Results 1 to 10 of about 82,903 (262)

Automated 5-year Mortality Prediction using Deep Learning and Radiomics Features from Chest Computed Tomography [PDF]

, 2016
We propose new methods for the prediction of 5-year mortality in elderly individuals using chest computed tomography (CT). The methods consist of a classifier that performs this prediction using a set of features extracted from the CT image and ...
Bradley, Andrew P., Carneiro, Gustavo, Nascimento, Jacinto, Oakden-Rayner, Luke, Palmer, Lyle   +4 more
core   +3 more sources

Preoperative prediction of lymph node metastasis in patients with ovarian cancer using contrast-enhanced computed tomography-based intratumoral and peritumoral radiomics features [PDF]

Frontiers in Oncology
PurposeTo develop and validate computed tomography (CT)-based intratumoral and peritumoral radiomics signatures for preoperative prediction of lymph node metastasis (LNM) in patients with ovarian cancer (OC).MethodsPatients with pathological diagnosis of
Jing Zhang, Qiyuan Li, Haoyu Liang, Yao Wang, Li Sun, Qingyuan Zhang, Chuanping Gao   +6 more
doaj   +2 more sources

Computed tomography based radiomics signature for predicting the expression of vascular endothelial growth factor in pediatric patients with nephroblastoma [PDF]

Scientific Reports
To construct a computed tomography (CT) based radiomics signature and assess its performance in predicting vascular endothelial growth factor (VEGF) expression in pediatric patients with nephroblastoma.
Ma Fu, Han Qi, Suyue Zhu, Yan Gao, Yanlin Li, Jian Wu, Dongsheng Zhu   +6 more
doaj   +2 more sources

Radiomics predicts the prognosis of patients with locally advanced breast cancer by reflecting the heterogeneity of tumor cells and the tumor microenvironment

Breast Cancer Research, 2022
Background This study investigated the efficacy of radiomics to predict survival outcome for locally advanced breast cancer (LABC) patients and the association of radiomics with tumor heterogeneity and microenvironment.
Xuanyi Wang, Tiansong Xie, Jurui Luo, Zhengrong Zhou, Xiaoli Yu, Xiaomao Guo   +5 more
doaj   +2 more sources

An externally validated fully automated deep learning algorithm to classify COVID-19 and other pneumonias on chest computed tomography

ERJ Open Research, 2022
Purpose In this study, we propose an artificial intelligence (AI) framework based on three-dimensional convolutional neural networks to classify computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19), influenza/community ...
Akshayaa Vaidyanathan, Julien Guiot, Fadila Zerka, Flore Belmans, Ingrid Van Peufflik, Louis Deprez, Denis Danthine, Gregory Canivet, Philippe Lambin, Sean Walsh, Mariaelena Occhipinti, Paul Meunier, Wim Vos, Pierre Lovinfosse, Ralph T.H. Leijenaar   +14 more
doaj   +1 more source

Multispectral Differential Reconstruction Strategy for Bioluminescence Tomography

Frontiers in Oncology, 2022
Bioluminescence tomography (BLT) is a promising in vivo molecular imaging tool that allows non-invasive monitoring of physiological and pathological processes at the cellular and molecular levels.
Yanqiu Liu, Yanqiu Liu, Mengxiang Chu, Mengxiang Chu, Hongbo Guo, Hongbo Guo, Xiangong Hu, Xiangong Hu, Jingjing Yu, Xuelei He, Xuelei He, Huangjian Yi, Huangjian Yi, Xiaowei He, Xiaowei He, Xiaowei He   +15 more
doaj   +1 more source

Robust imaging habitat computation using voxel-wise radiomics features

Scientific Reports, 2021
Tumor heterogeneity has been postulated as a hallmark of treatment resistance and a cure constraint in cancer patients. Conventional quantitative medical imaging (radiomics) can be extended to computing voxel-wise features and aggregating tumor ...
Kinga Bernatowicz, Francesco Grussu, Marta Ligero, Alonso Garcia, Eric Delgado, Raquel Perez-Lopez   +5 more
doaj   +1 more source

A Multilevel Probabilistic Cerenkov Luminescence Tomography Reconstruction Framework Based on Energy Distribution Density Region Scaling

Frontiers in Oncology, 2021
Cerenkov luminescence tomography (CLT) is a promising non-invasive optical imaging method with three-dimensional semiquantitative in vivo imaging capability.
Xiao Wei, Xiao Wei, Hongbo Guo, Hongbo Guo, Jingjing Yu, Xuelei He, Xuelei He, Huangjian Yi, Huangjian Yi, Yuqing Hou, Yuqing Hou, Xiaowei He, Xiaowei He   +12 more
doaj   +1 more source

CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII

Insights into Imaging, 2023
The workflow of radiomics is complex with several methodological steps and nuances, which often leads to inadequate reproducibility, reporting, and evaluation.
B. Koçak, B. Baessler, S. Bakas, R. Cuocolo, A. Fedorov, L. Maier-Hein, N. Mercaldo, Henning Müller, Fanny Orlhac, Daniel Pinto dos Santos, A. Stanzione, L. Ugga, A. Zwanenburg   +12 more
semanticscholar   +1 more source

External validation of a radiomic signature to predict p16 (HPV) status from standard CT images of anal cancer patients

Scientific Reports, 2023
The paper deals with the evaluation of the performance of an existing and previously validated CT based radiomic signature, developed in oropharyngeal cancer to predict human papillomavirus (HPV) status, in the context of anal cancer.
Ralph T. H. Leijenaar, Sean Walsh, Akshayaa Vaidyanathan, Lorenzo Aliboni, Victoria Lopez Sanchez, Michelle Leech, Ronan Joyce, Charles Gillham, Frédéric Kridelka, Roland Hustinx, Denis Danthine, Mariaelena Occhipinti, Wim Vos, Julien Guiot, Philippe Lambin, Pierre Lovinfosse   +15 more
doaj   +1 more source