[HTML][HTML] Feasibility of artificial intelligence-driven interfractional monitoring of organ changes by mega-voltage computed tomography in intensity-modulated …

Y Lee, HJ Choi, H Kim, S Kim, MS Kim… - Radiation Oncology …, 2023 - ncbi.nlm.nih.gov
Purpose High-dose radiotherapy (RT) for localized prostate cancer requires careful
consideration of target position changes and adjacent organs-at-risk (OARs), such as the …

Patient-specific finetuning of deep learning models for adaptive radiotherapy in prostate CT

MS Elmahdy, T Ahuja… - 2020 IEEE 17th …, 2020 - ieeexplore.ieee.org
Contouring of the target volume and Organs-At-Risk (OARs) is a crucial step in radiotherapy
treatment planning. In an adaptive radiotherapy setting, updated contours need to be …

[HTML][HTML] Deep-learning-based segmentation using individual patient data on prostate cancer radiation therapy

S Jeong, W Cheon, S Kim, W Park, Y Han - PloS one, 2024 - journals.plos.org
Purpose Organ-at-risk segmentation is essential in adaptive radiotherapy (ART). Learning-
based automatic segmentation can reduce committed labor and accelerate the ART …

Joint registration and segmentation via multi-task learning for adaptive radiotherapy of prostate cancer

MS Elmahdy, L Beljaards, S Yousefi, H Sokooti… - IEEE …, 2021 - ieeexplore.ieee.org
Medical image registration and segmentation are two of the most frequent tasks in medical
image analysis. As these tasks are complementary and correlated, it would be beneficial to …

Patient‐specific transfer learning for auto‐segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi‐centric evaluation

M Kawula, I Hadi, L Nierer, M Vagni… - Medical …, 2023 - Wiley Online Library
Background Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear
accelerators (MR‐Linacs) can administer a tailored radiation dose at each treatment fraction …

[HTML][HTML] Cross-domain data augmentation for deep-learning-based male pelvic organ segmentation in cone beam CT

J Léger, E Brion, P Desbordes, C De Vleeschouwer… - Applied Sciences, 2020 - mdpi.com
For prostate cancer patients, large organ deformations occurring between radiotherapy
treatment sessions create uncertainty about the doses delivered to the tumor and …

[HTML][HTML] Automated contouring of CTV and OARs in planning CT scans using novel hybrid convolution-transformer networks for prostate cancer radiotherapy

N Arjmandi, S Nasseri, M Momennezhad… - Discover Oncology, 2024 - Springer
Purpose objective (s) Manual contouring of the prostate region in planning computed
tomography (CT) images is a challenging task due to factors such as low contrast in soft …

Deep learning based clinical target volumes contouring for prostate cancer: Easy and efficient application

F Wen, Z Chen, X Wang, M Dou, J Yang… - Journal of Applied …, 2024 - Wiley Online Library
Background Radiotherapy has been crucial in prostate cancer treatment. However, manual
segmentation is labor intensive and highly variable among radiation oncologists. In this …

Cascaded neural network segmentation pipeline for automated delineation of prostate and organs at risk in male pelvic CT

R Pemmaraju, DY Song, J Lee - Medical Imaging 2023: Image …, 2023 - spiedigitallibrary.org
Delineation of the prostate and nearby organs at risk (OARs) is a fundamental step in
prostate cancer radiation therapy planning. Such contouring is often done manually, which …

[HTML][HTML] Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy

MHF Savenije, M Maspero, GG Sikkes… - Radiation …, 2020 - Springer
Background Structure delineation is a necessary, yet time-consuming manual procedure in
radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and …