Radiomics: the process and the challenges

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Items 201–300 of 1,000

1. Preoperative prediction of cavernous sinus invasion by pituitary adenomas using a radiomics method based on magnetic resonance images
   Jianxing Niu, Shuaitong Zhang, Shunchang Ma, Jinfu Diao, Wenjianlong Zhou, Jie Tian, Yali Zang, Wang Jia · 2018 · European Radiology
2. 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
3. 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
4. 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
5. Clinical Utility of Quantitative Imaging
   Andrew B. Rosenkrantz, Mishal Mendiratta‐Lala, Brian J. Bartholmai, Dhakshinamoorthy Ganeshan, Richard Glenn Abramson, Kirsteen R. Burton, John‐Paul J. Yu, Ernest M. Scalzetti, Thomas E. Yankeelov, Rathan M. Subramaniam et al. · 2014 · Academic Radiology
6. Non-small cell lung carcinoma histopathological subtype phenotyping using high-dimensional multinomial multiclass CT radiomics signature
   Zahra Khodabakhshi, Shayan Mostafaei, Hossein Arabi, Mehrdad Oveisi, Isaac Shiri, Habib Zaidi · 2021 · Computers in Biology and Medicine
7. Optimal co-clinical radiomics: Sensitivity of radiomic features to tumour volume, image noise and resolution in co-clinical T1-weighted and T2-weighted magnetic resonance imaging
   Sudipta Singha Roy, Timothy Whitehead, James D. Quirk, Amber R. Salter, Foluso Olabisi Ademuyiwa, Shunqiang Li, Hongyu An, Kooresh Isaac Shoghi · 2020 · EBioMedicine
8. Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT
   Elizabeth Huynh, Thibaud P. Coroller, Vivek Narayan, Vishesh Agrawal, John Romano, Idalid “Ivy” Franco, Chintan Parmar, Ying Hou, Raymond H. Mak, Hugo J.W.L. Aerts · 2017 · PLoS ONE
9. Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)
   European Society of Radiology, Nandita M. deSouza, Eric Achten, Ángel Alberich‐Bayarri, Fabian Bamberg, Ronald Boellaard, Olivier Clémеnt, Laure S Fournier, Ferdia Aidan Gallagher, Xavier Golay et al. · 2019 · Insights into Imaging
10. Predicting Malignancy in Thyroid Nodules: Radiomics Score Versus 2017 American College of Radiology Thyroid Imaging, Reporting and Data System
    Jinyu Liang, Xiao-wen Huang, Hangtong Hu, Yihao Liu, Qian Zhou, Qinghua Cao, Wei Wang, Baoxian Liu, Yanling Zheng, Xin Li et al. · 2018 · Thyroid
11. Optimizing Neuro-Oncology Imaging: A Review of Deep Learning Approaches for Glioma Imaging
    Madeleine Shaver, Paul A. Kohanteb, Catherine Chiou, Michelle D. Bardis, Chanon Chantaduly, Daniela Annenelie Bota, Christopher G. Filippi, Brent D. Weinberg, Jack Grinband, Daniel S. Chow et al. · 2019 · Cancers
12. Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives
    Davide Cusumano, Luca Boldrini, Jennifer Dhont, Claudio Fiorino, Olga Green, Görkem Güngör, N. Jornet, Sebastian Klüter, Guillaume Landry, Gian Carlo Mattiucci et al. · 2021 · Physica Medica
13. Radiomics based on multicontrast MRI can precisely differentiate among glioma subtypes and predict tumour-proliferative behaviour
    Changliang Su, Jingjing Jiang, Shun Zhang, Jingjing Shi, Kaibin Xu, Nanxi Shen, Jiaxuan Zhang, Li Li, Lingyun Zhao, Ju Zhang et al. · 2018 · European Radiology
14. The role of texture analysis in imaging as an outcome predictor and potential tool in radiotherapy treatment planning
    Sheaka Alobaidli, Sarah J. McQuaid, C. South, Vineet Prakash, Philip Evans, A. Nisbet · 2014 · British Journal of Radiology
