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 …
Deep learning based synthetic‐CT generation in radiotherapy and PET: a review
Abstract Recently, deep learning (DL)‐based methods for the generation of synthetic
computed tomography (sCT) have received significant research attention as an alternative to …
computed tomography (sCT) have received significant research attention as an alternative to …
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 …
Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review
Purpose In radiotherapy, MRI is used for target volume and organs-at-risk delineation for its
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …
superior soft-tissue contrast as compared to CT imaging. However, MRI does not provide the …
The role of generative adversarial networks in brain MRI: a scoping review
The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …
made available. Generative adversarial networks (GANs) showed a lot of potential to …
Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model …
A Barragán-Montero, A Bibal… - Physics in Medicine …, 2022 - iopscience.iop.org
The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …
the performance leap that occurred with new techniques of deep learning, convolutional …
From CNNs to GANs for cross-modality medical image estimation
AS Fard, DC Reutens, V Vegh - Computers in biology and medicine, 2022 - Elsevier
Cross-modality image estimation involves the generation of images of one medical imaging
modality from that of another modality. Convolutional neural networks (CNNs) have been …
modality from that of another modality. Convolutional neural networks (CNNs) have been …
Generative adversarial networks in brain imaging: A narrative review
Artificial intelligence (AI) is expected to have a major effect on radiology as it demonstrated
remarkable progress in many clinical tasks, mostly regarding the detection, segmentation …
remarkable progress in many clinical tasks, mostly regarding the detection, segmentation …
Clinical validation of a commercially available deep learning software for synthetic CT generation for brain
M Lerner, J Medin, C Jamtheim Gustafsson, S Alkner… - Radiation …, 2021 - Springer
Background Most studies on synthetic computed tomography (sCT) generation for brain rely
on in-house developed methods. They often focus on performance rather than clinical …
on in-house developed methods. They often focus on performance rather than clinical …
[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 …