FreeHemoSeg detects fetal GMH-IVH on T2-weighted MRI with high sensitivity and specificity and moderate segmentation accuracy using pseudo-image synthesis from normal scans, outperforming supervised and unsupervised baselines in internal and external validation.
Real-time automatic fetal brain extraction in fetal MRI by deep learning
2 Pith papers cite this work. Polarity classification is still indexing.
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Replacing the generic Stable Diffusion VAE with domain-specific MedVAE pretrained on 1.6M medical images improves diffusion-based SR PSNR by 2.91-3.29 dB on knee/brain MRI and chest X-ray, with gains in fine details and VAE quality predicting SR performance (R²=0.67).
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Annotation-free deep learning for detection and segmentation of fetal germinal matrix-intraventricular hemorrhage in brain MRI
FreeHemoSeg detects fetal GMH-IVH on T2-weighted MRI with high sensitivity and specificity and moderate segmentation accuracy using pseudo-image synthesis from normal scans, outperforming supervised and unsupervised baselines in internal and external validation.
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Domain-Specific Latent Representations Improve the Fidelity of Diffusion-Based Medical Image Super-Resolution
Replacing the generic Stable Diffusion VAE with domain-specific MedVAE pretrained on 1.6M medical images improves diffusion-based SR PSNR by 2.91-3.29 dB on knee/brain MRI and chest X-ray, with gains in fine details and VAE quality predicting SR performance (R²=0.67).