AIMC Topic: Image Processing, Computer-Assisted

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An extragradient and noise-tuning adaptive iterative network for diffusion MRI-based microstructural estimation.

Medical image analysis
Diffusion MRI (dMRI) is a powerful technique for investigating tissue microstructure properties. However, advanced dMRI models are typically complex and nonlinear, requiring a large number of acquisitions in the q-space. Deep learning techniques, spe...

Data-driven cultural background fusion for environmental art image classification: Technical support of the dual Kernel squeeze and excitation network.

PloS one
This study aims to explore a data-driven cultural background fusion method to improve the accuracy of environmental art image classification. A novel Dual Kernel Squeeze and Excitation Network (DKSE-Net) model is proposed for the complex cultural bac...

Unsupervised Machine Learning-Based Image Recognition of Raw Infrared Spectra: Toward Chemist-like Chemical Structural Classification and Beyond Numerical Data.

Journal of chemical information and modeling
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) spectral images, without relying on prior chemic...

An overview of utilizing artificial intelligence in localized prostate cancer imaging.

Expert review of medical devices
INTRODUCTION: Prostate cancer (PCa) is a leading cause of cancer-related deaths among men, and accurate diagnosis is critical for effective management. Multiparametric MRI (mpMRI) has become an essential tool in PCa diagnosis due to its superior spat...

The IBEX Knowledge-Base: A central resource for multiplexed imaging techniques.

PLoS biology
Multiplexed imaging is a powerful approach in spatial biology, although it is complex, expensive and labor-intensive. Here, we present the IBEX Knowledge-Base, a central resource for reagents, protocols and more, to enhance knowledge sharing, optimiz...

GatedSegDiff: a gated fusion diffusion model for skin lesion segmentation.

Medical & biological engineering & computing
Skin lesion segmentation is a vital process in skin disease diagnosis, crucial for maintaining diagnostic precision. Despite progress in existing image segmentation methods, challenges remain in handling the fuzzy boundaries of skin lesion areas. To ...

Stagger Network: Rethinking information loss in medical image segmentation with various-sized targets.

Neural networks : the official journal of the International Neural Network Society
Medical image segmentation presents the challenge of segmenting various-size targets, demanding the model to effectively capture both local and global information. Despite recent efforts using CNNs and ViTs to predict annotations of different scales,...

Deep learning by Vision Transformer to classify bacterial and fungal keratitis using different types of anterior segment images.

Computers in biology and medicine
PURPOSE: To develop three novel Vision Transformer (ViT) frameworks for the specific diagnosis of bacterial and fungal keratitis using different types of anterior segment images and compare their performances.

Asymmetric Convolution-based GAN Framework for Low-Dose CT Image Denoising.

Computers in biology and medicine
Noise reduction is essential to improve the diagnostic quality of low-dose CT (LDCT) images. In this regard, data-driven denoising methods based on generative adversarial networks (GAN) have shown promising results. However, custom designs with 2D co...

Complex wound analysis using AI.

Computers in biology and medicine
Impaired wound healing is a significant clinical challenge. Standard wound analysis approaches are macroscopic, with limited histological assessments that rely on visual inspection of haematoxylin and eosin (H&E)-stained sections of biopsies. The ana...