AIMC Topic: Image Processing, Computer-Assisted

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The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT.

Medicine
In 2020, the new type of coronal pneumonitis became a pandemic in the world, and has firstly been reported in Wuhan, China. Chest CT is a vital component in the diagnostic algorithm for patients with suspected or confirmed COVID-19 infection. Therefo...

Deep learning approaches for neural decoding across architectures and recording modalities.

Briefings in bioinformatics
Decoding behavior, perception or cognitive state directly from neural signals is critical for brain-computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method i...

Detection of glaucoma using retinal fundus images: A comprehensive review.

Mathematical biosciences and engineering : MBE
Content-based image analysis and computer vision techniques are used in various health-care systems to detect the diseases. The abnormalities in a human eye are detected through fundus images captured through a fundus camera. Among eye diseases, glau...

[The Application Value of Artificial Intelligence-based Filtering and Interpolated Image Reconstruction Algorithm in Abdominal Magnetic Resonance Image Denoising].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To compare the noise reduction performance of conventional filtering and artificial intelligence-based filtering and interpolation (AIFI) and to explore for optimal parameters of applying AIFI in the noise reduction of abdominal magnetic r...

[Noise Reduction Effect of Deep-learning-based Image Reconstruction Algorithms in Thin-section Chest CT].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To evaluate the noise reduction effect of deep learning-based reconstruction algorithms in thin-section chest CT images by analyzing images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (A...

[Digital Pathology: Current Status and Prospects of Clinical Application].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
In recent years, with the progress of image processing and network transmission technology, digital pathology (DP) is being more and more extensive applied in clinical practice, and new artificial-intelligence-assisted diagnosis technology based on d...

Neural network model assisted Fourier ptychography with Zernike aberration recovery and total variation constraint.

Journal of biomedical optics
SIGNIFICANCE: Fourier ptychography (FP) is a computational imaging approach that achieves high-resolution reconstruction. Inspired by neural networks, many deep-learning-based methods are proposed to solve FP problems. However, the performance of FP ...

Radiomics and deep learning in liver diseases.

Journal of gastroenterology and hepatology
Recently, radiomics and deep learning have gained attention as methods for computerized image analysis. Radiomics and deep learning can perform diagnostic or predictive tasks using high-dimensional image-derived features and have the potential to exp...

PET/CT for Brain Amyloid: A Feasibility Study for Scan Time Reduction by Deep Learning.

Clinical nuclear medicine
PURPOSE: This study was to develop a convolutional neural network (CNN) model with a residual learning framework to predict the full-time 18F-florbetaben (18F-FBB) PET/CT images from corresponding short-time scans.

Generative adversarial network based data augmentation to improve cervical cell classification model.

Mathematical biosciences and engineering : MBE
The survival rate of cervical cancer can be improved by the early screening. However, the screening is a heavy task for pathologists. Thus, automatic cervical cell classification model is proposed to assist pathologists in screening. In cervical cell...