Results 81 to 90 of about 71,655 (241)

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

Breast MRI radiomics and machine learning radiomics-based predictions of response to neoadjuvant chemotherapy -- how are they affected by variations in tumour delineation? [PDF]

arXiv, 2023
Manual delineation of volumes of interest (VOIs) by experts is considered the gold-standard method in radiomics analysis. However, it suffers from inter- and intra-operator variability. A quantitative assessment of the impact of variations in these delineations on the performance of the radiomics predictors is required to develop robust radiomics based
arxiv  

The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights.

Radiology
Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the visible image using radiomics.
P. Whybra, A. Zwanenburg, V. Andrearczyk, Roger Schaer, Aditya Apte, Alexandre Ayotte, B. Baheti, S. Bakas, A. Bettinelli, Ronald Boellaard, L. Boldrini, I. Buvat, Gary J R Cook, Florian Dietsche, N. Dinapoli, H. Gabryś, V. Goh, M. Guckenberger, Mathieu Hatt, Mahdi Hosseinzadeh, A. Iyer, J. Lenkowicz, Mahdi A L Loutfi, Steffen Löck, F. Marturano, Olivier Morin, C. Nioche, Fanny Orlhac, Sarthak Pati, Arman Rahmim, S. M. Rezaeijo, Christopher G Rookyard, Mohammad R. Salmanpour, Andreas Schindele, I. Shiri, E. Spezi, S. Tanadini-Lang, F. Tixier, T. Upadhaya, Vincenzo Valentini, Joost J. M. van Griethuysen, F. Yousefirizi, H. Zaidi, H. Müller, M. Vallières, A. Depeursinge   +45 more
semanticscholar   +1 more source

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

Development of a PET/CT molecular radiomics-clinical model to predict thoracic lymph node metastasis of invasive lung adenocarcinoma ≤ 3 cm in diameter

EJNMMI Research, 2022
Background To investigate the value of 18F-FDG PET/CT molecular radiomics combined with a clinical model in predicting thoracic lymph node metastasis (LNM) in invasive lung adenocarcinoma (≤ 3 cm). Methods A total of 528 lung adenocarcinoma patients were
Cheng Chang, Maomei Ruan, Bei Lei, Hong Yu, Wenlu Zhao, Yaqiong Ge, Shaofeng Duan, Wenjing Teng, Qianfu Wu, Xiaohua Qian, Lihua Wang, Hui Yan, Ciyi Liu, Liu Liu, Jian Feng, Wenhui Xie   +15 more
doaj   +1 more source

Multi-modality radiomics nomogram based on DCE-MRI and ultrasound images for benign and malignant breast lesion classification

Frontiers in Oncology, 2022
ObjectiveTo develop a multi-modality radiomics nomogram based on DCE-MRI, B-mode ultrasound (BMUS) and strain elastography (SE) images for classifying benign and malignant breast lesions.Material and MethodsIn this retrospective study, 345 breast lesions
Xinmiao Liu, Xinmiao Liu, Ji Zhang, Jiejie Zhou, Jiejie Zhou, Yun He, Yunyu Xu, Zhenhua Zhang, Guoquan Cao, Haiwei Miao, Zhongwei Chen, Youfan Zhao, Xiance Jin, Xiance Jin, Meihao Wang, Meihao Wang   +15 more
doaj   +1 more source

Ultra-high dimensional confounder selection algorithms comparison with application to radiomics data [PDF]

arXiv, 2023
Radiomics is an emerging area of medical imaging data analysis particularly for cancer. It involves the conversion of digital medical images into mineable ultra-high dimensional data. Machine learning algorithms are widely used in radiomics data analysis to develop powerful decision support model to improve precision in diagnosis, assessment of ...
arxiv  

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

Radiomics Is Effective for Distinguishing Coronavirus Disease 2019 Pneumonia From Influenza Virus Pneumonia

Frontiers in Public Health, 2021
Objectives: To develop and validate a radiomics model for distinguishing coronavirus disease 2019 (COVID-19) pneumonia from influenza virus pneumonia.Materials and Methods: A radiomics model was developed on the basis of 56 patients with COVID-19 ...
Liaoyi Lin, Jinjin Liu, Qingshan Deng, Na Li, Jingye Pan, Houzhang Sun, Shichao Quan   +6 more
doaj   +1 more source

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