Results 41 to 50 of about 55,768 (244)
iScience, 2023 Summary: To guide individualized intensity-modulated radiotherapy (IMRT), we developed and prospectively validated a multiview radiomics risk model for predicting radiation-induced hypothyroidism in patients with nasopharyngeal carcinoma.
Shan-Shan Yang +8 more
doaj +1 more source
Radiomics-Based Outcome Prediction for Pancreatic Cancer Following Stereotactic Body Radiotherapy [PDF]
, 2020 (1) Background: Radiomics use high-throughput mining of medical imaging data to extract unique information and predict tumor behavior. Currently available clinical prediction models poorly predict treatment outcomes in pancreatic adenocarcinoma ...
Baine, Michael +11 more
core +1 more source
Cardiac Computed Tomography Radiomics [PDF]
Journal of Thoracic Imaging, 2018 Radiologic images are vast three-dimensional data sets in which each voxel of the underlying volume represents distinct physical measurements of a tissue-dependent characteristic. Advances in technology allow radiologists to image pathologies with unforeseen detail, thereby further increasing the amount of information to be processed.
Kolossváry, Márton József +3 more
openaire +3 more sources
EJNMMI Research, 2023 Background Vertebral compression fractures (VCFs) are common clinical problems that arise from various reasons. The differential diagnosis of benign and malignant VCFs is challenging.
Xun Wang +8 more
doaj +1 more source
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 +10 more
doaj +1 more source
MRI radiomic features are independently associated with overall survival in soft tissue sarcoma [PDF]
, 2019 Purpose: Soft tissue sarcomas (STS) represent a heterogeneous group of diseases, and selection of individualized treatments remains a challenge. The goal of this study was to determine whether radiomic features extracted from magnetic resonance (MR ...
Ball, Kevin C +11 more
core +2 more sources
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 +11 more
openaire +3 more sources
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 +13 more
doaj +1 more source
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 +5 more
doaj +1 more source
Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images [PDF]
, 2018 Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology Images, we compare one handcrafted feature extractor and five transfer ...
FA Spanhol +8 more
core +5 more sources