Radiomics: Images Are More than Pictures, They Are Data

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Items 301–400 of 1,034

1. Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer
   Davide Cusumano, N. Dinapoli, Luca Boldrini, Giuditta Chiloiro, Roberto Gatta, Carlotta Masciocchi, Jacopo Lenkowicz, Calogero Casà, Andrea Damiani, L. Azario et al. · 2017 · La radiologia medica
2. Radiomics in Oncological PET/CT: a Methodological Overview
   Seunggyun Ha, Hongyoon Choi, Jin Chul Paeng, Gi Jeong Cheon · 2019 · Nuclear Medicine and Molecular Imaging
3. Radiomics in Nuclear Medicine Applied to Radiation Therapy: Methods, Pitfalls, and Challenges
   Sylvain Reuzé, Antoine Schernberg, Fanny Orlhac, Roger Sun, Cyrus Chargari, Laurent Dercle, Éric Deutsch, Irène Buvat, Charlotte Robert · 2018 · International Journal of Radiation Oncology*Biology*Physics
4. The utility of quantitative CT radiomics features for improved prediction of radiation pneumonitis
   Shane Paul Krafft, Arvind U.K. Rao, Francesco C. Stingo, Tina Marie Briere, Laurence Edward Court, Zhongxing X. Liao, Mary K. Martel · 2018 · Medical Physics
5. How clinical imaging can assess cancer biology
   Roberto García‐Figueiras, Sandra Baleato‐González, Anwar R. Padhani, Antonio Luna, Juan Antonio Vallejo Casas, Evis Sala, Joan Carles Vilanova, Dow‐Mu Koh, Michel Herranz-Carnero, Herbert Alberto Vargas · 2019 · Insights into Imaging
6. Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning
   Wei Zhao, Jiancheng Yang, Bingbing Ni, Dexi Bi, Yingli Sun, Mengdi Xu, Xiaoxia Zhu, Cheng Li, Liang Jin, Pan Gao et al. · 2019 · Cancer Medicine
7. Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS
   Weiquan Luo, Qing-xiu Huang, Xiao-wen Huang, Hang-tong Hu, Fu-qiang Zeng, Wei Wang · 2019 · Scientific Reports
8. Prediction of cervical cancer recurrence using textural features extracted from 18F-FDG PET images acquired with different scanners
   Sylvain Reuzé, Fanny Orlhac, Cyrus Chargari, Christophe Nioche, Elaine Johanna Limkin, François Georges Riet, Alexandre Escande, Christine Haie-Méder, Laurent Dercle, Sébastien Gouy et al. · 2017 · Oncotarget
9. Radiomic signature of 18F fluorodeoxyglucose PET/CT for prediction of gastric cancer survival and chemotherapeutic benefits
   Yuming Jiang, Qingyu Yuan, Wenbing Lv, Sujuan Xi, Weicai Huang, Zepang Sun, Hao Chen, Liying Zhao, Wei Liu, Yanfeng Hu et al. · 2018 · Theranostics
10. A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis
    Lian Zou, Shaode Yu, Tiebao Meng, Zhicheng Zhang, Xiaokun Liang, Yaoqin Xie · 2019 · Computational and Mathematical Methods in Medicine
11. Progress and Future Trends in PET/CT and PET/MRI Molecular Imaging Approaches for Breast Cancer
    Yue Ming, Nan Wu, Tianyi Qian, Xiao Li, David Q. Wan, Cai‐Ying Li, Yalun Li, Zhihong Wu, Xiang Wang, Jiaqi Liu et al. · 2020 · Frontiers in Oncology
12. Application of radiomics-based multiomics combinations in the tumor microenvironment and cancer prognosis
    Wendi Kang, Xiang Qiu, Yingen Luo, Jianwei Luo, Yang Liu, Junqing Xi, Xiao Li, Zhengqiang Yang · 2023 · Journal of Translational Medicine
13. Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine
    Ilke Tunali, Robert J. Gillies, Matthew B. Schabath · 2021 · Cold Spring Harbor Perspectives in Medicine
14. Radiomics to predict immunotherapy-induced pneumonitis: proof of concept
