Results 61 to 70 of about 82,903 (262)

Highly accurate model for prediction of lung nodule malignancy with CT scans [PDF]

, 2018
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer.
Causey, Jason L., Huang, Xiuzhen, Jiang, Bo, Ma, Shiqian, Politte, David G., Prior, Fred, Qualls, Jake A., Zhang, Junyu, Zhang, Shuzhong   +8 more
core   +3 more sources

Radiomics in Spine Surgery

International Journal of Spine Surgery, 2023
Radiomics is an emerging approach to analyze clinical images with the purpose of revealing quantitative features that are unvisible to the naked eye. Radiomic features can be further combined with clinical data and genomic information to formulate prediction models using machine learning algorithms or manual statistical analysis.
Daniel, Alsoof, Christopher L, McDonald, Wesley M, Durand, Bassel G, Diebo, Eren O, Kuris, Alan H, Daniels   +5 more
openaire   +2 more sources

Radiomics Analysis for Predicting Epilepsy in Patients With Unruptured Brain Arteriovenous Malformations

Frontiers in Neurology, 2021
Objectives: To investigate the association between radiomics features and epilepsy in patients with unruptured brain arteriovenous malformations (bAVMs) and to develop a prediction model based on radiomics features and clinical characteristics for bAVM ...
Shaozhi Zhao, Shaozhi Zhao, Qi Zhao, Yuming Jiao, Yuming Jiao, Hao Li, Hao Li, Jiancong Weng, Jiancong Weng, Ran Huo, Ran Huo, Jie Wang, Jie Wang, Hongyuan Xu, Hongyuan Xu, Junze Zhang, Junze Zhang, Yan Li, Zhenzhou Wu, Shuo Wang, Shuo Wang, Yong Cao, Yong Cao, Jizong Zhao, Jizong Zhao   +24 more
doaj   +1 more source

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 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

Radiomics in cervical and endometrial cancer

The British Journal of Radiology, 2021
Radiomics is an emerging field of research that aims to find associations between quantitative information extracted from imaging examinations and clinical data to support the best clinical decision. In the last few years, some papers have been evaluating the role of radiomics in gynecological malignancies, mainly focusing on ovarian cancer ...
Manganaro L., Nicolino G. M., Dolciami M., Martorana F., Stathis A., Colombo I., Rizzo S.   +6 more
openaire   +3 more sources

QuantImage v2: a comprehensive and integrated physician-centered cloud platform for radiomics and machine learning research

European Radiology Experimental, 2023
Background Radiomics, the field of image-based computational medical biomarker research, has experienced rapid growth over the past decade due to its potential to revolutionize the development of personalized decision support models. However, despite its
Daniel Abler, Roger Schaer, Valentin Oreiller, Himanshu Verma, Julien Reichenbach, Orfeas Aidonopoulos, Florian Evéquoz, Mario Jreige, John O. Prior, Adrien Depeursinge   +9 more
doaj   +1 more source

Uncontrolled Confounders May Lead to False or Overvalued Radiomics Signature: A Proof of Concept Using Survival Analysis in a Multicenter Cohort of Kidney Cancer

Frontiers in Oncology, 2021
PurposeWe aimed to explore potential confounders of prognostic radiomics signature predicting survival outcomes in clear cell renal cell carcinoma (ccRCC) patients and demonstrate how to control for them.Materials and MethodsPreoperative contrast ...
Lin Lu, Firas S. Ahmed, Oguz Akin, Lyndon Luk, Xiaotao Guo, Hao Yang, Jin Yoon, A. Aari Hakimi, Lawrence H. Schwartz, Binsheng Zhao   +9 more
doaj   +1 more source

Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer

, 2017
Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk assessment and the quantification of intratumoural heterogeneity. In this
Aerts, Hugo J. W. L., Furstoss, Christophe, Kay-Rivest, Emily, Khaouam, Nader, Liem, Xavier, Naqa, Issam El, Nguyen-Tan, Phuc Felix, Perrin, Léo Jean, Seuntjens, Jan, Sultanem, Khalil, Vallières, Martin, Wang, Chang-Shu   +11 more
core   +2 more sources

Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software. [PDF]

, 2017
ObjectiveThe purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software.Materials and methodsMR images of 45 ...
Jamshidi, Neema, Kim, Jong Hyo, Kuo, Michael D, Lee, Myungeun, Woo, Boyeong   +4 more
core   +1 more source