Artificial intelligence and machine learning for medical imaging: A technology review

A Barragán-Montero, U Javaid, G Valdés, D Nguyen… - Physica Medica, 2021 - Elsevier
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 …

Artificial intelligence: reshaping the practice of radiological sciences in the 21st century

I El Naqa, MA Haider, ML Giger… - The British journal of …, 2020 - academic.oup.com
Advances in computing hardware and software platforms have led to the recent resurgence
in artificial intelligence (AI) touching almost every aspect of our daily lives by its capability for …

Deep learning empowered volume delineation of whole-body organs-at-risk for accelerated radiotherapy

F Shi, W Hu, J Wu, M Han, J Wang, W Zhang… - Nature …, 2022 - nature.com
In radiotherapy for cancer patients, an indispensable process is to delineate organs-at-risk
(OARs) and tumors. However, it is the most time-consuming step as manual delineation is …

Synthetic MRI-aided multi-organ segmentation on male pelvic CT using cycle consistent deep attention network

X Dong, Y Lei, S Tian, T Wang, P Patel… - Radiotherapy and …, 2019 - Elsevier
Background and purpose Manual contouring is labor intensive, and subject to variations in
operator knowledge, experience and technique. This work aims to develop an automated …

CT prostate segmentation based on synthetic MRI‐aided deep attention fully convolution network

Y Lei, X Dong, Z Tian, Y Liu, S Tian, T Wang… - Medical …, 2020 - Wiley Online Library
Purpose Accurate segmentation of the prostate on computed tomography (CT) for treatment
planning is challenging due to CT's poor soft tissue contrast. Magnetic resonance imaging …

Male pelvic multi-organ segmentation aided by CBCT-based synthetic MRI

Y Lei, T Wang, S Tian, X Dong, AB Jani… - Physics in Medicine …, 2020 - iopscience.iop.org
Male pelvic multi-organ segmentation aided by CBCT-based synthetic MRI - IOPscience This
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AUNet: attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms

H Sun, C Li, B Liu, Z Liu, M Wang… - Physics in Medicine …, 2020 - iopscience.iop.org
Mammography is one of the most commonly applied tools for early breast cancer screening.
Automatic segmentation of breast masses in mammograms is essential but challenging due …

Male pelvic multi-organ segmentation using token-based transformer Vnet

S Pan, Y Lei, T Wang, J Wynne… - Physics in Medicine …, 2022 - iopscience.iop.org
Objective. This work aims to develop an automated segmentation method for the prostate
and its surrounding organs-at-risk in pelvic computed tomography to facilitate prostate …

[HTML][HTML] Segmentation of organs-at-risk in cervical cancer CT images with a convolutional neural network

Z Liu, X Liu, B Xiao, S Wang, Z Miao, Y Sun, F Zhang - Physica Medica, 2020 - Elsevier
Purpose We introduced and evaluated an end-to-end organs-at-risk (OARs) segmentation
model that can provide accurate and consistent OARs segmentation results in much less …

Intelligent inverse treatment planning via deep reinforcement learning, a proof-of-principle study in high dose-rate brachytherapy for cervical cancer

C Shen, Y Gonzalez, P Klages, N Qin… - Physics in Medicine …, 2019 - iopscience.iop.org
Inverse treatment planning in radiation therapy is formulated as solving optimization
problems. The objective function and constraints consist of multiple terms designed for …