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Image Interpretation, Computer-Assisted

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AI-based association analysis for medical imaging using latent-space geometric confounder correction.

Medical image analysis
This study addresses the challenges of confounding effects and interpretability in artificial-intelligence-based medical image analysis. Whereas existing literature often resolves confounding by removing confounder-related information from latent rep...

UGS-M3F: unified gated swin transformer with multi-feature fully fusion for retinal blood vessel segmentation.

BMC medical imaging
Automated segmentation of retinal blood vessels in fundus images plays a key role in providing ophthalmologists with critical insights for the non-invasive diagnosis of common eye diseases. Early and precise detection of these conditions is essential...

D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.

Journal of medical systems
Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (FFA), recognized as the gold standard for diagnosing DR, effectively reveals abnormalities in retina...

A Lightweight Deep Convolutional Neural Network Extracting Local and Global Contextual Features for the Classification of Alzheimer's Disease Using Structural MRI.

IEEE journal of biomedical and health informatics
Recent advancements in the classification of Alzheimer's disease have leveraged the automatic feature generation capability of convolutional neural networks (CNNs) using neuroimaging biomarkers. However, most of the existing CNN-based methods often d...

Syn-Net: A Synchronous Frequency-Perception Fusion Network for Breast Tumor Segmentation in Ultrasound Images.

IEEE journal of biomedical and health informatics
Accurate breast tumor segmentation in ultrasound images is a crucial step in medical diagnosis and locating the tumor region. However, segmentation faces numerous challenges due to the complexity of ultrasound images, similar intensity distributions,...

Deep Augmented Metric Learning Network for Prostate Cancer Classification in Ultrasound Images.

IEEE journal of biomedical and health informatics
Prostate cancer screening often relies on cost-intensive MRIs and invasive needle biopsies. Transrectal ultrasound imaging, as a more affordable and non-invasive alternative, faces the challenge of high inter-class similarity and intra-class variabil...

AI-Generated Synthetic STIR of the Lumbar Spine from T1 and T2 MRI Sequences Trained with Open-Source Algorithms.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Lumbar spine MRIs can be time consuming, stressful for patients, and costly to acquire. In this work, we train and evaluate open-source generative adversarial network (GAN) to create synthetic lumbar spine MRI STIR volumes fro...

Graph-based prototype inverse-projection for identifying cortical sulcal pattern abnormalities in congenital heart disease.

Medical image analysis
Examining the altered arrangement and patterning of sulcal folds offers insights into the mechanisms of neurodevelopmental differences in psychiatric and neurological disorders. Previous sulcal pattern analysis used spectral graph matching of sulcal ...

Integrating language into medical visual recognition and reasoning: A survey.

Medical image analysis
Vision-Language Models (VLMs) are regarded as efficient paradigms that build a bridge between visual perception and textual interpretation. For medical visual tasks, they can benefit from expert observation and physician knowledge extracted from text...

Comparative analysis of machine learning and deep learning algorithms for knee arthritis detection using YOLOv8 models.

Journal of X-ray science and technology
Knee arthritis is a prevalent joint condition that affects many people worldwide. Early detection and appropriate treatment are essential to slow the disease's progression and enhance patients' quality of life. In this study, various machine learning...