent-based modelling outputs can be challenging, as the relationships...

Rupture risk prediction of cerebral aneurysms using a novel convolutional neural network-based deep learning model.

Journal of neurointerventional surgery
BACKGROUND: Cerebral aneurysms should be treated before rupture because ruptured aneurysms result in serious disability. Therefore, accurate prediction of rupture risk is important and has been estimated using various hemodynamic factors.

Report on the AAPM deep-learning sparse-view CT grand challenge.

Medical physics
PURPOSE: The purpose of the challenge is to find the deep-learning (DL) technique for sparse-view computed tomography (CT) image reconstruction that can yield the minimum root mean square error (RMSE) under ideal conditions, thereby addressing the qu...

Highly Efficient and Accurate Deep Learning-Based Classification of MRI Contrast on a CPU and GPU.

Journal of digital imaging
Classifying MR images based on their contrast mechanism can be useful in image segmentation where additional information from different contrast mechanisms can improve intensity-based segmentation and help separate the class distributions. In additio...