AIMC Topic: Image Processing, Computer-Assisted

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Impact of F-FDG PET Intensity Normalization on Radiomic Features of Oropharyngeal Squamous Cell Carcinomas and Machine Learning-Generated Biomarkers.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
We aimed to investigate the effects of F-FDG PET voxel intensity normalization on radiomic features of oropharyngeal squamous cell carcinoma (OPSCC) and machine learning-generated radiomic biomarkers. We extracted 1,037 F-FDG PET radiomic features q...

Associating Knee Osteoarthritis Progression with Temporal-Regional Graph Convolutional Network Analysis on MR Images.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Artificial intelligence shows promise in assessing knee osteoarthritis (OA) progression on MR images, but faces challenges in accuracy and interpretability.

Automatic Skeleton Segmentation in CT Images Based on U-Net.

Journal of imaging informatics in medicine
Bone metastasis, emerging oncological therapies, and osteoporosis represent some of the distinct clinical contexts which can result in morphological alterations in bone structure. The visual assessment of these changes through anatomical images is co...

Cryo-EM images of phase-separated lipid bilayer vesicles analyzed with a machine-learning approach.

Biophysical journal
Lateral lipid heterogeneity (i.e., raft formation) in biomembranes plays a functional role in living cells. Three-component mixtures of low- and high-melting lipids plus cholesterol offer a simplified experimental model for raft domains in which a li...

Recognition of diabetic retinopathy and macular edema using deep learning.

Medical & biological engineering & computing
Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associated with diabetes and if left untreated, and they can lead to permanent blindness. Traditional methods for screening these conditions rely on manual ima...

Any region can be perceived equally and effectively on rotation pretext task using full rotation and weighted-region mixture.

Neural networks : the official journal of the International Neural Network Society
In recent years, self-supervised learning has emerged as a powerful approach to learning visual representations without requiring extensive manual annotation. One popular technique involves using rotation transformations of images, which provide a cl...

Learning shared template representation with augmented feature for multi-object pose estimation.

Neural networks : the official journal of the International Neural Network Society
Template matching pose estimation methods based on deep learning have made significant advancements via metric learning or reconstruction learning. Existing approaches primarily build distinct template representation libraries (codebooks) from render...

Automated Measurement and Three-Dimensional Fitting of Corneal Ulcerations and Erosions via AI-Based Image Analysis.

Current eye research
PURPOSE: Artificial intelligence (AI)-tools hold great potential to compensate for missing resources in health-care systems but often fail to be implemented in clinical routine. Intriguingly, no-code and low-code technologies allow clinicians to deve...

An Optimization Numerical Spiking Neural Membrane System with Adaptive Multi-Mutation Operators for Brain Tumor Segmentation.

International journal of neural systems
Magnetic Resonance Imaging (MRI) is an important diagnostic technique for brain tumors due to its ability to generate images without tissue damage or skull artifacts. Therefore, MRI images are widely used to achieve the segmentation of brain tumors. ...

Fine-grained food image classification and recipe extraction using a customized deep neural network and NLP.

Computers in biology and medicine
Global eating habits cause health issues leading people to mindful eating. This has directed attention to applying deep learning to food-related data. The proposed work develops a new framework integrating neural network and natural language processi...