Results 11 to 20 of about 73,359 (292)

Radiomics [PDF]

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, Seetha, Sithin Thulasi, Refaee, Turkey A. G., Lieverse, Relinde I. Y., Granzier, Renee W. Y., Ibrahim, Abdalla, Keek, Simon A., Sanduleanu, Sebastian, Primakov, Sergey P., Beuque, Manon P. L., Marcus, Damienne, van der Wiel, Alexander M. A., Zerka, Fadila, Oberije, Cary J. G., van Timmeren, Janita E., Woodruff, Henry C., Lambin, Philippe   +16 more
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Radiomics [PDF]

KYAMC Journal, 2019
Abstract not available KYAMC Journal Vol.
Farzad Khalvati, Yucheng Zhang, Alexander Wong, Masoom A. Haider   +3 more
  +6 more sources

Radiomics [PDF]

, 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 ...
Julie Constanzo, Issam El Naqa
  +4 more sources

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, Andrzej, Materka, Georg, Langs, Ida, Häggström, Piotr, Szczypiński, Peter, Gibbs, Gary, Cook   +6 more
openaire   +2 more sources

Radiomics

Nature Reviews Clinical Oncology, 2017
Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research.
Muhammad Idris, Arlene Campos, Candace Moore   +2 more
openaire   +2 more sources

Spatially aware radiomics integrating anatomical knowledge to improve lymph node malignancy prediction in head and neck cancer. [PDF]

J Appl Clin Med Phys
Abstract Background Radiomics holds the potential to improve the diagnostic evaluation of equivocal lymph nodes in head and neck cancer (HNC). While conventional radiomics models utilize features such as intensity, geometry, and texture of individual lymph node, they often neglect key spatial and anatomical characteristics tied to lymphatic ...
Chen L, Radpour S, Dohopolski M, Sher D, Wang J.   +4 more
europepmc   +2 more sources

Multi-omics predicts radiotherapy response in small cell lung cancer patients receiving whole brain irradiation. [PDF]

J Appl Clin Med Phys
Abstract Objective Dosiomics and radiomics elaborate the low‐and high‐order features extracted from images to predict clinical outcomes. Whole‐brain radiotherapy (WBRT) has been widely used in patients with diffuse brain metastases of small cell lung cancer (SCLC).
Lei Y, Bai H, Gong C, Xia Y, Hou Y, Yang R, Yu J, Zhang Z, Wang L, Li B, Wang L, Li L.   +11 more
europepmc   +2 more sources

Radiomics in immuno-oncology [PDF]

Immuno-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,
Bodalal, Z., Wamelink, I., Trebeschi, S., Beets-Tan, R. G.H.   +3 more
openaire   +3 more sources

Radiomics

Nuclear Medicine Communications, 2022
Cancer treatment is heading towards precision medicine driven by genetic and biochemical markers. Various genetic and biochemical markers are utilized to render personalized treatment in cancer. In the last decade, noninvasive imaging biomarkers have also been developed to assist personalized decision support systems in oncology. The imaging biomarkers
Jha, Ashish Kumar, Mithun, Sneha, Purandare, Nilendu C, Kumar, Rakesh, Rangarajan, Venkatesh, Wee, Leonard, Dekker, Andre   +6 more
openaire   +1 more source

Lung radiomics features for characterizing and classifying COPD stage based on feature combination strategy and multi-layer perceptron classifier

Mathematical Biosciences and Engineering, 2022
Computed tomography (CT) has been the most effective modality for characterizing and quantifying chronic obstructive pulmonary disease (COPD). Radiomics features extracted from the region of interest in chest CT images have been widely used for lung ...
Yingjian Yang , Wei Li , Yingwei Guo , Nanrong Zeng, Shicong Wang , Ziran Chen, Yang Liu, Huai Chen, Wenxin Duan, Xian Li , Wei Zhao, Rongchang Chen , Yan Kang   +12 more
doaj   +1 more source