Results 91 to 100 of about 82,903 (262)

Joint EANM/SNMMI guideline on radiomics in nuclear medicine

European Journal of Nuclear Medicine and Molecular Imaging, 2022
Purpose The purpose of this guideline is to provide comprehensive information on best practices for robust radiomics analyses for both hand-crafted and deep learning-based approaches.
M. Hatt, A. Krizsan, A. Rahmim, T. Bradshaw, P. F. Costa, A. Forgács, R. Seifert, A., Zwanenburg, I. Naqa, Paul Kinahan, F. Tixier, A. Jha, D. Visvikis   +13 more
semanticscholar   +1 more source

Radiomics: A primer for the radiation oncologist

Cancer/Radiothérapie, 2020
Radiomics are a set of methods used to leverage medical imaging and extract quantitative features that can characterize a patient's phenotype. All modalities can be used with several different software packages. Specific informatics methods can then be used to create meaningful predictive models.
Anita Burgun, Nicolas Giraud, Jean-Emmanuel Bibault, Jean-Emmanuel Bibault, Paul Giraud, R. El Ayachy, Pierre Decazes, L. Xing   +7 more
openaire   +6 more sources

Radiomics in esophageal and gastric cancer [PDF]

Abdominal Radiology, 2018
Esophageal, esophago-gastric, and gastric cancers are major causes of cancer morbidity and cancer death. For patients with potentially resectable disease, multi-modality treatment is recommended as it provides the best chance of survival. However, quality of life may be adversely affected by therapy, and with a wide variation in outcome despite multi ...
Gary Cook, Gary Cook, Vicky Goh, Vicky Goh, Bert-Ram Sah, Kasia Owczarczyk, Musib Siddique   +6 more
openaire   +4 more sources

An Approach Based on Mammographic Imaging and Radiomics for Distinguishing Male Benign and Malignant Lesions: A Preliminary Study

Frontiers in Oncology, 2021
PurposeTo develop and validate an imaging-radiomics model for the diagnosis of male benign and malignant breast lesions.MethodsNinety male patients who underwent preoperative mammography from January 2011 to December 2018 were enrolled in this study (63 ...
Yan Huang, Yan Huang, Qin Xiao, Qin Xiao, Yiqun Sun, Yiqun Sun, Zhe Wang, Qin Li, Qin Li, He Wang, He Wang, He Wang, Yajia Gu, Yajia Gu   +13 more
doaj   +1 more source

Radiomics for Response and Outcome Assessment for Non-Small Cell Lung Cancer. [PDF]

, 2018
Routine follow-up visits and radiographic imaging are required for outcome evaluation and tumor recurrence monitoring. Yet more personalized surveillance is required in order to sufficiently address the nature of heterogeneity in nonsmall cell lung ...
Benedict, Stanley, He, Yaoyao, Qiu, Jianfeng, Rong, Yi, Shi, Liting, Valicenti, Richard, Yuan, Zilong   +6 more
core   +1 more source

Feasibility of using CT radiomic signatures for predicting CD8-T cell infiltration and PD-L1 expression in renal cell carcinoma

European Journal of Radiology Open, 2022
Objectives: To identify computed tomography (CT)-based radiomic signatures of cluster of differentiation 8 (CD8)-T cell infiltration and programmed cell death ligand 1 (PD-L1) expression levels in patients with clear-cell renal cell carcinoma (ccRCC ...
Bino Varghese, Steven Cen, Haris Zahoor, Imran Siddiqui, Manju Aron, Akash Sali, Suhn Rhie, Xiaomeng Lei, Marielena Rivas, Derek Liu, Darryl Hwang, David Quinn, Mihir Desai, Ulka Vaishampayan, Inderbir Gill, Vinay Duddalwar   +15 more
doaj  

Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative

European Radiology, 2022
Objective The main aim of the present systematic review was a comprehensive overview of the Radiomics Quality Score (RQS)–based systematic reviews to highlight common issues and challenges of radiomics research application and evaluate the relationship ...
Gaia Spadarella, A. Stanzione, Tugba Akinci D'Antonoli, A. Andreychenko, S. C. Fanni, L. Ugga, E. Kotter, R. Cuocolo   +7 more
semanticscholar   +1 more source

4D radiomics: impact of 4D-CBCT image quality on radiomic analysis

Physics in Medicine & Biology, 2021
To investigate the impact of 4D-CBCT image quality on radiomic analysis and the efficacy of using deep learning based image enhancement to improve the accuracy of radiomic features of 4D-CBCT.In this study, 4D-CT data from 16 lung cancer patients were obtained.
Jordan Torok, Lei Ren, Fang-Fang Yin, Zeyu Zhang, Zhuoran Jiang, Zhuoran Jiang, Yushi Chang, Mi Huang   +7 more
openaire   +3 more sources

Prediction of PD-L1 and CD68 in Clear Cell Renal Cell Carcinoma with Green Learning

Journal of Imaging
Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer. Extensive efforts have been made to utilize radiomics from computed tomography (CT) imaging to predict tumor immune microenvironment (TIME) measurements. This study proposes
Yixing Wu, Alexander Shieh, Steven Cen, Darryl Hwang, Xiaomeng Lei, S. J. Pawan, Manju Aron, Inderbir Gill, William D. Wallace, C.-C. Jay Kuo, Vinay Duddalwar   +10 more
doaj   +1 more source

A CT-based radiomics approach to predict intra-tumoral tertiary lymphoid structures and recurrence of intrahepatic cholangiocarcinoma

Insights into Imaging, 2023
Purpose To predict the tertiary lymphoid structures (TLSs) status and recurrence-free survival (RFS) of intrahepatic cholangiocarcinoma (ICC) patients using preoperative CT radiomics.
Ying Xu, Zhuo Li, Yi Yang, Lu Li, Yanzhao Zhou, Jingzhong Ouyang, Zhen Huang, Sicong Wang, Lizhi Xie, Feng Ye, Jinxue Zhou, Jianming Ying, Hong Zhao, Xinming Zhao   +13 more
doaj   +1 more source