AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Enhancing cancer prediction in challenging screen-detected incident lung nodules using time-series deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Lung cancer screening (LCS) using annual computed tomography (CT) scanning significantly reduces mortality by detecting cancerous lung nodules at an earlier stage. Deep learning algorithms can improve nodule malignancy risk stratification. However, t...

Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.

European radiology experimental
BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR).

Impact of intelligent virtual and AI-based automated collimation functionalities on the efficiency of radiographic acquisitions.

Radiography (London, England : 1995)
INTRODUCTION: Intelligent virtual and AI-based collimation functionalities have the potential to enable an efficient workflow for radiographers, but the specific impact on clinical routines is still unknown. This study analyzes primarily the influenc...

Performance of AI to exclude normal chest radiographs to reduce radiologists' workload.

European radiology
INTRODUCTION: This study investigates the performance of a commercially available artificial intelligence (AI) system to identify normal chest radiographs and its potential to reduce radiologist workload.

A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer.

La Radiologia medica
OBJECTIVE: To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal g...

BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning.

BMC medical informatics and decision making
BACKGROUND: Chest X-ray imaging based abnormality localization, essential in diagnosing various diseases, faces significant clinical challenges due to complex interpretations and the growing workload of radiologists. While recent advances in deep lea...

New Diagnostic Tools for Pulmonary Embolism Detection.

Methodist DeBakey cardiovascular journal
The presentation of pulmonary embolism (PE) varies from asymptomatic to life-threatening, and management involves multiple specialists. Timely diagnosis of PE is based on clinical presentation, D-dimer testing, and computed tomography pulmonary angio...