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Robust imaging habitat computation using voxel-wise radiomics features [PDF]
Scientific Reports, 2021 Tumor heterogeneity has been postulated as a hallmark of treatment resistance and a cure constraint in cancer patients. Conventional quantitative medical imaging (radiomics) can be extended to computing voxel-wise features and aggregating tumor ...
Kinga Bernatowicz +5 more
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The transformational potential of molecular radiomics
Journal 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
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Radiomics in Hepatocellular Carcinoma
Journal of Gastrointestinal Cancer, 2020 Radiomics is an emerging field that extracts high-throughput imaging data from different types of images to build models and predict clinical outcomes ina non-invasive manner. This field currently is in the initial growth phase and lacks standardized evaluation criteria but remains a very promising tool for the future todevelop suitable biomarkers for ...
Kahraman, Aysegul Sagir
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British Journal of Radiology, 2020 Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it into valuable predictive outcomes, As a result of advances in both computational hardware and machine learning algorithms, computers are making great strides in obtaining quantitative information ...
Rogers, William +16 more
+6 more sources
KYAMC Journal, 2019 Abstract not available KYAMC Journal Vol.
Farzad Khalvati +3 more
+6 more sources
CT radiomics and PET radiomics: ready for clinical implementation?
The Quarterly Journal of Nuclear Medicine and Molecular Imaging, 2019 Today, rapid technical and clinical developments result in an increasing number of treatment options for oncological diseases. Thus, decision support systems are needed to offer the right treatment to the right patient. Imaging biomarkers hold great promise in patient-individual treatment guidance. Routinely performed for diagnosis and staging, imaging
Bogowicz, Marta +7 more
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Introduction to Radiomics [PDF]
Journal 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 may, alone or in combination with demographic, histologic, genomic, or proteomic data, be used for ...
Marius E, Mayerhoefer +6 more
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, 2018 Recent advances in image-guided and adaptive radiotherapy have ushered new requirements for using single and/or multiple-imaging modalities in staging, treatment planning, and predicting response of different cancer types. Quantitative information analysis from multi-imaging modalities, known as ‘radiomics', have generated great promises to unravel ...
Ke Nie, Min-Ying Lydia Su
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ERJ Open Research, 2022 Purpose In this study, we propose an artificial intelligence (AI) framework based on three-dimensional convolutional neural networks to classify computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19), influenza/community ...
Akshayaa Vaidyanathan +14 more
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Multispectral Differential Reconstruction Strategy for Bioluminescence Tomography
Frontiers in Oncology, 2022 Bioluminescence tomography (BLT) is a promising in vivo molecular imaging tool that allows non-invasive monitoring of physiological and pathological processes at the cellular and molecular levels.
Yanqiu Liu +15 more
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