    Colen, Rivka R., Fujii, Takeo, Bilen, Mehmet Asim, Kotrotsou, Aikaterini, Abrol, Srishti, Hess, Kenneth R., Hajjar, Joud, Suarez-Almazor, Maria E., Alshawa, Anas, Hong, David S. et al. · 2018 · Investigational New Drugs
15. A systematic review reporting quality of radiomics research in neuro-oncology: toward clinical utility and quality improvement using high-dimensional imaging features
    Park, Ji Eun, Kim, Ho Sung, Kim, Donghyun, Park, Seo Young, Kim, Jung Youn, Cho, Se Jin, Kim, Jeong Hoon · 2020 · BMC Cancer
16. Prostate Cancer Differentiation and Aggressiveness: Assessment With a Radiomic‐Based Model vs. PI‐RADS v2
    Tong Chen, Mengjuan Li, Yuefan Gu, Yueyue Zhang, Shuo Yang, Chaogang Wei, Jiangfen Wu, Xin Li, Wenlu Zhao, Junkang Shen · 2018 · Journal of Magnetic Resonance Imaging
17. Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer using tumor heterogeneity and angiogenesis properties on MRI
    Ji Young Lee, Kwang‐Sig Lee, Bo Kyoung Seo, Kyu Ran Cho, Ok Hee Woo, Sung Eun Song, Eun‐Kyung Kim, Hye Yoon Lee, Jung Sun Kim, Jaehyung Cha · 2021 · European Radiology
18. Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues
    Aleksandra M. Karolak, Dmitry A. Markov, Lisa J. McCawley, Katarzyna Anna Rejniak · 2018 · Journal of The Royal Society Interface
19. The predictive value of CT-based radiomics in differentiating indolent from invasive lung adenocarcinoma in patients with pulmonary nodules
    Yunlang She, Lei Zhang, Huiyuan Zhu, Chenyang Dai, Dong Xie, Huikang Xie, Wei Zhang, Lilan Zhao, Liling Zou, Ke Fei et al. · 2018 · European Radiology
20. Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics
    Rogier R. Wildeboer, Christophe K. Mannaerts, Ruud J. G. van Sloun, Lars Budäus, Derya Tilki A, Hessel Wijkstra, Georg Salomon, Massimo Mischi · 2019 · European Radiology
21. Development and validation of a MRI-based radiomics signature for prediction of KRAS mutation in rectal cancer
    Yanfen Cui, Huanhuan Liu, Jialiang Ren, Xiaosong Du, Lei Xin, Dandan Li, Xiaotang Yang, Dengbin Wang · 2020 · European Radiology
22. Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients
    Isaac Shiri, Majid Sorouri, Parham Geramifar, Mostafa Nazari, Mohammad Abdollahi, Yazdan Salimi, Bardia Khosravi, Dariush Askari, Leila Aghaghazvini, Ghasem Hajianfar et al. · 2021 · Computers in Biology and Medicine
23. Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study
    Saad, Maliazurina B, Hong, Lingzhi, Aminu, Muhammad, Vokes, Natalie I, Chen, Pingjun, Salehjahromi, Morteza, Qin, Kang, Sujit, Sheeba J, Lu, Xuetao, Young, Elliana et al. · 2023 · The Lancet Digital Health
24. Pediatric Brain Tumor Genetics: What Radiologists Need to Know
    Jehan AlRayahi, Michal Zápotocký, Vijay Ramaswamy, Prasad Baladev Hanagandi, Helen M. Branson, Walid Mabrouk Mubarak, Charles Raybaud, Suzanne Laughlin · 2018 · Radiographics
25. Repeatability and reproducibility study of radiomic features on a phantom and human cohort
    Ashish Kumar Jha, Sneha Mithun, Vinay Jaiswar, Umesh B. Sherkhane, Nilendu C. Purandare, Kumar Prabhash, Venkatesh Rangarajan, Andre L.A.J. Dekker, Leonard Wee, Alberto Traverso · 2021 · Scientific Reports
26. Assessing PD-L1 Expression Level by Radiomic Features From PET/CT in Nonsmall Cell Lung Cancer Patients: An Initial Result
    Mengmeng Jiang, Dazhen Sun, Yinglong Guo, Yixian Guo, Jie Xiao, Lisheng Wang, Xiuzhong Yao · 2019 · Academic Radiology
27. Impact of image preprocessing on the scanner dependence of multi-parametric MRI radiomic features and covariate shift in multi-institutional glioblastoma datasets