15. Impact of Preprocessing and Harmonization Methods on the Removal of Scanner Effects in Brain MRI Radiomic Features
    Yingping Li, Samy Ammari, Corinne Balleyguier, Nathalie Lassau, Émilie Chouzenoux · 2021 · Cancers
16. Radiomics in precision medicine for gastric cancer: opportunities and challenges
    Qiuying Chen, Lu Zhang, Shuyi Liu, Jingjing You, Luyan Chen, Zhe Jin, Shuixing Zhang, Bin Zhang · 2022 · European Radiology
17. Sparse Representation-Based Radiomics for the Diagnosis of Brain Tumors
    Guoqing Wu, Yinsheng Chen, Yuanyuan Wang, Jinhua Yu, Xiaofei Lv, Xue Ju, Zhifeng Shi, Liang Chen, Zhongping Chen · 2017 · IEEE Transactions on Medical Imaging
18. Metabolic Tumor Volume Metrics in Lymphoma
    Lale Kostakoğlu, Stéphane Chauvie · 2017 · Seminars in Nuclear Medicine
19. Hepatic tumor classification using texture and topology analysis of non-contrast-enhanced three-dimensional T1-weighted MR images with a radiomics approach
    Asuka Oyama, Yasuaki Hiraoka, Ippei Obayashi, Yusuke Saikawa, Shigeru Furui, Kenshiro Shiraishi, Shinobu Kumagai, Tatsuya Hayashi, J. Kotoku · 2019 · Scientific Reports
20. Radiomics feature robustness as measured using an MRI phantom
    Joonsang Lee, Angela Steinmann, Yao Ding, Hannah J. Lee, Constance A. Owens, Jihong Wang, Jinzhong Yang, David S Followill, Rachel B. Ger, Dennis Mackin et al. · 2021 · Scientific Reports
21. Relationship between Glioblastoma Heterogeneity and Survival Time: An MR Imaging Texture Analysis
    Yang Liu, Xiaopan Xu, Lulu Yin, Xi Zhang, Lihong C. Li, Hongbing Lu · 2017 · American Journal of Neuroradiology
22. Development and clinical application of radiomics in lung cancer
    Bojiang Chen, Rui Zhang, Yuncui Gan, Lan Yang, Weimin Li · 2017 · Radiation Oncology
23. Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic Review
    Amit Jethanandani, Timothy A. Lin, Stefania Volpe, Hesham M. Elhalawani, Abdallah Mohamed, Pei Yang, Clifton David Fuller · 2018 · Frontiers in Oncology
24. Breast cancer Ki67 expression prediction by DCE-MRI radiomics features
    Wenjuan Ma, Yu Ji, Lisha Qi, Xiaojing Guo, Xiaojie Jian, P. Liu · 2018 · Clinical Radiology
25. Unsupervised machine learning of radiomic features for predicting treatment response and overall survival of early stage non-small cell lung cancer patients treated with stereotactic body radiation therapy
    Hongming Li, Maya Galperin-Aizenberg, Daniel A. Pryma, Charles B. Simone, Yong Fan A · 2018 · Radiotherapy and Oncology
26. MRI radiomics analysis for predicting preoperative synchronous distant metastasis in patients with rectal cancer
    Huanhuan Liu, Caiyuan Zhang, Lijun Wang, Ran Luo, Jinning Li, Hui Wen Zheng, Qiufeng Yin, Zhongyang Zhang, Shaofeng Duan, Xin Shane Li et al. · 2018 · European Radiology
27. Radiomics in radiooncology – challenging the medical physicist
    Peeken, Jan C., Bernhofer, Michael, Wiestler, Benedikt, Goldberg, Tatyana, Cremers, Daniel, Rost, Burkhard, Wilkens, Jan J., Combs, Stephanie E., Nüsslin, Fridtjof · 2018 · Physica Medica
28. Radiomics for Response and Outcome Assessment for Non-Small Cell Lung Cancer
    Liting Shi, Yaoyao He, Zilong Yuan, Stanley Benedict, Richard Kenneth Valicenti, Jianfeng Qiu, Yi Rong · 2018 · Technology in Cancer Research & Treatment
29. Robustness of radiomic features in magnetic resonance imaging: review and a phantom study
    Renee F. Cattell, Shenglan Chen, Chuan Huang · 2019 · Visual Computing for Industry Biomedicine and Art
