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Radiologists' trust of AI is critical for hospital adoption
It wasn't that long ago that artificial intelligence (AI) proponents perpetuated the notion of AI marketplaces, believing that they provide a more straightforward way to purchase the technology that would soon lead to widespread adoption in hospital systems. But acquiring AI algorithms has never been the most challenging aspect of AI adoption.
January 25, 2022
2022 01 25 18 07 6201 Batman Sinan
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CT
CT 5-star quality rating system supports optimization
The rating framework demonstrated robust reproducibility, with three-reader concordance reaching up to 93% in highly standardized centers.
Radiological Report 400
Ultrasound
READ-DVT model performs well in finding DVT from ultrasound reports
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Bone scan testing has fallen 35% among Medicare beneficiaries
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MRI
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CT 5-star quality rating system supports optimization
By Will Morton
The rating framework demonstrated robust reproducibility, with three-reader concordance reaching up to 93% in highly standardized centers.
August 7, 2026
Radiation Symbol
READ-DVT model performs well in finding DVT from ultrasound reports
By Amerigo Allegretto
The AI model accurately identified the presence or absence of deep vein thrombosis on unstructured ultrasound reports.
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Radiological Report 400
Bone scan testing has fallen 35% among Medicare beneficiaries
By Will Morton
Declines in testing were greatest among certain underserved groups.
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Dexa
MRI-based models may predict atypical brain development in children
By Amerigo Allegretto
The models could provide a framework for identifying which adolescents are at higher risk of developing psychiatric conditions.
August 7, 2026
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Ultrasound MinnieCast, Episode 14: Weathering the sonographer shortage
By Amerigo Allegretto
SDMS President Aubrey Rybyinski discusses how clinics can address sonographer vacancies.
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Avoiding the ED cuts urgent CT turnaround time by half
By Will Morton
This is the first reported pilot of an expedited outpatient direct-to-CT imaging program designed to promote ED avoidance.
August 6, 2026
Emergency2
VLMs miss most lung nodules on chest x-rays
By Will Morton
Findings indicate poor performance of six VLMs for lung nodule detection on chest x-rays.
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Chatgpt2
Patient-friendly radiology reports improve family comprehension
By Will Morton
Terminology in radiology reports can be difficult for patients and families to comprehend.
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Pediatric Imaging
Early CTA leads to improved stroke outcomes for patients with BCVI
By Amerigo Allegretto
Early CTA is linked to reduced stroke, decreased complications, and reduced intensive care unit length of stay.
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Most histotripsy procedures used for metastatic disease treatment
By Amerigo Allegretto
Trends suggest that histotripsy has low rates of procedure-related complications and is mostly performed in outpatient settings.
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Imaging turnaround times continued to climb in 2024
By Erik L. Ridley
The largest increases were found in ultrasound and x-ray.
August 4, 2026
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DBT-based foundational model classifies breast density
By Amerigo Allegretto
DBT-DINO showed strong performance in classifying breast density from DBT images.
August 4, 2026
(A) Free-response receiver operating characteristic (FROC) curve for DBT-DINO and DINOv2 (Meta AI) on the detection task. DINOv2 achieved higher sensitivity than DBT-DINO across most false-positive thresholds. (B) Detection rates of DBT-DINO and DINOv2 for lesions that were ultimately found to be benign (n = 70) and lesions that were found to be cancerous (n = 66). Error bars represent 95% CIs estimated via patient-level bootstrapping with 1000 repetitions. Both models showed similar detection rates for cancerous lesions, whereas DINOv2 detected more benign lesions than DBT-DINO. (C) Example bounding box predictions for DBT-DINO and DINOv2 on the detection test set. Each image is a single two-dimensional section from a three-dimensional digital breast tomosynthesis volume; the first column shows a mediolateral oblique view, and the second and third columns show craniocaudal views. Both models struggled to detect very small lesions, such as the 3-mm-diameter lesion shown in the first column. FP = false positive.
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