    Hyemin Um, Florent Tixier, Dalton H. Bermudez, Joseph O. Deasy, Robert J. Young, Harini Veeraraghavan · 2019 · Physics in Medicine and Biology
28. Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning–based radiomics
    Bing Mao, Lianzhong Zhang, Peigang Ning, Feng Hua Ding, Fatian Wu, Gary G. Lu, Yayuan Geng, Jingdong Ma · 2020 · European Radiology
29. Understanding Sources of Variation to Improve the Reproducibility of Radiomics
    Zhao, Binsheng · 2021 · Frontiers in Oncology
30. Associations between radiologist-defined semantic and automatically computed radiomic features in non-small cell lung cancer
    Stephen S. F. Yip, Ying Liu, Chintan Parmar, Qian Li, Shichang Liu, Fangyuan Qu, Zhaoxiang Ye, Robert J. Gillies, Hugo J.W.L. Aerts · 2017 · Scientific Reports
31. Radiomics Strategy for Molecular Subtype Stratification of Lower‐Grade Glioma: Detecting IDH and TP53 Mutations Based on Multimodal MRI
    Xi Zhang, Qiang Tian, Liang Wang, Yang Liu, Baojuan Li A, Zhengrong Liang, Peng Gao, Kaizhong Zheng, Bo-feng Zhao, Hongbing Lu · 2018 · Journal of Magnetic Resonance Imaging
32. Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis
    Wei Li, Yang Huang, Bowen Zhuang, Guangjian Liu, Hang-Tong Hu, Xin Li, Jinyu Liang, Zhu Wang, Xiao-wen Huang, Chu-Qing Zhang et al. · 2018 · European Radiology
33. Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning
    Márton Kolossváry, Carlo Nicola De Cecco, Gudrun Maria Feuchtner, Pál Maurovich‐Horvat · 2019 · Journal of cardiovascular computed tomography
34. Identification of high-risk carotid plaque with MRI-based radiomics and machine learning
    Ranying Zhang, Qingwei Zhang, Aihua Ji, Peng Lv, Jingjing Zhang, Caixia Fu, Jiang Lin · 2020 · European Radiology
35. Novel Nomogram for Preoperative Prediction of Early Recurrence in Intrahepatic Cholangiocarcinoma
    Wenjie Liang, Lei Xu, Pengfei Yang, Lele Zhang, Dalong Wan, Qiang Huang, Tianye Niu, Feng Chen · 2018 · Frontiers in Oncology
36. Predicting Survival Using Pretreatment CT for Patients With Hepatocellular Carcinoma Treated With Transarterial Chemoembolization: Comparison of Models Using Radiomics
    Jong‐Hoon Kim, Seung Joon Choi, Seung-Hak Lee, Ho Yun Lee, Hyunjin Park · 2018 · American Journal of Roentgenology
37. Prediction of Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma: A Radiomics Method Based on Preoperative Ultrasound Images
    Tongtong Liu, Shichong Zhou, Jinhua Yu, Yi Guo, Yuanyuan Wang, Jin Zhou, Cai Chang · 2019 · Technology in Cancer Research & Treatment
38. Radiomics in head and neck cancer: from exploration to application
    Andrew J. Wong, Aasheesh Kanwar, Abdallah Mohamed, Clifton David Fuller · 2016 · Translational Cancer Research
39. Radiomics: Data Are Also Images
    Mathieu Hatt, Catherine Cheze Le Rest, Florent Tixier, Bogdan Badic, Ulrike Schick, Dimitris Visvikis · 2019 · Journal of Nuclear Medicine
40. Radiomics in radiation oncology—basics, methods, and limitations
    Philipp Lohmann, Khaled Bousabarah, Mauritius Hoevels, Harald Treuer · 2020 · Strahlentherapie und Onkologie
41. Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune checkpoint blockade
    Pranjal Vaidya, K. Bera, P. Patil, Amit Gupta, P. Jain, M. Alilou, Mohammadhadi Khorrami, V. Velcheti, A. Madabhushi · 2020 · Journal for ImmunoTherapy of Cancer
42. Radiomics for the Prediction of Treatment Outcome and Survival in Patients With Colorectal Cancer: A Systematic Review