30. Using ultrasound features and radiomics analysis to predict lymph node metastasis in patients with thyroid cancer
    Fu Li, Denghua Pan, Yun He, Yuquan Wu, Jin‐Bo Peng, Jiehua Li, Ye Wang, Hong Yang, Junqiang Chen · 2020 · BMC Surgery
31. Computed tomography-based radiomics decodes prognostic and molecular differences in interstitial lung disease related to systemic sclerosis
    Janine Gote-Schniering, Małgorzata Maciukiewicz, Hubert Szymon Gabryś, Matthias Brunner, Christian Blüthgen, C. Meier, Sophie Braga-Lagache, Anne‐Christine Uldry, Manfred Heller, Oliver Distler et al. · 2021 · European Respiratory Journal
32. Cardiac magnetic resonance radiomics: basic principles and clinical perspectives
    Zahra Raisi‐Estabragh, Cristian Izquierdo, Víctor M. Campello, Carlos Martín-Isla, Arjun Jaggi, Nicholas C. Harvey, Karim Lekadir, Steffen Erhard Petersen · 2020 · European Heart Journal - Cardiovascular Imaging
33. Radiomics in Stroke Neuroimaging: Techniques, Applications, and Challenges
    Qian Chen, Tianyi Xia, Mingyue Zhang, Nengzhi Xia, Jinjin Liu, Yunjun Yang · 2021 · Aging and Disease
34. Cochlea CT radiomics predicts chemoradiotherapy induced sensorineural hearing loss in head and neck cancer patients: A machine learning and multi-variable modelling study
    Hamid Abdollahi, Shayan Mostafaei, Susan Cheraghi, Isaac Shiri, Seied Rabi Mahdavi, Anoshirvan Kazemnejad · 2018 · Physica Medica
35. A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules
    Tingdan Hu, Sheng-Ping Wang, Lv Huang, Jia-Zhou Wang, De-Bing Shi, Yuan Li, Tong Tong, Weijun Peng · 2018 · European Radiology
36. Radiomic signature as a predictive factor for lymph node metastasis in early‐stage cervical cancer
    Yangyang Kan, Di Dong, Yuchen Zhang, Wenyan Jiang, Nannan Zhao, Lu Han, Mengjie Fang, Yali Zang, Chaoen Hu, Jie Tian et al. · 2018 · Journal of Magnetic Resonance Imaging
37. Machine learning-based analysis of CT radiomics model for prediction of colorectal metachronous liver metastases
    Marjaneh Taghavi, Stefano Trebeschi, Rita Simões, David B. Meek, Rianne C.J. Beckers, Doenja M. J. Lambregts, Cornelis Kees Verhoef, Janneke B. Houwers, Uulke A. van der Heide, Regina G. H. Beets‐Tan et al. · 2020 · Abdominal Radiology
38. Deep Radiomic Analysis of MRI Related to Alzheimer’s Disease
    Ahmad Chaddad, Christian Desrosiers, Tamim Mohammad Niazi · 2018 · IEEE Access
39. Biobanks—A Platform for Scientific and Biomedical Research
    Kristina Akhmedovna Malsagova, Arthur Tigranovich Kopylov, Alexander A. Stepanov, Tatiana V. Butkova, Alexandra A. Sinitsyna, Alexander Izotov, Anna L. Kaysheva · 2020 · Diagnostics
40. Radiogenomics in Renal Cancer Management—Current Evidence and Future Prospects
    Matteo Ferro, Gennaro Musi, Michele Marchioni, Martina Maggi, Alessandro Veccia, Francesco Del Giudice, Biagio Barone, Felice Crocetto, Francesco M. Lasorsa, Alessandro Antonelli et al. · 2023 · International Journal of Molecular Sciences
41. CT texture analysis of lung adenocarcinoma: can Radiomic features be surrogate biomarkers for EGFR mutation statuses
    Dongdong Mei, Yan Luo, Yan Wang, Jingshan Gong · 2018 · Cancer Imaging
42. Radiomics analysis of multiparametric MRI for the preoperative evaluation of pathological grade in bladder cancer tumors
    Huanjun J. Wang, Daokun Hu, Haohua Yao, Mao-Dong Chen, Shurong Li, Haolin Chen, Junhang Luo, Yanqiu Feng, Yan Guo · 2019 · European Radiology
43. Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features
