FedSynthCT-Brain: A Federated Learning Framework for Multi-Institutional Brain MRI-to-CT Synthesis
CB Raggio, MK Zabaleta, N Skupien, O Blanck… - ar** fields traditionally reliant on human cognitive abilities. This transition, driven …
Balancing data consistency and diversity: Preprocessing and online data augmentation for multi-center deep learning-based MR-to-CT synthesis
Abstract Background and Purpose: Deep learning (DL)-based MR-to-CT translation is
crucial for MRI-only radiotherapy, enabling dose planning directly from MRI and bypassing …
crucial for MRI-only radiotherapy, enabling dose planning directly from MRI and bypassing …
Adapted nnU-Net: A Robust Baseline for Cross-Modality Synthesis and Medical Image Inpainting
In medical image synthesis, the development of robust and reliable baseline methods is
crucial due to the complexity and variability of existing techniques. Despite advances with …
crucial due to the complexity and variability of existing techniques. Despite advances with …
[HTML][HTML] Indirect deformable image registration using synthetic image generated by unsupervised deep learning
Background and purpose 3D image registration is now common in many medical domains.
Multimodal registration implies the use of different imaging modalities, which results in lower …
Multimodal registration implies the use of different imaging modalities, which results in lower …
Generating synthetic CT images from unpaired head and neck CBCT images and validating the importance of detailed nasal cavity acquisition through simulations
S Ryu, JH Kim, YJ Choi, JS Lee - Computers in Biology and Medicine, 2025 - Elsevier
Background and objective Computed tomography (CT) of the head and neck is crucial for
diagnosing internal structures. The demand for substituting traditional CT with cone beam …
diagnosing internal structures. The demand for substituting traditional CT with cone beam …
[HTML][HTML] Abdominal synthetic CT generation for MR-only radiotherapy using structure-conserving loss and transformer-based cycle-GAN
Purpose Recent deep-learning based synthetic computed tomography (sCT) generation
using magnetic resonance (MR) images have shown promising results. However …
using magnetic resonance (MR) images have shown promising results. However …
[HTML][HTML] Modeling dose uncertainty in cone-beam computed tomography: Predictive approach for deep learning-based synthetic computed tomography generation
Background and purpose: Cone-beam computed tomography (CBCT) is essential in image-
guided radiotherapy (RT) for patient positioning and daily dose calculation. However, CT …
guided radiotherapy (RT) for patient positioning and daily dose calculation. However, CT …