BACKGROUND: 3D neural network dose predictions are useful for automating brachytherapy (BT) treatment planning for cervical cancer. Cervical BT can be delivered with numerous applicators, which necessitates developing models that generalize to multip...
To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model.Two 3D UNets were established to predict ph...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
May 29, 2024
PURPOSE: To propose a novel deep-learning based dosimetry method that allows quick and accurate estimation of organ doses for individual patients, using only their computed tomography (CT) images as input.
AJR. American journal of roentgenology
May 29, 2024
Coronary artery calcification (CAC) on lung cancer screening low-dose chest CT (LDCT) is a cardiovascular risk marker. South Korea was the first Asian country to initiate a national LDCT lung cancer screening program, although CAC-related outcomes a...
BACKGROUND: Neck computed tomography (NCT) is essential for diagnosing suspected neck tumors and abscesses, but radiation exposure can be an issue. In conventional reconstruction techniques, limiting radiation dose comes at the cost of diminished dia...
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).
OBJECTIVES: To investigate the feasibility of low-radiation dose and low iodinated contrast medium (ICM) dose protocol combining low-tube voltage and deep-learning reconstruction (DLR) algorithm in thin-slice abdominal CT.
Biomedical physics & engineering express
May 15, 2024
. To improve breast cancer risk prediction for young women, we have developed deep learning methods to estimate mammographic density from low dose mammograms taken at approximately 1/10th of the usual dose. We investigate the quality and reliability ...
. Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-prin...
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