Jan Makela

Practice Management
Unlocking the potential of imaging in Alzheimer’s disease care
GE HealthCare
In the U.S., Alzheimer's disease cases are projected to rise to nearly 13 million, making effective imaging even more crucial for early identification and effective monitoring and treatment of the condition.
January 19, 2024
Brain Puzzle Night Sky
AI
New imaging systems driven by AI will reduce radiologist burnout
Many radiologists are facing a tipping point when it comes to the overwhelming volume of imaging studies they face every day. Will new technologies such as artificial intelligence help? Jan Makela of GE Healthcare offers a perspective.
December 20, 2021
2019 11 14 18 07 2163 Computer Doctor Future 400
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Pediatric Imaging
Practice Management
Patient-friendly radiology reports improve family comprehension
Terminology in radiology reports can be difficult for patients and families to comprehend.
Ct Scanner 400
CT
Early CTA leads to improved stroke outcomes for patients with BCVI
Liver Cancer 400
Interventional
Most histotripsy procedures used for metastatic disease treatment
Radiologist Computer Screen X Ray
Administration
Imaging turnaround times continued to climb in 2024
(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.
Breast
DBT-based foundational model classifies breast density
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Patient-friendly radiology reports improve family comprehension
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Early CTA leads to improved stroke outcomes for patients with BCVI
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Most histotripsy procedures used for metastatic disease treatment
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The largest increases were found in ultrasound and x-ray.
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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.
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(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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By AuntMinnie.com staff writers
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LLMs could potentially help address multiple persistent pain points in radiology workflow.
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Notably, the TESLA trial used a noncontrast CT (NCCT)-alone patient selection protocol.
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Surveillance imaging doesn't improve pancreatic cancer survival
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Study authors are calling for better strategies for early detection and intervention for pancreatic cysts that become malignant.
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Incorporating patient preferences into communication may improve understanding and follow-up in addressing incidental findings.
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