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 …
Inverse optimization: Theory and applications
Inverse optimization describes a process that is the “reverse” of traditional mathematical
optimization. Unlike traditional optimization, which seeks to compute optimal decisions given …
optimization. Unlike traditional optimization, which seeks to compute optimal decisions given …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer
Abstract Machine learning (ML) holds great promise for impacting healthcare delivery;
however, to date most methods are tested in 'simulated'environments that cannot …
however, to date most methods are tested in 'simulated'environments that cannot …
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 …
Artificial intelligence in radiotherapy
G Li, X Wu, X Ma - Seminars in Cancer Biology, 2022 - Elsevier
Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
(AI) has developed rapidly over the past few years. With the explosive growth of medical big …
OpenKBP: the open‐access knowledge‐based planning grand challenge and dataset
Purpose To advance fair and consistent comparisons of dose prediction methods for
knowledge‐based planning (KBP) in radiation therapy research. Methods We hosted …
knowledge‐based planning (KBP) in radiation therapy research. Methods We hosted …
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 …
A cascade 3D U‐Net for dose prediction in radiotherapy
Purpose Although large datasets are available, to learn a robust dose prediction model from
a limited dataset still remains challenging. This work employed cascaded deep learning …
a limited dataset still remains challenging. This work employed cascaded deep learning …