Results 101 to 110 of about 82,903 (262)

Radiomics: is it time to compose the puzzle? [PDF]

Clinical and Translational Imaging, 2018
-
Castiglioni I., Gilardi M. C.
openaire   +5 more sources

Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction

, 2018
Deep learning for regression tasks on medical imaging data has shown promising results. However, compared to other approaches, their power is strongly linked to the dataset size.
A Jungo, AW Awad, B Fischl, BH Menze, CH Lampert, DN Louis, DR Cox, G Wang, J Lao, JJ Griethuysen van, Julián Pérez-Beteta, N Sanai, R Meier, R Tibshirani, RJ Gillies, S Bakas, S Pereira, S Rathore, Spyridon Bakas, Spyridon Bakas, T Hastie, TC Steed, Y Li   +22 more
core   +1 more source

Introduction to radiomics for a clinical audience

Clinical Radiology, 2023
Radiomics is a rapidly developing field of research focused on the extraction of quantitative features from medical images, thus converting these digital images into minable, high-dimensional data, which offer unique biological information that can enhance our understanding of disease processes and provide clinical decision support.
McCague, C, Ramlee, S, Reinius, M, Selby, I, Hulse, D, Piyatissa, P, Bura, V, Crispin-Ortuzar, M, Sala, E, Woitek, R   +9 more
openaire   +2 more sources

Machine Learning Model Integrating CT Radiomics of the Lung to Predict Checkpoint Inhibitor Pneumonitis in Patients with Advanced Cancer

Technology in Cancer Research & Treatment
Objective Checkpoint inhibitor pneumonitis (CIP) is a potentially life-threatening immune-related adverse event. Efficient strategies to select patients at risk are still required.
François Cousin MD, PhD, Thomas Louis MS, PhD, Pierre Frères MD, PhD, Julien Guiot MD, PhD, Mariaelena Occhipinti MD, Fabio Bottari MS, Wim Vos MS, Roland Hustinx MD, PhD   +7 more
doaj   +1 more source

Development of a MRI-Based Radiomics Nomogram for Prediction of Response of Patients With Muscle-Invasive Bladder Cancer to Neoadjuvant Chemotherapy

Frontiers in Oncology, 2022
ObjectiveTo develop and evaluate the performance of a magnetic resonance imaging (MRI)-based radiomics nomogram for prediction of response of patients with muscle-invasive bladder cancer (MIBC) to neoadjuvant chemotherapy (NAC).MethodsA total of 70 ...
Xinxin Zhang, Yichen Wang, Jin Zhang, Lianyu Zhang, Sicong Wang, Yan Chen   +5 more
doaj   +1 more source

A review in radiomics: Making personalized medicine a reality via routine imaging

Medicinal research reviews (Print), 2021
Radiomics is the quantitative analysis of standard‐of‑care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models.
J. Guiot, A. Vaidyanathan, L. Deprez, F. Zerka, Denis Danthine, A. Frix, P. Lambin, F. Bottari, N. Tsoutzidis, B. Miraglio, S. Walsh, W. Vos, R. Hustinx, M. Ferreira, P. Lovinfosse, R. Leijenaar   +15 more
semanticscholar   +1 more source

Radiogenomic correlation of hypoxia-related biomarkers in clear cell renal cell carcinoma

Journal of Cancer Research and Clinical Oncology
Purpose This study aimed to evaluate radiomic models’ ability to predict hypoxia-related biomarker expression in clear cell renal cell carcinoma (ccRCC).
Yijun Shao, Harmony S. Cen, Anu Dhananjay, S. J. Pawan, Xiaomeng Lei, Inderbir S. Gill, Anishka D’souza, Vinay A. Duddalwar   +7 more
doaj   +1 more source

A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules

Cancer Imaging, 2020
Purpose To develop a radiomics nomogram based on computed tomography (CT) images that can help differentiate lung adenocarcinomas and granulomatous lesions appearing as sub-centimeter solid nodules (SCSNs).
Xiangmeng Chen, Bao Feng, Yehang Chen, Kunfeng Liu, Kunwei Li, Xiaobei Duan, Yixiu Hao, Enming Cui, Zhuangsheng Liu, Chaotong Zhang, Wansheng Long, Xueguo Liu   +11 more
doaj   +1 more source

A Combined-Radiomics Approach of CT Images to Predict Response to Anti-PD-1 Immunotherapy in NSCLC: A Retrospective Multicenter Study

Frontiers in Oncology, 2022
ObjectiveBased on non-contrast-enhanced (NCE)/contrast-enhanced (CE) computed tomography (CT) images, we try to identify a combined-radiomics model and evaluate its predictive capacity regarding response to anti-PD1 immunotherapy of patients with non ...
Minghao Wu, Minghao Wu, Yanyan Zhang, Jianing Zhang, Yuwei Zhang, Yina Wang, Feng Chen, Yahong Luo, Shuai He, Yulin Liu, Qian Yang, Yanying Li, Hong Wei, Hong Zhang, Nian Lu, Sicong Wang, Yan Guo, Zhaoxiang Ye, Ying Liu   +18 more
doaj   +1 more source

Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis. [PDF]

, 2018
Radiomics is an emerging technology for imaging biomarker discovery and disease-specific personalized treatment management. This paper aims to determine the benefit of using multi-modality radiomics data from PET and MR images in the characterization ...
Arasu, Vignesh A, Behr, Spencer C, Copeland, Timothy P, Esserman, Laura, Franc, Benjamin L, Harnish, Roy J, Huang, Shih-Ying, Hylton, Nola M, Jones, Ella F, Kornak, John, Liu, Gengbo, Mitra, Debasis, Price, Elissa R, Seo, Youngho   +13 more
core