International Society for Computed Tomography (ISCT) Symposium

Sep 18th, 2019Sep 20th, 2019
San Diego, CA
US
http://www.isct.org/
Phone:650-762-9003
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MR elastography effective for assessing liver stiffness in children
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MR elastography is an effective technique for noninvasive monitoring of liver stiffness -- a surrogate for fibrosis -- in children and young adults with autoimmune liver disease, researchers have reported.
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Recurrence-free breast cancer survival is less likely in women with high breast density compared with women with low density.
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Can ChatGPT ‘data mine’ patient reports for stroke registries?
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ChatGPT-4 appears useful for extracting details from reports on thrombectomy procedures in stroke patients, a labor-intensive and error-prone task currently performed by human readers.
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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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Radiologist consultation improves patients' LCS attitudes
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Consulting with a radiologist boosts patients' attitudes toward lung cancer screening (LCS) and their interest in quitting smoking, researchers have reported.
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AI proposed to help radiologists detect child abuse injuries
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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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ChatGPT-4 matches radiologists in flagging errors on reports
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ChatGPT-4 matched radiologists when tasked with detecting errors in imaging reports, with the study suggesting the technology may be useful for improving reporting accuracy.
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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.
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