Recent applications of artificial intelligence in radiotherapy: where we are and beyond

M Santoro, S Strolin, G Paolani, G Della Gala… - Applied Sciences, 2022 - mdpi.com
Featured Application Computational models based on artificial intelligence (AI) variants
have been developed and applied successfully in many areas, both inside and outside of …

Review and recommendations on deformable image registration uncertainties for radiotherapy applications

L Nenoff, F Amstutz, M Murr… - Physics in Medicine …, 2023 - iopscience.iop.org
Deformable image registration (DIR) is a versatile tool used in many applications in
radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment …

Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer

SH Ahn, AU Yeo, KH Kim, C Kim, Y Goh, S Cho… - Radiation …, 2019 - Springer
Background Accurate and standardized descriptions of organs at risk (OARs) are essential
in radiation therapy for treatment planning and evaluation. Traditionally, physicians have …

Artificial intelligence for image registration in radiation oncology

J Teuwen, ZAR Gouw, JJ Sonke - Seminars in Radiation Oncology, 2022 - Elsevier
Automatic image registration plays an important role in many aspects of the radiation
oncology workflow ranging from treatment simulation, image guided and adaptive …

Rigid and deformable image registration for radiation therapy: a self-study evaluation guide for NRG oncology clinical trial participation

Y Rong, M Rosu-Bubulac, SH Benedict, Y Cui… - Practical radiation …, 2021 - Elsevier
Purpose The registration of multiple imaging studies to radiation therapy computed
tomography simulation, including magnetic resonance imaging, positron emission …

[HTML][HTML] Patient specific deep learning based segmentation for magnetic resonance guided prostate radiotherapy

S Fransson, D Tilly, R Strand - Physics and Imaging in Radiation Oncology, 2022 - Elsevier
Abstract Background and Purpose Treatments on combined Magnetic Resonance (MR)
scanners and Linear Accelerators (Linacs) for radiotherapy, called MR-Linacs, often require …

Cone-beam computed tomography-based delta-radiomics for early response assessment in radiotherapy for locally advanced lung cancer

L Shi, Y Rong, M Daly, B Dyer, S Benedict… - Physics in Medicine …, 2020 - iopscience.iop.org
Cone-beam computed tomography (CBCT) images acquired during radiotherapy may allow
early response assessment. Previous studies have reported inconsistent findings on an …

[HTML][HTML] A review of medical image registration for different modalities

F Darzi, T Bocklitz - Bioengineering, 2024 - mdpi.com
Medical image registration has become pivotal in recent years with the integration of various
imaging modalities like X-ray, ultrasound, MRI, and CT scans, enabling comprehensive …

Clinical evaluation of commercial atlas-based auto-segmentation in the head and neck region

H Lee, E Lee, N Kim, J Kim, K Park, H Lee… - Frontiers in …, 2019 - frontiersin.org
Background: While atlas segmentation (AS) has proven to be a time-saving and promising
method for radiation therapy contouring, optimal methods for its use have not been well …

Atlas-based auto-segmentation for postoperative radiotherapy planning in endometrial and cervical cancers

N Kim, JS Chang, YB Kim, JS Kim - Radiation Oncology, 2020 - Springer
Background Since intensity-modulated radiation therapy (IMRT) has become popular for the
treatment of gynecologic cancers, the contouring process has become more critical. This …