    Femke C.R. Staal, Denise J. van der Reijd, Marjaneh Taghavi, Doenja M. J. Lambregts, Regina G. H. Beets‐Tan, Monique Maas · 2020 · Clinical Colorectal Cancer
43. Understanding Changes in Tumor Texture Indices in PET: A Comparison Between Visual Assessment and Index Values in Simulated and Patient Data
    Fanny Orlhac, Christophe Nioche, Michaël Soussan, Irène Buvat · 2016 · Journal of Nuclear Medicine
44. Preoperative tumor texture analysis on MRI predicts high‐risk disease and reduced survival in endometrial cancer
    Sigmund Ytre‐Hauge, Julie Andrea Dybvik, Arvid Lundervold, Øyvind Olav Salvesen, Camilla Krakstad, Kristine Eldevik Fasmer, Henrica M.J. Werner, Balaji Ganeshan, Erling André Høivik, Line Bjørge et al. · 2018 · Journal of Magnetic Resonance Imaging
45. A Deep Look Into the Future of Quantitative Imaging in Oncology: A Statement of Working Principles and Proposal for Change
    Olivier Morin, Martin Vallières, Arthur Jochems, Henry C. Woodruff, Gilmer Valdés, Steve E. Braunstein, Joachim Ernst Wildberger, Javier E. Villanueva-Meyer, Vasant P. Kearney, Sue Sun Yom et al. · 2018 · International Journal of Radiation Oncology*Biology*Physics
46. Multiparametric MRI and radiomics in prostate cancer: a review
    Sun Young Yu, Hayley M. Reynolds, Bimal Kumar Parameswaran, Darren Wraith, Mary E. Finnegan, Scott Williams, Annette Haworth · 2019 · Australasian Physical & Engineering Sciences in Medicine
47. Deep learning: definition and perspectives for thoracic imaging
    Guillaume Chassagnon, Maria Vakalopolou, Nikos Paragios A, Marie‐Pierre Revel · 2019 · European Radiology
48. Radiomics-based machine learning model to predict risk of death within 5-years in clear cell renal cell carcinoma patients
    Mostafa Nazari, Isaac Shiri, Habib Zaidi · 2020 · Computers in Biology and Medicine
49. Development and Validation of a Novel Computed-Tomography Enterography Radiomic Approach for Characterization of Intestinal Fibrosis in Crohn’s Disease
    Xuehua Li, Liang Dong, Jixin Meng, Jie Zhou, Chen Zhao, Siyun Huang, Baolan Lu, Yun Qiu, Mark E. Baker, Ziyin Ye et al. · 2021 · Gastroenterology
50. Development of an Immune-Pathology Informed Radiomics Model for Non-Small Cell Lung Cancer
    Tang, Chad, Hobbs, Brian, Amer, Ahmed, Li, Xiao, Behrens, Carmen, Canales, Jaime Rodriguez, Cuentas, Edwin Parra, Villalobos, Pamela, Fried, David, Chang, Joe Y. et al. · 2018 · Scientific Reports
51. Unsupervised Clustering of Quantitative Image Phenotypes Reveals Breast Cancer Subtypes with Distinct Prognoses and Molecular Pathways
    Jia Wu, Yi Cui, Xiaoli Sun, Guohong Cao, Bailiang Li, Debra M. Ikeda, Allison W. Kurian, Ruijiang Li · 2017 · Clinical Cancer Research
52. CT-based radiomics signature for differentiating Borrmann type IV gastric cancer from primary gastric lymphoma
    Zelan Ma, Mengjie Fang, Yanqi Huang, Lan He, Xin Chen, Cuishan Liang, Xiaomei Huang, Zixuan Cheng, Di Dong, Changhong Liang et al. · 2017 · European Journal of Radiology
53. Analyzing the quality and challenges of uncertainty estimations for brain tumor segmentation
    Jungo, Alain, Balsiger, Fabian, Reyes, Mauricio · 2020 · Frontiers in Neuroscience
54. Radiomics as a personalized medicine tool in lung cancer: Separating the hope from the hype
    Isabella Fornacon-Wood, Corinne Faivre Finn, James P.B. O’Connor, Gareth J. Price · 2020 · Lung Cancer
55. Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics
    Bing Mao, Jingdong Ma, Shaobo Duan, Yuwei Xia, Yaru Tao, Lianzhong Zhang · 2021 · European Radiology
56. Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning–Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status
    Burak Koçak, Emine Şebnem Durmaz, Ece Ateş Kuş, Melis Baykara Ulusan · 2019 · American Journal of Roentgenology
57. Radiomics Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Prediction of Sentinel Lymph Node Metastasis in Breast Cancer
    Jia Liu, Dong Sun, Linli Chen, Fang Zheng, Weixiang Song, Dajing Guo, Tiangen Ni, Chuan Liu, Feng Lin, Yuwei Xia et al. · 2019 · Frontiers in Oncology
58. Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature
    Yiming Li, Xing Liu, Zenghui Qian, Zhiyan Sun, Kaibin Xu, Kai Wang, Xing Fan, Zhong Zhang, Shaowu Li, Yinyan Wang et al. · 2018 · European Radiology
59. Machine learning in cardiac CT: Basic concepts and contemporary data
    Gurpreet Singh, Subhi Jamal Alaref, Marly van Assen, Timothy Suyong Kim, Alexander van Rosendael, Kranthi K. Kolli, Aeshita Dwivedi, Gabriel Maliakal, Mohit Kumar Pandey, Jing Wang et al. · 2018 · Journal of cardiovascular computed tomography
60. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset
    Mingjie Xu, Shouliang Qi, Yong Yue, Yueyang Teng, Lisheng Xu, Yudong Yao, Wei Qian · 2019 · BioMedical Engineering OnLine
61. Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review
    Quinlan D. Buchlak, Nazanin Esmaili, Jean‐Christophe Leveque, Christine C. Bennett, Farrokh R. Farrokhi, Massimo Piccardi · 2021 · Journal of Clinical Neuroscience
62. Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab
    Patrick Großmann, Vivek Narayan, Ken Chang, Rifaquat M. Rahman, Lauren E. Abrey, David A. Reardon, Lawrence Howard Schwartz, Patrick Yung Wen, Brian Michael Alexander, Raymond Y. Huang et al. · 2017 · Neuro-Oncology
63. Evaluation of radiomic texture feature error due to MRI acquisition and reconstruction: A simulation study utilizing ground truth
    Fei Yang, Nesrin Dogan, Radka S. Stoyanova, John C. Ford · 2018 · Physica Medica
64. Radiomics nomogram outperforms size criteria in discriminating lymph node metastasis in resectable esophageal squamous cell carcinoma
    Xian-Zheng Tan, Zelan Ma, Lifen Yan, Weitao Ye, Zaiyi Liu, Changhong Liang · 2018 · European Radiology
65. Perfusion MRI in treatment evaluation of glioblastomas: Clinical relevance of current and future techniques
    Bart R. J. van Dijken, Peter Jan van Laar, Marion Smits, Jan Willem Dankbaar, Roelien H. Enting, Anouk van der Hoorn · 2018 · Journal of Magnetic Resonance Imaging
66. The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features
    Elaine Johanna Limkin, Sylvain Reuzé, Alexandre Carré, Roger Sun, Antoine Schernberg, Anthony Alexis, Éric Deutsch, Charles Ferté, Charlotte Robert · 2019 · Scientific Reports
67. Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer
    Feihong Yu, Jianxiang Wang, Xinhua Ye, Jing Deng, Jing Hang, Bin Yang · 2019 · European Journal of Radiology
68. Preoperative diagnosis of malignant pulmonary nodules in lung cancer screening with a radiomics nomogram
    Ailing Liu, Zhiheng Wang, Yachao Yang, Jingtao Wang, Xiaoyu Dai, Lijie Wang, Yuan Lu, Fuzhong Xue · 2020 · 癌症：英文版
69. Imaging approaches to optimize molecular therapies
    Ralph Weissleder, Markus C. Schwaiger, Sanjiv Sam Gambhir, Hedvig Hricak · 2016 · Science Translational Medicine
