Results 51 to 60 of about 73,359 (292)

Tensor Radiomics: Paradigm for Systematic Incorporation of Multi-Flavoured Radiomics Features

SSRN Electronic Journal, 2022
Radiomics features extract quantitative information from medical images, towards the derivation of biomarkers for clinical tasks, such as diagnosis, prognosis, or treatment response assessment. Different image discretization parameters (e.g. bin number or size), convolutional filters, segmentation perturbation, or multi-modality fusion levels can be ...
Rahmim, Arman, Toosi, Amirhosein, Salmanpour, Mohammad R., Dubljevic, Natalia, Janzen, Ian, Shiri Lord, Isaac, Yuan, Ren, Ho, Cheryl, Zaidi, Habib, MacAulay, Calum, Uribe, Carlos, Yousefirizi, Fereshteh   +11 more
openaire   +3 more sources

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

Three-Dimensional Radiomics Features From Multi-Parameter MRI Combined With Clinical Characteristics Predict Postoperative Cerebral Edema Exacerbation in Patients With Meningioma

Frontiers in Oncology, 2021
BackgroundPostoperative cerebral edema is common in patients with meningioma. It is of great clinical significance to predict the postoperative cerebral edema exacerbation (CEE) for the development of individual treatment programs in patients with ...
Bing Xiao, Yanghua Fan, Zhe Zhang, Zilong Tan, Huan Yang, Wei Tu, Lei Wu, Xiaoli Shen, Hua Guo, Zhen Wu, Xingen Zhu   +10 more
doaj   +1 more source

Highly accurate model for prediction of lung nodule malignancy with CT scans [PDF]

, 2018
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer.
Causey, Jason L., Huang, Xiuzhen, Jiang, Bo, Ma, Shiqian, Politte, David G., Prior, Fred, Qualls, Jake A., Zhang, Junyu, Zhang, Shuzhong   +8 more
core   +3 more sources

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

Radiomics and Deep Radiomics for precision medicine

, 2021
{"references": ["E Bertelli, L Mercatelli, C Marzi, E Pachetti, M Baccini, et al. Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI., Fron in Oncology, 5515, 2021, https://doi.org/10.3389/fonc.2021.802964", "F Gioia, MA Pascali, A Greco, S Colantonio, EP Scilingo.
openaire   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +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  

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

Physics in Medicine & Biology, 2021
Abstract Purpose. 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. Material and Methods.
Zeyu Zhang, Mi Huang, Zhuoran Jiang, Yushi Chang, Jordan Torok, Fang-Fang Yin, Lei Ren   +6 more
openaire   +3 more sources

Heterogeneity of Rheumatoid Arthritis–Associated Interstitial Lung Disease by Longitudinal Forced Vital Capacity Trajectory and Associations With Disease Outcomes

Arthritis Care &Research, EarlyView.
Objective We aimed to identify unique disease trajectories within rheumatoid arthritis–associated interstitial lung disease (RA‐ILD) based on longitudinal forced vital capacity (FVC) values and their associated clinical outcomes. Methods We performed a cohort study of RA‐ILD within the Veterans Health Administration from 1999 to 2021.
Bryant R. England, Yangyuna Yang, Punyasha Roul, Tate M. Johnson, Scott M. Matson, Grant W. Cannon, Brian C. Sauer, Jeffrey R. Curtis, Joshua F. Baker, Ted R. Mikuls   +9 more
wiley   +1 more source