AutoPET
PulseAugur coverage of AutoPET — every cluster mentioning AutoPET across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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Unified Vision-Language Model Enhances PSMA PET/CT Analysis
Researchers have developed a novel unified vision-language model designed to enhance the analysis of PSMA PET/CT scans for prostate cancer management. This model integrates report generation, visual question answering, …
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AI model tackles PET/CT lesion segmentation challenge
Libo Zhang has developed a novel three-phase curriculum learning approach for interactive lesion segmentation in PET/CT scans, addressing the autoPETV Grand Challenge. This method utilizes a U-Net architecture with appr…
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LLMs and RL enhance PET/CT lesion segmentation in new RADIANT-PET framework
Researchers have developed RADIANT-PET, a novel framework for improving lesion segmentation in PET/CT scans for oncology. This system integrates a voxel-level segmentation model with a large language model (LLM) for les…
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New MuDuo framework uses dual-foundation models for semi-supervised PET/CT segmentation
Researchers have developed a novel semi-supervised learning framework called MuDuo for segmenting organs in PET/CT scans. This method leverages dual-foundation models, utilizing SAM-Med3D for CT imaging and SegAnyPET fo…
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AI framework MuDuo enhances PET/CT segmentation with dual-foundation models
Researchers have developed a novel mutual distillation framework called MuDuo for semi-supervised segmentation of PET/CT scans, addressing the high cost of manual annotation in oncology. This framework leverages dual-fo…
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Open PET/CT foundation model advances tumor segmentation with less data
Researchers have developed an open-source foundation model for segmenting tumors in FDG PET/CT scans, integrating anatomical and metabolic data from the outset. This model, trained on nearly 5,000 harmonized scans from …