AIMC Topic: Radiation Dosage
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Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT.
Artificial intelligence in medicine
Dec 16, 2024
In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predi...
Feasibility of Sub-milliSievert Low-dose Computed Tomography with Deep Learning Image Reconstruction in Evaluating Pulmonary Subsolid Nodules: A Prospective Intra-individual Comparison Study.
Academic radiology
Dec 13, 2024
RATIONALE AND OBJECTIVES: To comprehensively assess the feasibility of low-dose computed tomography (LDCT) using deep learning image reconstruction (DLIR) for evaluating pulmonary subsolid nodules, which are challenging due to their susceptibility to...
Federated learning for enhanced dose-volume parameter prediction with decentralized data.
Medical physics
Dec 6, 2024
BACKGROUND: The widespread adoption of knowledge-based planning in radiation oncology clinics is hindered by the lack of data and the difficulty associated with sharing medical data.
Deep learning based super-resolution for CBCT dose reduction in radiotherapy.
Medical physics
Dec 3, 2024
BACKGROUND: Cone-beam computed tomography (CBCT) is a crucial daily imaging modality in image-guided and adaptive radiotherapy. However, the use of ionizing radiation in CBCT imaging increases the risk of secondary cancers, which is particularly conc...
Low dose threshold for measuring cardiac functional metrics using four-dimensional CT with deep learning.
Journal of applied clinical medical physics
Dec 3, 2024
BACKGROUND: Four-dimensional CT is increasingly used for functional cardiac imaging, including prognosis for conditions such as heart failure and post myocardial infarction. However, radiation dose from an acquisition spanning the full cardiac cycle ...
External validation of the performance of commercially available deep-learning-based lung nodule detection on low-dose CT images for lung cancer screening in Japan.
Japanese journal of radiology
Nov 30, 2024
PURPOSE: Artificial intelligence (AI) algorithms for lung nodule detection have been developed to assist radiologists. However, external validation of its performance on low-dose CT (LDCT) images is insufficient. We examined the performance of the co...
Radiation Dosage
Early Detection of Cancer
Radiographic Image Interpretation, Computer-Assisted
Japan
Male
Female
Humans
Aged
Middle Aged
Retrospective Studies
Tomography, X-Ray Computed
Aged, 80 and over
Deep Learning
Lung
Sensitivity and Specificity
Lung Neoplasms
Multiple Pulmonary Nodules
Solitary Pulmonary Nodule
Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.
European radiology
Nov 29, 2024
PURPOSE: The purpose of this study is to estimate the extent to which the implementation of deep learning reconstruction (DLR) may reduce the risk of radiation-induced cancer from CT examinations, utilizing real-world clinical data.
3D full-dose brain-PET volume recovery from low-dose data through deep learning: quantitative assessment and clinical evaluation.
European radiology
Nov 28, 2024
OBJECTIVES: Low-dose (LD) PET imaging would lead to reduced image quality and diagnostic efficacy. We propose a deep learning (DL) method to reduce radiotracer dosage for PET studies while maintaining diagnostic quality.
A deep learning method for the recovery of standard-dose imaging quality from ultra-low-dose PET on wavelet domain.
European journal of nuclear medicine and molecular imaging
Nov 25, 2024
PURPOSE: Recent development in positron emission tomography (PET) dramatically increased the effective sensitivity by increasing the geometric coverage leading to total-body PET imaging. This encouraging breakthrough brings the hope of ultra-low dose...
The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence.
Archivos de bronconeumologia
Nov 22, 2024
In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and explore the contributions of artificial intelligence (AI), in overcoming them. We focus on evaluating th...
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