Radiomics and Artificial Intelligence in Oncology Imaging

74.1K

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152

authors

24

articles

Radiomics and Artificial Intelligence in Oncology Imaging

74.1K

views

152

authors

24

articles

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Imaging plays a key role in oncology, whether at the diagnostic stage, in the preparation of treatment, the evaluation of the response, or in terms of prognosis. The progress made in image acquisition and analysis by the various medical specialties has led to improvements in patient care.

Despite this, there is still a great deal of information to be discovered from these images.
Radiomics can now drastically increase the amount of information that can be extracted from these images. Given the big amount of data extracted, the use of artificial intelligence algorithms is essential to the analysis of these data. Elsewhere, the use of artificial intelligence could also improve the workflow at each step of the process in imaging.

This research topic aims to explore the various fields of application of radiomic studies, in terms of diagnostic aid, treatment preparation, assessment of response to treatment, or personalization of treatment. The question can be addressed to different types of imaging, with a focus on metabolic imaging. The potential of AI algorithms in the analysis of radiomics data or in the improvement of imaging workflow will also be explore.

The research topic is addressed to all clinicians or researchers working in the field of imaging, especially those working in metabolic imaging.

It will cover all aspects or radiomics and artificial intelligence in imaging.
Authors could propose different types of manuscripts, from review to research articles.

Imaging plays a key role in oncology, whether at the diagnostic stage, in the preparation of treatment, the evaluation of the response, or in terms of prognosis. The progress made in image acquisition and analysis by the various medical specialties has led to improvements in patient care.

Despite this, there is still a great deal of information to be discovered from these images.
Radiomics can now drastically increase the amount of information that can be extracted from these images. Given the big amount of data extracted, the use of artificial intelligence algorithms is essential to the analysis of these data. Elsewhere, the use of artificial intelligence could also improve the workflow at each step of the process in imaging.

This research topic aims to explore the various fields of application of radiomic studies, in terms of diagnostic aid, treatment preparation, assessment of response to treatment, or personalization of treatment. The question can be addressed to different types of imaging, with a focus on metabolic imaging. The potential of AI algorithms in the analysis of radiomics data or in the improvement of imaging workflow will also be explore.

The research topic is addressed to all clinicians or researchers working in the field of imaging, especially those working in metabolic imaging.

It will cover all aspects or radiomics and artificial intelligence in imaging.
Authors could propose different types of manuscripts, from review to research articles.

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Frontiers in Nuclear Medicine

Radiomics and Artificial Intelligence

Journal Thumbnail

Frontiers in Endocrinology

Thyroid Endocrinology

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Frontiers in Oncology

Thoracic Oncology

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