    Emmanuel Rios Velazquez, Raphael Meier, William D. Dunn, Brian Michael Alexander, Roland Wiest, Stefan Bauer, David A. Gutman, Mauricio Reyes, Hugo J.W.L. Aerts · 2015 · Scientific Reports
44. Standardization of imaging features for radiomics analysis
    Akihiro Haga, Wataru Takahashi, Shuri Aoki, Kanabu Nawa, Hideomi Yamashita, Osamu Abe, Keiichi Nakagawa · 2019 · The Journal of Medical Investigation
45. Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures
    Steven W. Mes, Floris H. P. van Velden, Boris Peltenburg, Carel F.W. Peeters, Dennis E. te Beest, Mark A. van de Wiel, Joost M. Mekke, Doriene C. Mulder, Roland M. Martens, Jonas A. Castelijns et al. · 2020 · European Radiology
46. 18F-FDG PET/CT metabolic tumor parameters and radiomics features in aggressive non-Hodgkin’s lymphoma as predictors of treatment outcome and survival
    Aatif Parvez, Noam Tau, Douglas Hussey, Manjula D. Maganti, Ur Metser · 2018 · Annals of Nuclear Medicine
47. Use of radiomic features and support vector machine to distinguish Parkinson’s disease cases from normal controls
    Yue Wu, Jiehui Jiang, Li Chen, Jiaying Lu, Jingjie Ge, Fengtao Liu, Jin‐Tai Yu, Wei Lin, Chuantao Zuo, Jian Wang · 2019 · Annals of Translational Medicine
48. Radiomics: a primer on high-throughput image phenotyping
    Kyle Jon Lafata, Yuqi Wang, Brandon Konkel, F.-F. Yin, Mustafa Rifaat Bashir · 2021 · Abdominal Radiology
49. Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening
    Saeed S. Alahmari, Dmitry Cherezov, Dmitry B. Goldgof, Lawrence Hall, Robert J. Gillies, Matthew B. Schabath · 2018 · IEEE Access
50. Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection
    Wuchao Li, Liwen Zhang, Chong Tian, Hui Song, Mengjie Fang, Chaoen Hu, Yali Zang, Ying Cao, Shiyuan Dai, Fang Wang et al. · 2018 · European Radiology
51. CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma
    Changsi Jiang, Yan Luo, Jialin Yuan, Shuyuan You, Zhiqiang Chen, Mingxiang Wu, Guangsuo Wang, Jingshan Gong · 2020 · European Radiology
52. Multiparametric MRI for characterization of the tumour microenvironment
    Emily Hoffmann, Max Masthoff, Wolfgang Gerhard Kunz, Max Seidensticker, Stefanie Bobe, Mirjam Gerwing, Wolfgang E. Berdel, Christoph Schliemann, Cornelius Faber, Moritz Wildgruber · 2024 · Nature Reviews Clinical Oncology
53. Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma
    Farzad Khalvati, Yucheng Zhang, Sameer Baig, Edrise M. Lobo-Mueller, Paul Jack Karanicolas, Steve Gallinger, Masoom A. Haider · 2019 · Scientific Reports
54. Radiomics in breast MRI: current progress toward clinical application in the era of artificial intelligence
    Hiroko Satake, Satoko Ishigaki, Rintaro Ito, Shinji Naganawa · 2021 · La radiologia medica
55. Role of imaging in the era of precision medicine
    Giardino, Angela, Gupta, Supriya, Olson, Emmi, Sepulveda, Karla, Lenchik, Leon, Ivanidze, Jana, Rakow-Penner, Rebecca, Patel, Midhir J., Subramaniam, Rathan M., Ganeshan, Dhakshinamoorthy · 2017 · Academic Radiology
56. Big Data and the Future of Radiology Informatics
    Akash P. Kansagra, John‐Paul J. Yu, Arindam Rano Chatterjee, Leon Lenchik, Daniel S. Chow, Adam B. Prater, Jean Yeh, Ankur M. Doshi, C. Matthew Hawkins, Marta Elise Heilbrun et al. · 2015 · Academic Radiology
57. A Triple‐Classification Radiomics Model for the Differentiation of Primary Chordoma, Giant Cell Tumor, and Metastatic Tumor of Sacrum Based on T2‐Weighted and Contrast‐Enhanced T1‐Weighted MRI
