AIMC Topic: Radiotherapy Planning, Computer-Assisted
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Generation of deep learning based virtual non-contrast CT using dual-layer dual-energy CT and its application to planning CT for radiotherapy.
PloS one
Dec 30, 2024
This paper presents a novel approach for generating virtual non-contrast planning computed tomography (VNC-pCT) images from contrast-enhanced planning CT (CE-pCT) scans using a deep learning model. Unlike previous studies, which often lacked sufficie...
Development and external validation of a multi-task feature fusion network for CTV segmentation in cervical cancer radiotherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 27, 2024
BACKGROUND AND PURPOSE: Accurate segmentation of the clinical target volume (CTV) is essential to deliver an effective radiation dose to tumor tissues in cervical cancer radiotherapy. Also, although automated CTV segmentation can reduce oncologists' ...
Descriptive overview of AI applications in x-ray imaging and radiotherapy.
Journal of radiological protection : official journal of the Society for Radiological Protection
Dec 27, 2024
Artificial intelligence (AI) is transforming medical radiation applications by handling complex data, learning patterns, and making accurate predictions, leading to improved patient outcomes. This article examines the use of AI in optimising radiatio...
A unified deep-learning framework for enhanced patient-specific quality assurance of intensity-modulated radiation therapy plans.
Medical physics
Dec 24, 2024
BACKGROUND: Modern radiation therapy techniques, such as intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT), use complex fluence modulation strategies to achieve optimal patient dose distribution. Ensuring their ...
Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).
Physics in medicine and biology
Dec 24, 2024
To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-ris...
Performance of recurrent neural networks with Monte Carlo dropout for predicting pharmacokinetic parameters from dynamic contrast-enhanced magnetic resonance imaging data.
Journal of applied clinical medical physics
Dec 23, 2024
PURPOSE: To quantitatively evaluate the performance of two types of recurrent neural networks (RNNs), long short-term memory (LSTM) and gated recurrent units (GRU), using Monte Carlo dropout (MCD) to predict pharmacokinetic (PK) parameters from dynam...
Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.
Journal of applied clinical medical physics
Dec 20, 2024
PURPOSE: Cardiotoxicity is one of the major concerns in breast cancer treatment, significantly affecting patient outcomes. To improve the likelihood of favorable outcomes for breast cancer survivors, it is essential to carefully balance the potential...
Personalized deep learning auto-segmentation models for adaptive fractionated magnetic resonance-guided radiation therapy of the abdomen.
Medical physics
Dec 19, 2024
BACKGROUND: Manual contour corrections during fractionated magnetic resonance (MR)-guided radiotherapy (MRgRT) are time-consuming. Conventional population models for deep learning auto-segmentation might be suboptimal for MRgRT at MR-Linacs since the...
Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 19, 2024
BACKGROUND AND PURPOSE: Knowledge-based planning (KBP) can consistently and efficiently create high-quality Volumetric Arc Therapy (VMAT) plans for cervix cancer. This study describes the cross-validation of two KBP models on geographically distinct ...
Validating knowledge-based volumetric modulated arc therapy plans with a multi-institution model (broad model) using a complete open-loop dataset for prostate cancer.
Physical and engineering sciences in medicine
Dec 18, 2024
This study examined the characteristics of the broad model (KBP) through a complete open-loop evaluation of volumetric modulated arc therapy (VMAT) plans for prostate cancer in 30 patients at two institutions. KBP, trained using 561 prostate cancer V...
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