AIMC Topic: Image Interpretation, Computer-Assisted

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Automatic cerebral microbleeds detection from MR images via multi-channel and multi-scale CNNs.

Computers in biology and medicine
BACKGROUND: Computer-aided detection (CAD) systems have been widely used to assist medical professionals in interpreting medical images, aiding in the detection of potential diseases. Despite their usefulness, CAD systems cannot yet fully replace doc...

Enhanced ISUP grade prediction in prostate cancer using multi-center radiomics data.

Abdominal radiology (New York)
BACKGROUND: To explore the predictive value of radiomics features extracted from anatomical ROIs in differentiating the International Society of Urological Pathology (ISUP) grading in prostate cancer patients.

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...