Snowmass 2023: Hot Topics in Radiology: Advanced Applications and Artificial Intelligence

Feb 4th, 2023Feb 9th, 2023
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Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.
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PET/MRI reveals sex differences in patients with autism
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PET/MRI shows that young women with autism spectrum disorder have increased brain metabolism associated with translocator protein.
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A team at Michigan State University has developed an AI model designed to detect rib fractures in children under 3 years old.
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Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.
Tailored lung cancer screening model helps determine nodule follow-up
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CT-based deep learning identifies patients at further lung cancer risk
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Deep-learning model determines breast tumor staging
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A deep-learning model based on mammographic images can determine tumor staging and sentinel lymph node metastasis in breast cancer patients.
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Researchers explain the data preparation and structure of a proposed CNN-based deep learning model using mammography features to determine breast tumor staging. The image is available for use under a Creative Commons license: CC BY-NC-ND 4.0 DEED Attribution-NonCommercial-NoDerivs 4.0 International.
FAPI-PET shows promise in patients with lung cancer
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FAPI-PET imaging could emerge as a new tool for assessing patients with single pulmonary tumors, especially in those with negative results on other scans.
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F-18 FDG and Ga-68 FAPI-46 images of a 51-year-old woman with adenocarcinoma with lepidic growth pattern in right upper lobe. (A) Maximum-intensity-projection PET images. The lesion had F-18 FDG uptake below blood pool level but was strongly Ga-68 FAPI-46-positive. CT-guided biopsy led to pathologic diagnosis of adenocarcinoma, and the patient was treated by stereotactic body radiation therapy because of functional inoperability. Image courtesy of the Journal of Nuclear Medicine.
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