Artificial intelligence for brain diseases: A systematic review
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …
analyzing complex medical data and extracting meaningful relationships in datasets, for …
Auto‐segmentation of organs at risk for head and neck radiotherapy planning: from atlas‐based to deep learning methods
T Vrtovec, D Močnik, P Strojan, F Pernuš… - Medical …, 2020 - Wiley Online Library
Radiotherapy (RT) is one of the basic treatment modalities for cancer of the head and neck
(H&N), which requires a precise spatial description of the target volumes and organs at risk …
(H&N), which requires a precise spatial description of the target volumes and organs at risk …
Automatic detection and segmentation of brain metastases on multimodal MR images with a deep convolutional neural network
Stereotactic treatments are today the reference techniques for the irradiation of brain
metastases in radiotherapy. The dose per fraction is very high, and delivered in small …
metastases in radiotherapy. The dose per fraction is very high, and delivered in small …
Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-
beam computed tomography (CBCT) imaging, which is routinely acquired for patient …
beam computed tomography (CBCT) imaging, which is routinely acquired for patient …
Interleaved 3D‐CNN s for joint segmentation of small‐volume structures in head and neck CT images
Purpose Accurate 3D image segmentation is a crucial step in radiation therapy planning of
head and neck tumors. These segmentation results are currently obtained by manual …
head and neck tumors. These segmentation results are currently obtained by manual …
Deep convolution neural network (DCNN) multiplane approach to synthetic CT generation from MR images—application in brain proton therapy
Purpose The first aim of this work is to present a novel deep convolution neural network
(DCNN) multiplane approach and compare it to single-plane prediction of synthetic …
(DCNN) multiplane approach and compare it to single-plane prediction of synthetic …
Automatic segmentation of mandible from conventional methods to deep learning—a review
B Qiu, H van der Wel, J Kraeima, HH Glas… - Journal of personalized …, 2021 - mdpi.com
Medical imaging techniques, such as (cone beam) computed tomography and magnetic
resonance imaging, have proven to be a valuable component for oral and maxillofacial …
resonance imaging, have proven to be a valuable component for oral and maxillofacial …
Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosis
Y Wang, E Lombardo, M Avanzo, S Zschaek… - Computer Methods and …, 2022 - Elsevier
Objectives Recent studies have shown that deep learning based on pre-treatment positron
emission tomography (PET) or computed tomography (CT) is promising for distant …
emission tomography (PET) or computed tomography (CT) is promising for distant …
Simple python module for conversions between DICOM images and radiation therapy structures, masks, and prediction arrays
Deep learning is becoming increasingly popular and available to new users, particularly in
the medical field. Deep learning image segmentation, outcome analysis, and generators rely …
the medical field. Deep learning image segmentation, outcome analysis, and generators rely …
Comparison of the suitability of CBCT-and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients
A Thummerer, BA De Jong, P Zaffino… - Physics in Medicine …, 2020 - iopscience.iop.org
Cone-beam computed tomography (CBCT)-and magnetic resonance (MR)-images allow a
daily observation of patient anatomy but are not directly suited for accurate proton dose …
daily observation of patient anatomy but are not directly suited for accurate proton dose …