Artificial general intelligence for radiation oncology
The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As
prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can …
prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can …
Machine learning for medical image translation: A systematic review
Background: CT scans are often the first and only form of brain imaging that is performed to
inform treatment plans for neurological patients due to its time-and cost-effective nature …
inform treatment plans for neurological patients due to its time-and cost-effective nature …
Fully-automated, CT-only GTV contouring for palliative head and neck radiotherapy
Planning for palliative radiotherapy is performed without the advantage of MR or PET
imaging in many clinics. Here, we investigated CT-only GTV delineation for palliative …
imaging in many clinics. Here, we investigated CT-only GTV delineation for palliative …
Channel-wise attention enhanced and structural similarity constrained cycleGAN for effective synthetic CT generation from head and neck MRI images
C Gong, Y Huang, M Luo, S Cao, X Gong, S Ding… - Radiation …, 2024 - Springer
Background Magnetic resonance imaging (MRI) plays an increasingly important role in
radiotherapy, enhancing the accuracy of target and organs at risk delineation, but the …
radiotherapy, enhancing the accuracy of target and organs at risk delineation, but the …
Synthetic MRI Generation from CT Scans for Stroke Patients
CT scans are currently the most common imaging modality used for suspected stroke
patients due to their short acquisition time and wide availability. However, MRI offers …
patients due to their short acquisition time and wide availability. However, MRI offers …
vOARiability: Interobserver and intermodality variability analysis in OAR contouring from head and neck CT and MR images
Background Accurate and consistent contouring of organs‐at‐risk (OARs) from medical
images is a key step of radiotherapy (RT) cancer treatment planning. Most contouring …
images is a key step of radiotherapy (RT) cancer treatment planning. Most contouring …
Synthetic Megavoltage Cone Beam Computed Tomography Image Generation for Improved Contouring Accuracy of Cardiac Pacemakers
H Baroudi, X Chen, W Cao, MD El Basha, S Gay… - Journal of …, 2023 - mdpi.com
In this study, we aimed to enhance the contouring accuracy of cardiac pacemakers by
improving their visualization using deep learning models to predict MV CBCT images based …
improving their visualization using deep learning models to predict MV CBCT images based …
[HTML][HTML] Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic …
F Villegas, R Dal Bello, E Alvarez-Andres… - Radiotherapy and …, 2024 - Elsevier
Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI)
can serve as a substitute for planning CT in radiation therapy (RT), thereby removing …
can serve as a substitute for planning CT in radiation therapy (RT), thereby removing …
Medical Multi-Modal Image Transformation With Modality Code Awareness
In the planning phase of radiation therapy, positron emission tomography (PET) images are
frequently integrated with computed tomography (CT) and MRI to accurately delineate the …
frequently integrated with computed tomography (CT) and MRI to accurately delineate the …
A systematic literature review: deep learning techniques for synthetic medical image generation and their applications in radiotherapy
MK Sherwani, S Gopalakrishnan - Frontiers in Radiology, 2024 - frontiersin.org
The aim of this systematic review is to determine whether Deep Learning (DL) algorithms
can provide a clinically feasible alternative to classic algorithms for synthetic Computer …
can provide a clinically feasible alternative to classic algorithms for synthetic Computer …