Knowledge‐based radiation treatment planning: a data‐driven method survey
This paper surveys the data‐driven dose prediction methods investigated for knowledge‐
based planning (KBP) in the last decade. These methods were classified into two major …
based planning (KBP) in the last decade. These methods were classified into two major …
Advances in automated treatment planning
D Nguyen, MH Lin, D Sher, W Lu, X Jia… - Seminars in radiation …, 2022 - Elsevier
Treatment planning in radiation therapy has progressed enormously over the past several
decades. Such advancements came in the form of innovative hardware and algorithms …
decades. Such advancements came in the form of innovative hardware and algorithms …
Multi-constraint generative adversarial network for dose prediction in radiotherapy
B Zhan, J Xiao, C Cao, X Peng, C Zu, J Zhou… - Medical Image …, 2022 - Elsevier
Radiation therapy (RT) is regarded as the primary treatment for cancer in the clinic, aiming to
deliver an accurate dose to the planning target volume (PTV) while protecting the …
deliver an accurate dose to the planning target volume (PTV) while protecting the …
Radiation therapy dose prediction for left-sided breast cancers using two-dimensional and three-dimensional deep learning models
N Hedden, H Xu - Physica Medica, 2021 - Elsevier
Purpose: To develop a deep learning model capable of producing clinically acceptable dose
distributions for left-sided breast cancers for 3D-CRT while exploring the use of two …
distributions for left-sided breast cancers for 3D-CRT while exploring the use of two …
ResNet-SVM: Fusion based glioblastoma tumor segmentation and classification
Computerized segmentation of brain tumor based on magnetic resonance imaging (MRI)
data presents an important challenging act in computer vision. In image segmentation …
data presents an important challenging act in computer vision. In image segmentation …
Multi-stage framework with difficulty-aware learning for progressive dose prediction
Purpose: In this study, we are concerned with overcoming the limitation that most existing
methods learn the dose prediction distribution without taking into account hard-to-predict …
methods learn the dose prediction distribution without taking into account hard-to-predict …
DoseDiff: distance-aware diffusion model for dose prediction in radiotherapy
Treatment planning, which is a critical component of the radiotherapy workflow, is typically
carried out by a medical physicist in a time-consuming trial-and-error manner. Previous …
carried out by a medical physicist in a time-consuming trial-and-error manner. Previous …
Learning-based dose prediction for pancreatic stereotactic body radiation therapy using dual pyramid adversarial network
Abstract Treatment planning for pancreatic cancer stereotactic body radiation therapy
(SBRT) is very challenging owing to vast spatial variations and close proximity of many …
(SBRT) is very challenging owing to vast spatial variations and close proximity of many …
A survey on deep learning for precision oncology
Precision oncology, which ensures optimized cancer treatment tailored to the unique biology
of a patient's disease, has rapidly developed and is of great clinical importance. Deep …
of a patient's disease, has rapidly developed and is of great clinical importance. Deep …
[HTML][HTML] A generalization performance study on the boosting radiotherapy dose calculation engine based on super-resolution
Y Wang, Y Liu, Y Bai, Q Zhou, S Xu, X Pang - Zeitschrift für Medizinische …, 2024 - Elsevier
Purpose During the radiation treatment planning process, one of the time-consuming
procedures is the final high-resolution dose calculation, which obstacles the wide …
procedures is the final high-resolution dose calculation, which obstacles the wide …