70. Radiomics in PET/CT: More Than Meets the Eye?
    Mathieu Hatt, Florent Tixier, Dimitris Visvikis, Catherine Cheze Le Rest · 2016 · Journal of Nuclear Medicine
71. Radiomics in stratification of pancreatic cystic lesions: Machine learning in action
    Vipin Dalal, Joseph Carmicheal, Amaninder Dhaliwal, Maneesh Jain, Sukhwinder Kaur, Surinder K. Batra · 2019 · Cancer Letters
72. Radiomics of Liver Metastases: A Systematic Review
    Francesco Fiz, Luca Viganò, Nicolò Gennaro, Guido Costa, Ludovico La Bella, Alexandra Boichuk, Lara Cavinato, Martina Sollini, Letterio Salvatore Politi, Arturo Chiti et al. · 2020 · Cancers
73. Deep learning and radiomics: The utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT
    Coy, Heidi, Hsieh, Kevin, Wu, Willie, Nagarajan, Mahesh B., Young, Jonathan R., Douek, Michael L., Brown, Matthew S., Scalzo, Fabien, Raman, Steven S. · 2019 · Abdominal Radiology
74. Imaging Phenotyping Using Radiomics to Predict Micropapillary Pattern within Lung Adenocarcinoma
    So Hee Song, Hyunjin Park, Geewon Lee, Ho Yun Lee, Insuk Sohn, Hye Seung Kim, Seung Hak Lee, Ji Yun Jeong, Jhingook Kim, Kyung Soo Lee et al. · 2016 · Journal of Thoracic Oncology
75. Renal cell carcinoma: the search for a reliable biomarker
    Nicholas J. Farber, Christopher J. Kim, Parth K. Modi, Jane Date Hon, Evita T. Sadimin, Eric A. Singer · 2017 · Translational Cancer Research
76. Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma
    Zhicheng Li, Hongmin Bai, Qiuchang Sun, Yuanshen Zhao, Yanchun Lv, Jian Hua Zhou, Chaofeng Liang, Yinsheng Chen, Dong Liang, Hairong Zheng · 2018 · Cancer Medicine
77. Radiomics-based prediction of microsatellite instability in colorectal cancer at initial computed tomography evaluation
    Jennifer S. Golia Pernicka, Johan Gagnière, Jayasree Chakraborty, Rikiya Yamashita, Lorenzo Nardo, John M. Creasy, Iva Petkovska, Richard R. K. Do, ‬David D. B. Bates, Viktoriya Paroder et al. · 2019 · Abdominal Radiology
78. Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer
    Yu‐Chun Lin, Chia‐Hung Lin, Hsin‐Ying Lu, Hsin-Ju Chiang, Ho-Kai Wang, Yu‐Ting Huang, Shu‐Hang Ng, Ji‐Hong Hong, Tzu‐Chen Yen, Chyong‐Huey Lai et al. · 2019 · European Radiology
79. Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review
    Seung-Hak Lee, Hyunjin Park, Eun Sook Ko · 2020 · Korean Journal of Radiology
80. Hippocampus and amygdala radiomic biomarkers for the study of autism spectrum disorder
    Ahmad Chaddad, Christian Desrosiers, Lama Hassan, Camel Tanougast · 2017 · BMC Neuroscience
81. Pattern Classification for Gastrointestinal Stromal Tumors by Integration of Radiomics and Deep Convolutional Features
    Zhenyuan Ning, Jiaxiu Luo, Yong Li, Shuai Han, Qianjin Feng, Yikai Xu, Wufan Chen, Tao Chen, Yu Zhang · 2018 · IEEE Journal of Biomedical and Health Informatics
82. A New Challenge for Radiologists: Radiomics in Breast Cancer
    Paola Crivelli, Roberta Eufrasia Ledda, Nicola Parascandolo, Alberto Fara, Daniela Soro, Maurizio Conti · 2018 · BioMed Research International
83. Differentiation of spinal metastases originated from lung and other cancers using radiomics and deep learning based on DCE-MRI
    Ning Lang, Yang Zhang, Enlong Zhang, Jiahui Zhang, Daniel S. Chow, Peter Chang, Hon J. Yu, Huishu Yuan, Min‐Ying Su · 2019 · Magnetic Resonance Imaging
84. A CT-based radiomics nomogram for differentiation of renal angiomyolipoma without visible fat from homogeneous clear cell renal cell carcinoma
    Pei Nie, Guangjie Yang, Zhenguang Wang, Lei Yan, Wenjie Miao, Dapeng Hao, Jie Wu, Yujun Zhao, Aidi Gong, Jingjing Cui et al. · 2019 · European Radiology
85. Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers
