Results 61 to 70 of about 71,655 (241)

Deep segmentation networks predict survival of non-small cell lung cancer [PDF]

, 2019
Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography-computed
Allen, Bryan, Baek, Stephen, Baek, Stephen, Buatti, John, Cabel, Katherine, Diehn, Maximilian, Gannon, Maggie, He, Yusen, Kim, Yusung, Loo, Billy, Plichta, Kristin, Seyedin, Steven, Smith, Brian, Sun, Zhiyu, Tong, Ling, Wu, Jia, Wu, Xiaodong   +16 more
core   +2 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

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, Bavitz, Kyle, Du, Qian, Hollingsworth, Michael, Kamal, Ahsan, Liang, Xiaoying, Lin, Chi, McAlister, Josiah, Parr, Elsa, Rux, Gerard, Zhang, Chi, Zheng, Dandan   +11 more
core   +1 more source

A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer. [PDF]

, 2016
Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts.
Echegaray, Sebastian, Gevaert, Olivier, Kadoch, Michael, Leung, Ann, Nair, Viswam, Napel, Sandy, Rubin, Daniel   +6 more
core   +1 more source

Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential

Frontiers in Oncology, 2022
The high-throughput extraction of quantitative imaging features from medical images for the purpose of radiomic analysis, i.e., radiomics in a broad sense, is a rapidly developing and emerging research field that has been attracting increasing interest ...
Xing-wei Zhang, Yanchun Zhang, Guijuan Zhang, Xingting Qiu, Wenjun Tan, Xiaoxia Yin, Liefa Liao   +6 more
semanticscholar   +1 more source

Prediction of pre-eclampsia by using radiomics nomogram from gestational hypertension patients

Frontiers in Neuroscience, 2022
BackgroundPre-eclampsia (PE) is the main cause of death in maternal and prenatal morbidity. No effective clinical tools could be used for the prediction of PE.
Xue-Fei Liu, Jing-Jing Lu, Meng-Die Li, Ying Li, An-Rong Zeng, Jin-Wei Qiang   +5 more
doaj   +1 more source

Moddicom: a Complete and Easily Accessible Library for Prognostic Evaluations Relying on Image Features [PDF]

, 2015
Decision Support Systems (DSSs) are increasingly exploited in the area of prognostic evaluations. For predicting the effect of therapies on patients, the trend is now to use image features, i.e.
Alitto, Anna Rita, Autorino, Rosa, Boldrini, Luca, Damiani, Andrea, Dinapoli, Nicola, Gatta, Roberto, Valentini, Vincenzo, Vallati, Mauro   +7 more
core   +1 more source

Machine and deep learning methods for radiomics.

Medical Physics (Lancaster), 2020
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints.
M. Avanzo, Lise Wei, J. Stancanello, M. Vallières, A. Rao, O. Morin, S. Mattonen, I. E. El Naqa   +7 more
semanticscholar   +1 more source

Radiomics in prostate cancer: an up-to-date review

Therapeutic Advances in Urology, 2022
Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach.
M. Ferro, O. de Cobelli, G. Musi, F. del Giudice, G. Carrieri, G. Busetto, U. Falagario, A. Sciarra, M. Maggi, F. Crocetto, B. Barone, V. Caputo, M. Marchioni, G. Lucarelli, C. Imbimbo, F. Mistretta, S. Luzzago, M. Vartolomei, L. Cormio, R. Autorino, O. Tătaru   +20 more
semanticscholar   +1 more source

Feasibility of using CT radiomic signatures for predicting CD8-T cell infiltration and PD-L1 expression in renal cell carcinoma

European Journal of Radiology Open, 2022
Objectives: To identify computed tomography (CT)-based radiomic signatures of cluster of differentiation 8 (CD8)-T cell infiltration and programmed cell death ligand 1 (PD-L1) expression levels in patients with clear-cell renal cell carcinoma (ccRCC ...
Bino Varghese, Steven Cen, Haris Zahoor, Imran Siddiqui, Manju Aron, Akash Sali, Suhn Rhie, Xiaomeng Lei, Marielena Rivas, Derek Liu, Darryl Hwang, David Quinn, Mihir Desai, Ulka Vaishampayan, Inderbir Gill, Vinay Duddalwar   +15 more
doaj