Artificial intelligence and machine learning for medical imaging: A technology review
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …
of disruptive technical advances and impressive experimental results, notably in the field of …
An overview of artificial intelligence in oncology
Cancer is associated with significant morbimortality globally. Advances in screening,
diagnosis, management and survivorship were substantial in the last decades, however …
diagnosis, management and survivorship were substantial in the last decades, however …
Multi-constraint generative adversarial network for dose prediction in radiotherapy
B Zhan, J **ao, 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 …
TransDose: Transformer-based radiotherapy dose prediction from CT images guided by super-pixel-level GCN classification
Radiotherapy is a mainstay treatment for cancer in clinic. An excellent radiotherapy
treatment plan is always based on a high-quality dose distribution map which is produced by …
treatment plan is always based on a high-quality dose distribution map which is produced by …
A transformer-embedded multi-task model for dose distribution prediction
Radiation therapy is a fundamental cancer treatment in the clinic. However, to satisfy the
clinical requirements, radiologists have to iteratively adjust the radiotherapy plan based on …
clinical requirements, radiologists have to iteratively adjust the radiotherapy plan based on …
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 …
Explainable attention guided adversarial deep network for 3D radiotherapy dose distribution prediction
Radiotherapy is the mainstay treatment for most patients with cancer. During radiotherapy
planning, it is essential to generate a clinically acceptable dose distribution map. In practice …
planning, it is essential to generate a clinically acceptable dose distribution map. In practice …
[HTML][HTML] Personalized brachytherapy dose reconstruction using deep learning
Background and purpose Accurate calculation of the absorbed dose delivered to the tumor
and normal tissues improves treatment gain factor, which is the major advantage of …
and normal tissues improves treatment gain factor, which is the major advantage of …
Deep learning dose prediction for IMRT of esophageal cancer: the effect of data quality and quantity on model performance
Purpose To investigate the effect of data quality and quantity on the performance of deep
learning (DL) models, for dose prediction of intensity-modulated radiotherapy (IMRT) of …
learning (DL) models, for dose prediction of intensity-modulated radiotherapy (IMRT) of …
[HTML][HTML] Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging
Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …
cancer based on imaging data continue to pose significant challenges. These include inter …