    Ping Yin, Ning Mao, Chao Zhao, Jiangfen Wu, Lei Chen, Nan Hong · 2018 · Journal of Magnetic Resonance Imaging
58. Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma
    Wei Lu, Lianzhen Zhong, Di Dong, Mengjie Fang, Qi Dai, Shaoyi Leng, Liwen Zhang, Wei Sun, Jie Tian, Jianjun Zheng et al. · 2019 · European Journal of Radiology
59. Early prediction of acute xerostomia during radiation therapy for nasopharyngeal cancer based on delta radiomics from CT images
    Yanxia Liu, Hongyu Shi, Sijuan Huang, Xiaochuan Chen, Huimin Zhou, Hui Chang, Yunfei Xia, Guohua Wang, Xin Yang · 2019 · Quantitative Imaging in Medicine and Surgery
60. Prediction early recurrence of hepatocellular carcinoma eligible for curative ablation using a Radiomics nomogram
    Chunwang Yuan, Zhenchang Wang, Dongsheng Gu, Jie Tian, Peng Zhao, Jingwei Wei, Xiaozhen Yang, Xiaohan Hao, Di Dong, Ning He et al. · 2019 · Cancer Imaging
61. Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI
    Nathan B. Gaw, Andrea J. Hawkins-Daarud, Leland Hu, Hyunsoo Yoon, Lujia Wang, Yanzhe Xu, Pamela Jackson, Kyle Singleton, Leslie C. Baxter, Jennifer Mary Eschbacher et al. · 2019 · Scientific Reports
62. Pancreas image mining: a systematic review of radiomics
    Bassam M. Abunahel, Beau P. Pontré, Haribalan Kumar, Maxim S. Petrov · 2020 · European Radiology
63. The impact of the variation of imaging parameters on the robustness of Computed Tomography radiomic features: A review
    Reza Reiazi, Engy Abbas, Petra Famiyeh, Aria Rezaie, Jennifer Y. Y. Kwan, Tirth Patel, Scott Victor Bratman, Tony Tadic, Fei‐Fei Liu, Benjamin Haibe‐Kains · 2021 · Computers in Biology and Medicine
64. Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis
    Evi J. van Kempen, Max Post, Manoj Mannil, Richard L. Witkam, Mark ter Laan, Ajay Patel, Frederick J. A. Meijer, Dylan Jozef Hendrik Augustinus Henssen · 2021 · European Radiology
65. Computer-Aided Diagnosis of Pancreas Serous Cystic Neoplasms: A Radiomics Method on Preoperative MDCT Images
    Ran Wei, Kanru Lin, Wenjun Yan, Yi Guo, Yuanyuan Wang, Ji Li, Jianqing Zhu · 2019 · Technology in Cancer Research & Treatment
66. Invasive ductal breast cancer: preoperative predict Ki-67 index based on radiomics of ADC maps
    Yu Zhang, Yifeng Zhu, Kai Zhang, Yajie Liu, Jingjing Cui, Juan Tao, Yingzi Wang, Shaowu Wang · 2019 · La radiologia medica
67. The Application of Radiomics in Breast MRI: A Review
    Dongman Ye, Haotian Wang, Tao Yu · 2020 · Technology in Cancer Research & Treatment
68. A field strength independent MR radiomics model to predict pathological complete response in locally advanced rectal cancer
    Davide Cusumano, Gert J. Meijer, Jacopo Lenkowicz, Giuditta Chiloiro, Luca Boldrini, Carlotta Masciocchi, N. Dinapoli, Roberto Gatta, Calogero Casà, Andrea Damiani et al. · 2020 · La radiologia medica
69. Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images
    Isaac Shiri, Mehdi Amini, Mostafa Nazari, Ghasem Hajianfar, Atlas Haddadi Avval, Hamid Abdollahi, Mehrdad Oveisi, Hossein Arabi, Arman Rahmim, Habib Zaidi · 2022 · Computers in Biology and Medicine
70. Radiologic Features of Small Pulmonary Nodules and Lung Cancer Risk in the National Lung Screening Trial: A Nested Case-Control Study
    Ying Liu, Hua X. Wang, Qian Li, Melissa J. McGettigan, Yoganand Balagurunathan, Alberto López García, Zachary Thompson, John Heine, Zhaoxiang Ye, Robert J. Gillies et al. · 2017 · Radiology
