Daniel Hägg and Emil Styrke

Image Processing
Imaging vendors have options for image processing hardware
When developing new imaging systems, OEMs can choose from many types of computer hardware platforms. Platform selection in turn affects the type of image processing to be used, which then influences the radiologist's work when viewing medical images. Software architects from advanced visualization developer ContextVision offer some guidance.
March 26, 2015
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CT
CT reveals severe craniofacial, ocular trauma from pager blasts
Head injuries were nearly universal, affecting 93.2% of patients.
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.
Molecular Imaging
Tau PET tracer flags early Alzheimer risk in healthy older adults
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).
AI
Radiologists can identify three out of four AI-generated images
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Womens Imaging
Women's Imaging MinnieCast, Episode 13: Partial breast irradiation in the spotlight
Annual and cumulative FDA authorizations of AI/ML-enabled medical devices, 1995–2025.
AI
Radiology dominates thirty years of FDA AI device approvals
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CT reveals severe craniofacial, ocular trauma from pager blasts
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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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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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