Results 11 to 20 of about 82,903 (262)

A deep look into radiomics [PDF]

open access: yesLa radiologia medica, 2021
Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging.
Camilla Scapicchio   +5 more
semanticscholar   +4 more sources

Introduction to Radiomics [PDF]

open access: yesJournal of Nuclear Medicine, 2020
Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics—the so-called radiomic features—within medical images. Radiomic features capture tissue and lesion characteristics such as heterogeneity and shape and
M. Mayerhoefer   +6 more
semanticscholar   +4 more sources

Towards reproducible radiomics research: introduction of a database for radiomics studies

open access: yesEuropean Radiology, 2023
Objectives To investigate the model-, code-, and data-sharing practices in the current radiomics research landscape and to introduce a radiomics research database. Methods A total of 1254 articles published between January 1, 2021, and December 31, 2022,
Tugba Akinci D'Antonoli   +3 more
semanticscholar   +4 more sources

The transformational potential of molecular radiomics

open access: yesJournal of Medical Radiation Sciences, 2023
Conventional radiomics in nuclear medicine involve hand‐crafted and computer‐assisted regions of interest. Recent developments in artificial intelligence (AI) have seen the emergence of AI‐augmented segmentation and extraction of lower order traditional ...
Geoffrey Currie   +2 more
doaj   +3 more sources

Radiomics in immuno-oncology [PDF]

open access: yesImmuno-Oncology and Technology, 2021
With the ongoing advances in imaging techniques, increasing volumes of anatomical and functional data are being generated as part of the routine clinical workflow. This surge of available imaging data coincides with increasing research in quantitative imaging, particularly in the domain of imaging features. An important and novel approach is radiomics,
I. Wamelink   +7 more
openaire   +4 more sources

Radiomics for liver tumours [PDF]

open access: yesStrahlentherapie und Onkologie, 2020
AbstractCurrent research, especially in oncology, increasingly focuses on the integration of quantitative, multiparametric and functional imaging data. In this fast-growing field of research, radiomics may allow for a more sophisticated analysis of imaging data, far beyond the qualitative evaluation of visible tissue changes.
Constantin Dreher   +3 more
openaire   +3 more sources

Radiomics in Nasopharyngeal Carcinoma [PDF]

open access: yesClinical Medicine Insights: Oncology, 2022
Nasopharyngeal carcinoma (NPC) is one of the most common head and neck malignancies, and the primary treatment methods are radiotherapy and chemotherapy. Radiotherapy alone, concurrent chemoradiotherapy, and induction chemotherapy combined with concurrent chemoradiotherapy can be used according to different grades. Treatment options and prognoses vary
Wenyue Duan   +5 more
openaire   +3 more sources

Radiomics in Oncology III

open access: yesDiagnostics, 2023
In recent years, radiomics has been among the most impactful topics in the research field of quantitative imaging [...]
Zerunian, Marta   +2 more
openaire   +3 more sources

State of Radiomics in Glioblastoma [PDF]

open access: yesNeurosurgery, 2021
Abstract Radiomics is an emerging discipline that aims to make intelligent predictions and derive medical insights based on quantitative features extracted from medical images as a means to improve clinical diagnosis or outcome. Pertaining to glioblastoma, radiomics has provided powerful, noninvasive tools for gaining insights into ...
Birra Taha   +3 more
openaire   +3 more sources

Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling

open access: yesMilitary Medical Research, 2023
Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’ anatomy. However, the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians.
Yuanpeng Zhang   +13 more
semanticscholar   +1 more source

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