71. Radiomics analysis allows for precise prediction of epilepsy in patients with low-grade gliomas
    Zhenyu Liu, Yinyan Wang, Xing Liu, Yang Du, Zhenchao Tang, Kai Wang, Jingwei Wei, Di Dong, Yali Zang, Jianping Dai et al. · 2018 · NeuroImage Clinical
72. Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review
    Matteo Ferro, Felice Crocetto, Biagio Barone, Francesco Del Giudice, Martina Maggi, Giuseppe Tiziano Lucarelli, Gian Maria Busetto, Riccardo Autorino B, Michele Marchioni, Francesco Cantiello et al. · 2023 · Therapeutic Advances in Urology
73. Prediction of Cognitive Decline in Parkinson’s Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems
    Mahdi Hosseinzadeh, Arman Gorji, Ali Fathi Jouzdani, Seyed Masoud Rezaeijo, Arman Rahmim, Mohammad R. Salmanpour · 2023 · Diagnostics
74. Magnetic Resonance Imaging-Based Radiomic Profiles Predict Patient Prognosis in Newly Diagnosed Glioblastoma Before Therapy
    Sean D. McGarry, Sarah L. Hurrell, Amy L. Kaczmarowski, Elizabeth J. Cochran, Jennifer Connelly, Scott D. Rand, Kathleen M. Schmainda, Peter S. LaViolette · 2016 · Tomography
75. Machine Learning and Feature Selection Methods for Disease Classification With Application to Lung Cancer Screening Image Data
    Darcie A. P. Delzell, Sara Magnuson, Tabitha Peter, Michelle Smith, Brian J. Smith · 2019 · Frontiers in Oncology
76. A radiomics-based biomarker for cytokeratin 19 status of hepatocellular carcinoma with gadoxetic acid–enhanced MRI
    Wentao Wang, Dongsheng Gu, Jingwei Wei, Ying Ding, Li Yang, Kai Zhu, Rongkui Luo, Shengxiang Rao, Jie Tian, Mengsu Zeng · 2020 · European Radiology
77. MR image-based radiomics to differentiate type Ι and type ΙΙ epithelial ovarian cancers
    Junming Jian, Yongai Li, Perry Joseph Pickhardt, Wei Xia, He Zhang, Rui Zhang, Shuhui Zhao, Xingyu Zhao, Songqi Cai, Jiayi Zhang et al. · 2020 · European Radiology
78. The progress of multimodal imaging combination and subregion based radiomics research of cancers
    Luyuan Zhang, Yumin Wang, Zhouying Peng, Yuxiang Weng, Zebin Fang, Feng Xiao, Chao Zhang, Zuoxu Fan, Kaiyuan Huang, Yu Zhu et al. · 2022 · International Journal of Biological Sciences
79. Radiomics models for diagnosing microvascular invasion in hepatocellular carcinoma: which model is the best model?
    Ming Ni, Xiaoming Zhou, Qian Lv, Zhiming Li, Yuanxiang Gao, Yongqi Tan, Jihua Liu, Fang Liu, Haiyang Yu, Linlin Jiao et al. · 2019 · Cancer Imaging
80. Radiomics Based on Lumbar Spine Magnetic Resonance Imaging to Detect Osteoporosis
    Li He, Zhai Liu, Chunying Liu, Zhimei Gao, Qingyun Ren, Licun Lei, Jialiang Ren · 2020 · Academic Radiology
81. Fine-tuning convolutional deep features for MRI based brain tumor classification
    Kaoutar Ben Ahmed, Lawrence Hall, Dmitry B. Goldgof, Renhao Liu, Robert A. Gatenby · 2017 · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
82. 18F-FDG PET image biomarkers improve prediction of late radiation-induced xerostomia
    Lisanne Vania van Dijk, Walter Noordzij, Charlotte L. Brouwer, Ronald Boellaard, Johannes G. M. Burgerhof, Johannes Albertus Langendijk, Nanna Maria Sijtsema, Roel J.H.M. Steenbakkers · 2017 · Radiotherapy and Oncology
83. Integrating molecular nuclear imaging in clinical research to improve anticancer therapy
    Elisabeth G.E. de Vries, Laura Kist de Ruijter, Marjolijn N. Lub–de Hooge, Rudi A. J. O. Dierckx, Sjoerd Geert Elias, Sjoukje F. Oosting · 2018 · Nature Reviews Clinical Oncology
