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Radiographic Image Interpretation, Computer-Assisted

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Virtual Monochromatic Imaging of Half-Iodine-Load, Contrast-Enhanced Computed Tomography with Deep Learning Image Reconstruction in Patients with Renal Insufficiency: A Clinical Pilot Study.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: We retrospectively examined image quality (IQ) of thin-slice virtual monochromatic imaging (VMI) of half-iodine-load, abdominopelvic, contrast-enhanced CT (CECT) by dual-energy CT (DECT) with deep learning image reconstruction (DLIR).

Intraoperative stenosis detection in X-ray coronary angiography via temporal fusion and attention-based CNN.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND AND OBJECTIVE: Coronary artery disease (CAD), the leading cause of mortality, is caused by atherosclerotic plaque buildup in the arteries. The gold standard for the diagnosis of CAD is via X-ray coronary angiography (XCA) during percutaneo...

Enhanced tuberculosis detection using Vision Transformers and explainable AI with a Grad-CAM approach on chest X-rays.

BMC medical imaging
Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a leading global health challenge, especially in low-resource settings. Accurate diagnosis from chest X-rays is critical yet challenging due to subtle manifestations of TB, particularly...

Segment Like A Doctor: Learning reliable clinical thinking and experience for pancreas and pancreatic cancer segmentation.

Medical image analysis
Pancreatic cancer is a lethal invasive tumor with one of the worst prognosis. Accurate and reliable segmentation for pancreas and pancreatic cancer on computerized tomography (CT) images is vital in clinical diagnosis and treatment. Although certain ...

Human-AI Interaction in the ScreenTrustCAD Trial: Recall Proportion and Positive Predictive Value Related to Screening Mammograms Flagged by AI CAD versus a Human Reader.

Radiology
Background The ScreenTrustCAD trial was a prospective study that evaluated the cancer detection rates for combinations of artificial intelligence (AI) computer-aided detection (CAD) and two radiologists. The results raised concerns about the tendency...

Value of Using a Generative AI Model in Chest Radiography Reporting: A Reader Study.

Radiology
Background Multimodal generative artificial intelligence (AI) technologies can produce preliminary radiology reports, and validation with reader studies is crucial for understanding the clinical value of these technologies. Purpose To assess the clin...

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance.

The international journal of cardiovascular imaging
Invasive coronary physiology is underused and carries risks/costs. Artificial Intelligence (AI) might enable non-invasive physiology from invasive coronary angiography (CAG), possibly outperforming humans, but has seldom been explored, especially for...

External Testing of a Commercial AI Algorithm for Breast Cancer Detection at Screening Mammography.

Radiology. Artificial intelligence
Purpose To test a commercial artificial intelligence (AI) system for breast cancer detection at the BC Cancer Breast Screening Program. Materials and Methods In this retrospective study of 136 700 female individuals (mean age, 58.8 years ± 9.4 [SD]; ...