PREF-XAI treats explanations as ranked alternatives and learns additive utility functions from limited user feedback to select and discover personalized rule explanations for black-box models.
DR-TTA: Dynamic and Robust Test-Time Adaptation Under Low-Quality Mri Conditions for Brain Tumor Segmentation
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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.
PBE-UNet adds scale-aware aggregation and progressive boundary expansion modules to U-Net and reports better segmentation performance than prior methods on four ultrasound datasets.
citing papers explorer
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PREF-XAI: Preference-Based Personalized Rule Explanations of Black-Box Machine Learning Models
PREF-XAI treats explanations as ranked alternatives and learns additive utility functions from limited user feedback to select and discover personalized rule explanations for black-box models.
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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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PBE-UNet: A light weight Progressive Boundary-Enhanced U-Net with Scale-Aware Aggregation for Ultrasound Image Segmentation
PBE-UNet adds scale-aware aggregation and progressive boundary expansion modules to U-Net and reports better segmentation performance than prior methods on four ultrasound datasets.