Results 1 to 10 of about 55,794 (349)

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

Machine learning-based radiomics prognostic model for patients with proximal esophageal cancer after definitive chemoradiotherapy [PDF]

Insights into Imaging
Objectives To explore the role of radiomics in predicting the prognosis of proximal esophageal cancer and to investigate the biological underpinning of radiomics in identifying different prognoses.
Linrui Li, Zhihui Qin, Juan Bo, Jiaru Hu, Yu Zhang, Liting Qian, Jiangning Dong   +6 more
doaj   +2 more sources

Radiomics: the facts and the challenges of image analysis [PDF]

European Radiology Experimental, 2018
Stefania Rizzo, Francesca Botta, Sara Raimondi, Daniela Origgi, Cristiana Fanciullo, A.G. Morganti, Massimo Bellomi   +6 more
openalex   +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

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

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

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

A Finite Element Mesh Regrouping Strategy-Based Hybrid Light Transport Model for Enhancing the Efficiency and Accuracy of XLCT

Frontiers in Oncology, 2022
X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality in optical molecular imaging, which has attracted more attention and has been widely studied. In XLCT, the accuracy and operational efficiency of an optical transmission
Yanqiu Liu, Yanqiu Liu, Xiangong Hu, Xiangong Hu, Mengxiang Chu, Mengxiang Chu, Hongbo Guo, Hongbo Guo, Jingjing Yu, Xiaowei He, Xiaowei He, Xiaowei He   +11 more
doaj   +1 more source

B₀ Correction for 3T Amide Proton Transfer (APT) MRI Using a Simplified Two-Pool Lorentzian Model of Symmetric Water and Asymmetric Solutes

Tomography, 2022
Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTRasym, the quantification method of APT, is easily influenced by B0 inhomogeneity and causes
Yibing Chen, Xujian Dang, Benqi Zhao, Zhuozhao Zheng, Xiaowei He, Xiaolei Song   +5 more
doaj   +1 more source