84. Radiomics for predicting hematoma expansion in patients with hypertensive intraparenchymal hematomas.
    Chao Ma, Yu-Peng Zhang, Tuerdialimu Niyazi, Jian Wei, Guo-Cai Guo, Jianan Liu, Shi-Kai Liang, F. Liang, P. Yan, Kun Wang et al. · 2019 · European Journal of Radiology
85. Integrating imaging and omics data: A review
    Laura Antonelli, Mario Rosario Guarracino, Lucia Maddalena, Mara Sangiovanni · 2019 · Biomedical Signal Processing and Control
86. Radiomics: A primer for the radiation oncologist
    Jean‐Emmanuel Bibault, Lei Xing, Philippe Giraud, Radouane El Ayachy, Nicolas Giraud, Pierre Decazes, Anita Burgun, Philippe Giraud · 2020 · Cancer/Radiothérapie
87. Peritumoral and intratumoral radiomic features predict survival outcomes among patients diagnosed in lung cancer screening
    Jaileene Pérez‐Morales, Ilke Tunali, Olya Stringfield, Steven A. Eschrich, Yoganand Balagurunathan, Robert J. Gillies, Matthew B. Schabath · 2020 · Scientific Reports
88. A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging
    Kaissis, Georgios, Ziegelmayer, Sebastian, Lohöfer, Fabian, Algül, Hana, Eiber, Matthias, Weichert, Wilko, Schmid, Roland, Friess, Helmut, Rummeny, Ernst, Ankerst, Donna et al. · 2019 · European Radiology Experimental
89. Deep learning for the fully automated segmentation of the inner ear on MRI
    Akshayaa Vaidyanathan, Marly F. J. A. van der Lubbe, Ralph T. H. Leijenaar, Marc van Hoof, Fadila Zerka, Benjamin Miraglio, Sergey P. Primakov, Alida Annechien Postma, Tjasse Doewe Bruintjes, Monique A. L. Bilderbeek-Beckers et al. · 2021 · Scientific Reports
90. A review on radiomics and the future of theranostics for patient selection in precision medicine
    Simon Andreas Keek, Ralph T. H. Leijenaar, Arthur Jochems, Henry C. Woodruff · 2018 · British Journal of Radiology
91. Noninvasive radiomics signature based on quantitative analysis of computed tomography images as a surrogate for microvascular invasion in hepatocellular carcinoma: a pilot study
    Shaimaa H. Bakr, Sebastian Echegaray, Rajesh P. Shah, Aya Kamaya, John D. Louie, Sandy A. Napel, Nishita Kothary, Olivier Gevaert · 2017 · Journal of medical imaging
92. The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II
    Wei Huang, Yiyi Chen, Andriy Fedorov, Xia Li, Guido H. Jajamovich, Dariya I. Malyarenko, Madhava P. Aryal, Peter S. LaViolette, Matthew J. Oborski, Finbarr O’Sullivan et al. · 2019 · Tomography
93. Radiomic analysis in contrast-enhanced CT: predict treatment response to chemoradiotherapy in esophageal carcinoma
    Zhen Hou, Wei Ren, Shuangshuang Li, Juan Liu, Sun Young Yu, Jing Yan, Suiren Wan · 2017 · Oncotarget
94. Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT
    Chia-Ying Lin, Shu‐Mei Guo, Jenn-Jier James Lien, Wen-Tsen Lin, Yi‐Sheng Liu, Chao‐Han Lai, I-Lin Hsu, Chao‐Chun Chang, Yau‐Lin Tseng · 2023 · La radiologia medica
95. Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT
    Rahul Paul, Samuel H. Hawkins, Lawrence Hall, Dmitry B. Goldgof, Robert J. Gillies · 2016 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
96. Biomarkers and Imaging of Breast Cancer
    Olena O. Weaver, Jessica W. T. Leung · 2017 · American Journal of Roentgenology
97. A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy
    Kaissis, Georgios, Ziegelmayer, Sebastian, Lohöfer, Fabian, Steiger, Katja, Algül, Hana, Muckenhuber, Alexander, Yen, Hsi-Yu, Rummeny, Ernst, Friess, Helmut, Schmid, Roland et al. · 2019 · PLOS ONE
98. Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas
    Yuqi Han, Zhen Xie, Yali Zang, Shuaitong Zhang, Dongsheng Gu, Mu Zhou, Olivier Gevaert, Jingwei Wei, Chao Li, Hongyan Chen et al. · 2018 · Journal of Neuro-Oncology
99. Radiomics prognostication model in glioblastoma using diffusion- and perfusion-weighted MRI
    Ji Eun Park, Ho Sung Kim, Youngheun Jo, Roh‐Eul Yoo, Seung Hong Choi, Soo Jung Nam, Jeong Hoon Kim · 2020 · Scientific Reports
100. Precision radiotherapy for non-small cell lung cancer
     Wen-Chi Yang, Feng‐Ming Hsu, Pan‐Chyr Yang · 2020 · Journal of Biomedical Science