AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time.
Radiology. Artificial intelligence
May 1, 2024
Purpose To develop an artificial intelligence (AI) model for the diagnosis of breast cancer on digital breast tomosynthesis (DBT) images and to investigate whether it could improve diagnostic accuracy and reduce radiologist reading time. Materials an...
Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.
Radiology. Artificial intelligence
May 1, 2024
Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized m...
Dark-Blood Computed Tomography Angiography Combined With Deep Learning Reconstruction for Cervical Artery Wall Imaging in Takayasu Arteritis.
Korean journal of radiology
Apr 1, 2024
OBJECTIVE: To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize ...
Impact of AI Decision Support on Clinical Experts' Radiographic Interpretation of Adamantinomatous Craniopharyngioma.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
This research explores the integration of Artificial Intelligence (AI) into clinical decision-making in pediatric brain tumor care, specifically Adamantinomatous Craniopharyngioma (ACP). We present a user-centered design approach to introducing AI to...
A Multi-Task Learning Approach for Segmentation of Breast Arterial Calcifications in Screening Mammograms.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
Screening mammogram is a standard and cost-efficient imaging procedure to measure breast cancer risk among 45+ year old women. Quantifying breast arterial calcification (BAC) from screening mammograms is a non-invasive and cost-efficient approach to ...
Enhancing coronary artery plaque analysis via artificial intelligence-driven cardiovascular computed tomography.
Therapeutic advances in cardiovascular disease
Jan 1, 2024
Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality of cardiac structures and vasculature considered comparable to invasive coronary angiography for the evaluation of coronary artery disease (CAD) in several major cardio...
Advanced Lung Disease Detection: CBAM-Augmented, Lightweight EfficientNetB2 with Visual Insights.
Current medical imaging
Jan 1, 2024
INTRODUCTION: This paper presents a multichannel deep-learning method for detecting lung diseases using chest X-ray images. Using EfficientNetB0 through EfficientNetB7 pretrained models, the methodology offers improved performance in classifying COVI...
A Multi-label Artificial Intelligence Approach for Improving Breast Cancer Detection With Mammographic Image Analysis.
In vivo (Athens, Greece)
Jan 1, 2024
BACKGROUND/AIM: Breast cancer remains a major global health concern. This study aimed to develop a deep-learning-based artificial intelligence (AI) model that predicts the malignancy of mammographic lesions and reduces unnecessary biopsies in patient...
Can AI generate diagnostic reports for radiologist approval on CXR images? A multi-reader and multi-case observer performance study.
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: Accurately detecting a variety of lung abnormalities from heterogenous chest X-ray (CXR) images and writing radiology reports is often difficult and time-consuming.
PSAA-nnUNet: An Efficient Method for CT Carotid Artery Image Segmentation.
Advances in experimental medicine and biology
Jan 1, 2024
Carotid artery (CA) stenosis (CAS) constitutes a significant factor to ischaemic cerebrovascular events which exhibiting no overt symptoms in the early stages. Early detection of CAS can prevent ischaemic stroke and improve patient prognosis. In this...
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