arXiv Machine Learning
1d ago
Zero-Shot Adaptation of Medical Vision Foundation Models for High-Frequency Micro-Ultrasound Prostate Segmentation
arXiv:2608. 14796v1 Announce Type: cross Abstract: Prostate cancer claims a life every 80 seconds.
Learning Where to Look: A Reinforcement Learning Framework for Robust Micro-Ultrasound Prostate Cancer Detection
arXiv:2606. 30951v1 Announce Type: cross Abstract: Micro-ultrasound ($\mu$US) is a new, emerging, and promising imaging modality for prostate cancer (PCa) detection, but accurate identification of suspicious tissue remains highly dependent on clinical experience, leading to substantial inter-observer variability.
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Externally Validated Breast Ultrasound Segmentation via Multi-task Learning with BI-RADS-Consistent Morphological Priors
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CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement
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Compass: Prostate Cancer Detection Needs Multi-View Context
arXiv:2607. 06919v1 Announce Type: cross Abstract: Artificial intelligence (AI) analysis of micro-ultrasound ($\mu$US) has shown promise for prostate cancer (PCa) detection.
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BiLoG-Net: A Bi-Context Location-Guided Network for Breast Mass Segmentation and Malignancy Classification in Mammography
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RL-ACRGNet: Reinforcement Learning-Based Chest Radiology Report Generation Network
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RADIANT-PET: Reasoning-Augmented PET/CT Lesion Segmentation with Large Language Models and Reinforcement Learning
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Spatially Grounded Concept Bottleneck Models for Trustworthy Breast Ultrasound Diagnosis
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MIRAGE: Multi-scale Lesion-Informed Representation with Auxiliary Guidance for MRI Contrast Enhancement
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Sequential Attention-based Sampling for Histopathological Analysis
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TRACE-PCa: Predicting Prostate Cancer Progression from Longitudinal MRI During Active Surveillance
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