Results 61 to 70 of about 462,780 (278)

Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning

, 2018
Multi-task neural network architectures provide a mechanism that jointly integrates information from distinct sources. It is ideal in the context of MR-only radiotherapy planning as it can jointly regress a synthetic CT (synCT) scan and segment organs-at-
Alexander, Daniel C., Bragman, Felix J. S., Cardoso, M. Jorge, Eaton-Rosen, Zach, Hawkes, David J., Li, Wenqi, McClelland, Jamie R., Ourselin, Sebastien, Tanno, Ryutaro   +8 more
core   +1 more source

Screening for lung cancer: A systematic review of overdiagnosis and its implications

Molecular Oncology, EarlyView.
Low‐dose computed tomography (CT) screening for lung cancer may increase overdiagnosis compared to no screening, though the risk is likely low versus chest X‐ray. Our review of 8 trials (84 660 participants) shows added costs. Further research with strict adherence to modern nodule management strategies may help determine the extent to which ...
Fiorella Karina Fernández‐Sáenz, Laura de la Torre‐Perez, David R Baldwin, Carlijn van der Aalst, Mangesh Thorat, David Ritchie, Andre L Carvalho, Carolina Espina, Ivan Solà, Carlos Canelo‐Aybar, Moira Magdalena Pissinis, Pablo Alonso‐Coello, Ana Carolina Pereira Nunes Pinto   +12 more
wiley   +1 more source

Synthetic computed tomography techniques for adaptive proton therapy in head and neck cancers

Physics and Imaging in Radiation Oncology
Head and neck (HN) radiotherapy often requires corrective interventions. This study evaluated three methods for synthetic computed tomography (CT) generation for adaptive HN planning using cone-beam CT (CBCT) images.
Suryakant Kaushik, Nadine Vatterodt, Jakob Ödén, Albin Fredriksson, Stine S. Korreman, Iuliana Toma-Dasu   +5 more
doaj   +1 more source

Forward Attention in Sequence-to-sequence Acoustic Modelling for Speech Synthesis

, 2018
This paper proposes a forward attention method for the sequenceto- sequence acoustic modeling of speech synthesis. This method is motivated by the nature of the monotonic alignment from phone sequences to acoustic sequences. Only the alignment paths that
Dai, Li-Rong, Ling, Zhen-Hua, Zhang, Jing-Xuan   +2 more
core   +1 more source

Reduced vascular leakage correlates with breast carcinoma T regulatory cell infiltration but not with metastatic propensity

Molecular Oncology, EarlyView.
A mouse model for vascular normalization and a human breast cancer cohort were studied to understand the relationship between vascular leakage and tumor immune suppression. For this, endothelial and immune cell RNAseq, staining for vascular function, and immune cell profiling were employed.
Liqun He, Chiara Testini, Neda Hekmati, Altea Bonello, Aglaia Schiza, Emmanuel Nwadozi, Mia Phillipson, Carina Strell, Michael Welsh   +8 more
wiley   +1 more source

Evaluation of magnetic resonance imaging and deep learning-based synthetic computed tomography for calcified intradural tumors – importance of domain-specific training and validation of synthetic imaging methods for clinical application

Acta Neurochirurgica
Purpose For intradural spinal tumors, information on the degree of calcification is helpful to plan the surgery. Novel deep-learning algorithms allow to generate synthetic computed tomography (CT) images from magnetic resonance imaging (MRI).
Gregor Fischer, Felix C. Stengel, Lorenzo Bertulli, Linda Bättig, Victor E. Staartjes, Tobias Dietrich, Olaf Chan-Hi Kim, Martin N. Stienen   +7 more
doaj   +1 more source

Cone-Beam CT to Synthetic CT Translation Using Conditional 3D Latent Diffusion-Based Model

IEEE Access
Accurate cone-beam CT (CBCT)-to-synthetic CT (sCT) translation is essential for image-guided adaptive radiotherapy (IGART), where Hounsfield unit (HU) fidelity and structural accuracy directly affect dose calculation.
Mohammed Al-Shalabi, Mohammed A. Mahdi, Reda Elbarougy, Ehab Tawfeek Alnfrawy, Muhammad Usman Hadi, Rao Faizan Ali   +5 more
doaj   +1 more source

Generating synthetic CT from low-dose cone-beam CT by using generative adversarial networks for adaptive radiotherapy

Radiation Oncology, 2021
Objective To develop high-quality synthetic CT (sCT) generation method from low-dose cone-beam CT (CBCT) images by using attention-guided generative adversarial networks (AGGAN) and apply these images to dose calculations in radiotherapy.
Liugang Gao, Kai Xie, Xiaojin Wu, Zhengda Lu, Chunying Li, Jiawei Sun, Tao Lin, Jianfeng Sui, Xinye Ni   +8 more
doaj   +1 more source

Accelerated gradient methods for total-variation-based CT image reconstruction [PDF]

, 2011
Total-variation (TV)-based Computed Tomography (CT) image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data.
Hansen, Per Christian, Jensen, Søren Holdt, Jensen, Tobias Lindstrøm, Jørgensen, Jakob Heide, Pan, Xiaochuan, Sidky, Emil Y.   +5 more
core   +2 more sources

CBCT-to-CT synthesis with a single neural network for head-and-neck, lung and breast cancer adaptive radiotherapy

, 2019
Purpose: CBCT-based adaptive radiotherapy requires daily images for accurate dose calculations. This study investigates the feasibility of applying a single convolutional network to facilitate CBCT-to-CT synthesis for head-and-neck, lung, and breast ...
Berg, Cornelis AT van den, Houweling, Anette C, Kotte, Alexis NTJ, Maspero, Matteo, Savenije, Mark HF, van Heijst, Tristan CF, Verhoeff, Joost JC   +6 more
core   +1 more source