Digital Breast Tomosynthesis

Sep 9th, 2016
Houston, TX
US
https://store.aheconline.com/index.php?route=product/product&path=59_78&product_id=2147
This course will investigate DBT technology, mammography technologist quality control testing, clinical applications, and more.
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F-18 PI-2620 average binding potential maps. Mean tracer binding (DVR) image from 165 older adults (A) and 13 young adults (B). Images are scaled from 1 to 1.8 for display purposes, but DVR values of less than 1 were frequently observed.
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Top eight incorrectly classified synthetic images (Most convincing fake images). Images A, B, C, D, E, F, G and H were the most infrequently correctly classified images at 24%, 43%, 59%, 64%, 69%, 71%, 71% and 73% respectively. All images are AI-generated. Images A, B and C are head CTs. Images D and E are chest CTs. Image F is a cardiac CT. Image G is a musculoskeletal MRI. Image H is a head MRI. Images are republished under a Creative Commons license (CC BY 4.0).
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F-18 PI-2620 average binding potential maps. Mean tracer binding (DVR) image from 165 older adults (A) and 13 young adults (B). Images are scaled from 1 to 1.8 for display purposes, but DVR values of less than 1 were frequently observed.
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Radiologists found it particularly difficult to distinguish between real and AI-generated CT and MR images.
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Top eight incorrectly classified synthetic images (Most convincing fake images). Images A, B, C, D, E, F, G and H were the most infrequently correctly classified images at 24%, 43%, 59%, 64%, 69%, 71%, 71% and 73% respectively. All images are AI-generated. Images A, B and C are head CTs. Images D and E are chest CTs. Image F is a cardiac CT. Image G is a musculoskeletal MRI. Image H is a head MRI. Images are republished under a Creative Commons license (CC BY 4.0).
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MRI showed comparable performance to DRE in prostate cancer staging without compromising patient outcomes.
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Incorrect AI suggestions influence reader performance on mammography
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The biggest impact on reader performance stemmed from false-negative AI suggestions.
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A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.
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Representative participant from each group shown. C-11 DTBZ non-displaceable binding potential (BPND) in voxels quantitated with simplified reference tissue model 2. Color scale indicates C-11 DTBZ BPND from 0 (black) to 3.5 (red), with reduced C-11 DTBZ BPND observed in the long COVID case compared to both healthy controls.
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