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 …
A high-performance method of deep learning for prostate MR-only radiotherapy planning using an optimized Pix2Pix architecture
S Tahri, A Barateau, C Cadin, H Chourak, S Ribault… - Physica Medica, 2022 - Elsevier
Purpose The first aim was to generate and compare synthetic-CT (sCT) images using a
conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate …
conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate …
Joint brain tumor segmentation from multi MR sequences through a deep convolutional neural network
Brain tumor segmentation is highly contributive in diagnosing and treatment planning. The
manual brain tumor delineation is a time-consuming and tedious task and varies depending …
manual brain tumor delineation is a time-consuming and tedious task and varies depending …
Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods
H Chourak, A Barateau, S Tahri, C Cadin… - Frontiers in …, 2022 - frontiersin.org
The quality assurance of synthetic CT (sCT) is crucial for safe clinical transfer to an MRI-only
radiotherapy planning workflow. The aim of this work is to propose a population-based …
radiotherapy planning workflow. The aim of this work is to propose a population-based …
Attention-based deep learning segmentation: Application to brain tumor delineation
R Karimzadeh, E Fatemizadeh… - 2021 28th National and …, 2021 - ieeexplore.ieee.org
Brain tumor segmentation is an important step in brain cancer diagnosis and treatment.
Manual segmentation is highly time consuming and tedious. To address these issues deep …
Manual segmentation is highly time consuming and tedious. To address these issues deep …
Artificial intelligence for detecting temporomandibular joint osteoarthritis using radiographic image data: A systematic review and meta-analysis of diagnostic test …
L Xu, J Chen, K Qiu, F Yang, W Wu - Plos one, 2023 - journals.plos.org
In this review, we assessed the diagnostic efficiency of artificial intelligence (AI) models in
detecting temporomandibular joint osteoarthritis (TMJOA) using radiographic imaging data …
detecting temporomandibular joint osteoarthritis (TMJOA) using radiographic imaging data …
Deep learning synthesis of cone-beam computed tomography from zero echo time magnetic resonance imaging
Cone-beam computed tomography (CBCT) produces high-resolution of hard tissue even in
small voxel size, but the process is associated with radiation exposure and poor soft tissue …
small voxel size, but the process is associated with radiation exposure and poor soft tissue …
MRI‐guided attenuation correction in torso PET/MRI: Assessment of segmentation‐, atlas‐, and deep learning‐based approaches in the presence of outliers
Purpose We compare the performance of three commonly used MRI‐guided attenuation
correction approaches in torso PET/MRI, namely segmentation‐, atlas‐, and deep learning …
correction approaches in torso PET/MRI, namely segmentation‐, atlas‐, and deep learning …
Comparison of four synthetic CT generators for brain and prostate MR-only workflow in radiotherapy
D Autret, C Guillerminet, A Roussel… - Radiation …, 2023 - Springer
Background The interest in MR-only workflows is growing with the introduction of artificial
intelligence in the synthetic CT generators converting MR images into CT images. The aim …
intelligence in the synthetic CT generators converting MR images into CT images. The aim …