    Laure S Fournier, Lena I. Costaridou, Luc M. Bidaut, Nicolas Michoux, Frederic E. Lecouvet, Lioe‐Fee de Geus‐Oei, Ronald Boellaard, Daniela E. Oprea‐Lager, Nancy A. Obuchowski, Anna Caroli et al. · 2021 · European Radiology
86. Sonoelastomics for Breast Tumor Classification: A Radiomics Approach with Clustering-Based Feature Selection on Sonoelastography
    Qi Zhang, Yang Xiao, Jingfeng Suo, Jun Shi, Jinhua Yu, Yi Guo, Yuanyuan Wang, Hairong Zheng · 2017 · Ultrasound in Medicine & Biology
87. Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic resonance imaging
    Andrés Larroza, Andrzej Materka, María Pilar López-Lereu, Jose Vicente Monmeneu, Vicente Bodı́, David Moratal · 2017 · European Journal of Radiology
88. Quantitative Radiomics: Impact of Pulse Sequence Parameter Selection on MRI-Based Textural Features of the Brain
    John C. Ford, Nesrin Dogan, Lori A. Young, Fei Yang · 2018 · Contrast Media & Molecular Imaging
89. Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients
    Zhenyu Tang, Yuyun Xu, Lei Jin, Abudumijiti Aibaidula, Junfeng Lu, Zhicheng Jiao, Jinsong Wu, Han Zhang, Dinggang G. Shen · 2020 · IEEE Transactions on Medical Imaging
90. 18F-FDG PET/CT radiomic predictors of pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer patients
    Panli Li, Xiuying Wang, Chong‐Rui Xu, Cheng Liu, Chaojie Zheng, MICHAEL J. FULHAM, Dagan D. Feng, Lisheng Wang, Shaoli Song, Gang Huang · 2020 · European Journal of Nuclear Medicine and Molecular Imaging
91. Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study
    Bi Cong Yan, Ying Li, Hua Feng, Guofu Zhang, Feng Feng, Ming Hua Sun, Guang Wu Lin, Jinwei Qiang · 2020 · European Radiology
92. Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
    Braman, Nathaniel, Gordon, Jacob W. H., Goossens, Emery T., Willis, Caleb, Stumpe, Martin C., Venkataraman, Jagadish · 2021 · Lecture Notes in Computer Science
93. Artificial intelligence-based MRI radiomics and radiogenomics in glioma
    Haiqing Fan, Yilin Luo, Fang Gu, Bin Tian, Yongqin Xiong, Guipeng Wu, Xin Nie, Jing Yu, Juan Tong, Xin Liao · 2024 · Cancer Imaging
94. Building CT Radiomics Based Nomogram for Preoperative Esophageal Cancer Patients Lymph Node Metastasis Prediction
    Chen Shen, Zhenyu Liu, Zhaoqi Wang, Jia Guo, Hongkai Zhang, Yingshu Wang, Jianjun Qin, Hailiang Li, Mengjie Fang, Zhenchao Tang et al. · 2018 · Translational Oncology
95. MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively
    Zhicong Li, Hailin Li, Shiyu Wang, Di Dong, Fangfang Yin, An Chen, Siwen Wang, Guangming Zhao, Siwen Wang, Jie Tian et al. · 2018 · Journal of Magnetic Resonance Imaging
96. T2‐based MRI Delta‐radiomics improve response prediction in soft‐tissue sarcomas treated by neoadjuvant chemotherapy.
    Amandine Crombé, Cynthia Périer, Michèle Kind, Baudouin Denis de Senneville, François Le Loarer, Antoîne Italiano, Xavier Buy, Olivier Saut · 2018 · Journal of Magnetic Resonance Imaging
97. Artificial intelligence in radiology
    Luka Filipović-Grčić, Filip Đerke · 2019 · Rad Hrvatske akademije znanosti i umjetnosti Medicinske znanosti
98. MRI-based radiomics of rectal cancer: preoperative assessment of the pathological features
    Xiaolu Ma, Fu Shen, Yan Jia, Yuwei Xia, Qihua Li, Jianping Lu · 2019 · BMC Medical Imaging
99. A primer for understanding radiology articles about machine learning and deep learning
    Takeshi Nakaura, Toru Higaki, Kazuo Awai, Osamu Ikeda, Yasuyuki Yamashita · 2020 · Diagnostic and Interventional Imaging
100. Radiomic Analysis Reveals Prognostic Information in T1-Weighted Baseline Magnetic Resonance Imaging in Patients With Glioblastoma
     Michael Ingrisch, Moritz Jörg Schneider, Dominik Nörenberg, G. Negrão de Figueiredo, Klaus Hermann Maier-Hein, Bogdana Suchorska, Ulrich Schüller, Nathalie L. Albert, H. Brückmann, Maximilian Ferdinand Reiser et al. · 2017 · Investigative Radiology