AIMC Topic: Image Processing, Computer-Assisted

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High-quality expert annotations enhance artificial intelligence model accuracy for osteosarcoma X-ray diagnosis.

Cancer science
Primary malignant bone tumors, such as osteosarcoma, significantly affect the pediatric and young adult populations, necessitating early diagnosis for effective treatment. This study developed a high-performance artificial intelligence (AI) model to ...

Assessment of multi-modal magnetic resonance imaging for glioma based on a deep learning reconstruction approach with the denoising method.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Deep learning reconstruction (DLR) with denoising has been reported as potentially improving the image quality of magnetic resonance imaging (MRI). Multi-modal MRI is a critical non-invasive method for tumor detection, surgery planning, a...

Robust mosquito species identification from diverse body and wing images using deep learning.

Parasites & vectors
Mosquito-borne diseases are a major global health threat. Traditional morphological or molecular methods for identifying mosquito species often require specialized expertise or expensive laboratory equipment. The use of convolutional neural networks ...

Three contrasts in 3 min: Rapid, high-resolution, and bone-selective UTE MRI for craniofacial imaging with automated deep-learning skull segmentation.

Magnetic resonance in medicine
PURPOSE: Ultrashort echo time (UTE) MRI can be a radiation-free alternative to CT for craniofacial imaging of pediatric patients. However, unlike CT, bone-specific MR imaging is limited by long scan times, relatively low spatial resolution, and a tim...

Predictive modeling of rice milling degree for three typical Chinese rice varieties using interpretative machine learning methods.

Journal of food science
Brown rice over-milling causes high economic and nutrient loss. The rice degree of milling (DOM) detection and prediction remain a challenge for moderate processing. In this study, a self-established grain image acquisition platform was built. Degree...

Shot-Noise Limited Nonlinear Optical Imaging Excited With GHz Femtosecond Pulses and Denoised by Deep-Learning.

Journal of biophotonics
Multiphoton fluorescence microscopy excited with femtosecond pulses at high repetition rates, particularly in the range of 100's MHz to GHz, offers an alternative solution to suppress photoinduced damage to biological samples, for example, photobleac...

Deep unfolding network with spatial alignment for multi-modal MRI reconstruction.

Medical image analysis
Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some modalities are limited by the long scanning time. To accelerate the whole acquisition process, MRI reconstruction of one modality from highly under-sam...

GlobalSR: Global context network for single image super-resolution via deformable convolution attention and fast Fourier convolution.

Neural networks : the official journal of the International Neural Network Society
Vision Transformer have achieved impressive performance in image super-resolution. However, they suffer from low inference speed mainly because of the quadratic complexity of multi-head self-attention (MHSA), which is the key to learning long-range d...

PSD-ELGAN: A pseudo self-distillation based CycleGAN with enhanced local adversarial interaction for single image dehazing.

Neural networks : the official journal of the International Neural Network Society
Compared to pixel-level content loss, domain-level style loss in CycleGAN-based dehazing algorithms just imposes relatively soft constraints on the intermediate translated images, resulting in struggling to accurately model haze-free features from re...

Deep learning for the harmonization of structural MRI scans: a survey.

Biomedical engineering online
Medical imaging datasets for research are frequently collected from multiple imaging centers using different scanners, protocols, and settings. These variations affect data consistency and compatibility across different sources. Image harmonization i...