Radiomics: the process and the challenges

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Items 301–400 of 1,000

1. Prognostic prediction of hypertensive intracerebral hemorrhage using CT radiomics and machine learning
   Xinghua Xu, Jiashu Zhang, Kai Ge Yang, Qun Wang, Xiaolei Chen, Bainan Xu · 2021 · Brain and Behavior
2. Effects of MRI scanner parameters on breast cancer radiomics
   Ashirbani Saha, Xiaozhi Yu, Dushyant Sahoo, Maciej A. Mazurowski · 2017 · Expert Systems with Applications
3. Feature selection methodology for longitudinal cone-beam CT radiomics
   Janita E. van Timmeren, Ralph T. H. Leijenaar, Wouter van Elmpt, Bart J.T. Reymen, Philippe Lambin · 2017 · Acta Oncologica
4. Radiomics: Principles and radiotherapy applications
   Isabelle Gardin, Vincent Grégoire, David Gibon, Hortense A. Kirişli, Dominique Pasquier, Juliette Thariat, Pierre Véra · 2019 · Critical Reviews in Oncology/Hematology
5. A Review of Radiomics and Deep Predictive Modeling in Glioma Characterization
   Sonal A. Gore, Tanay Chougule, Jayant Jagtap, Jitender S. Saini, Madhura Ingalhalikar · 2020 · Academic Radiology
6. CT-based radiomics for differentiating renal tumours: a systematic review
   Abhishta Bhandari, Muhammad Amin Ibrahim, Chinmay Sharma, Rebecca Liong, Sonja Gustafson, Marita Prior · 2020 · Abdominal Radiology
7. Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments
   Arman Rahmim, Yousef Salimpour, Saurabh Jain, Stephan A. L. Blinder, Ivan S. Klyuzhin, Gwenn S. Smith, Zoltan K. Mari, Vesna Sossi · 2016 · NeuroImage Clinical
8. The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest
   Yiping Lu, Li Liu, Shihai Luan, Ji Xiong, Daoying Geng, Bo Yin · 2018 · European Radiology
9. Systematic review and meta-analysis of the accuracy of 18F-FDG PET/CT for detection of regional lymph node metastasis in esophageal squamous cell carcinoma
   Chenxue Jiang, Yun Chen, Yaoyao Zhu, Yapping Xu · 2018 · Journal of Thoracic Disease
10. Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: Test–retest and image registration analyses
    Isaac Shiri, Ghasem Hajianfar, Ahmad Sohrabi, Hamid Abdollahi, Sajad P. Shayesteh, Parham Geramifar, Habib Zaidi, Mehrdad Oveisi, Arman Rahmim · 2020 · Medical Physics
11. Radiomics and radiogenomics in ovarian cancer: a literature review
    Stéphanie Nougaret, Cathal McCague, Hichem Tibermacine, Hebert Alberto Vargas, Stefania Rizzo, Evis Sala · 2020 · Abdominal Radiology
12. Machine Learning Algorithms for Predicting Surgical Outcomes after Colorectal Surgery: A Systematic Review
    Mustafa Bektaş, Jurriaan B. Tuynman, Jaime Costa Pereira, George Louis Burchell, Donald Leonard van der Peet · 2022 · World Journal of Surgery
13. Towards precision medicine: from quantitative imaging to radiomics
    U. Rajendra Acharya, Yuki Hagiwara, Vidya K. Sudarshan, Wai Yee Chan, Kwan Hoong Ng · 2018 · Journal of Zhejiang University SCIENCE B
14. Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer
    Constance A. Owens, Christine B. Peterson, Chad Z. Tang, Eugene Jon Koay, Wen Juan Yu, Dennis Mackin, Jing Li, Mohammad Salehpour, David Fuentes, Laurence Edward Court et al. · 2018 · PLoS ONE
15. Gold nanoparticle‐induced sonosensitization enhances the antitumor activity of ultrasound in colon tumor‐bearing mice
    Jaber Beik, Mohammad Bagher Shiran, Ziaeddin Abed, Isaac Shiri, Ali Ghadimi‐Daresajini, Forough Farkhondeh, Habib Ghaznavi, Ali Shakeri‐Zadeh · 2018 · Medical Physics
16. Radiomics and Digital Image Texture Analysis in Oncology (Review)
    Andrey Litvin, Dmitriy Burkin, A.A. Kropinov, Fedor Paramzin · 2021 · Современные технологии в медицине
17. Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals
    Shu-Cheng Liu, Jesyin Lai, Jhao-Yu Huang, Chia-Fong Cho, Pei Hua Lee, Min-Hsuan Lu, Chun‐Chieh Yeh, Jiaxin Yu, Wei‐Ching Lin · 2021 · Cancer Imaging
18. Radiomic features of pretreatment MRI could identify T stage in patients with rectal cancer: Preliminary findings
    Yiqun Sun, Panpan Hu, Jiazhou Wang, Lijun Shen, Fan Xia, Qing Yu Gan, Weigang Hu, Zhen Zhang, Chao Xin, Weijun Peng et al. · 2018 · Journal of Magnetic Resonance Imaging
19. Automated detection of hippocampal sclerosis using clinically empirical and radiomics features
    Jiajie Mo, Zhenyu Liu, Kai Sun, Yanshan Ma, Wenhan Hu, Chao Zhang, Yao Wang, Xiu Wang, Chang Liu, Baotian Zhao et al. · 2019 · Epilepsia
20. Additive manufacturing in radiation oncology: a review of clinical practice, emerging trends and research opportunities
    Rance Tino, Martin Leary, Adam Unjin Yeo, Elizabeth Kyriakou, Tomas Kron, Milan Brandt · 2020 · International Journal of Extreme Manufacturing
21. Muscle Composition Analysis of Ultrasound Images: A Narrative Review of Texture Analysis
    Michael T. Paris, Marina Mourtzakis · 2021 · Ultrasound in Medicine & Biology
22. Enhancing radiomics and Deep Learning systems through the standardization of medical imaging workflows
    Miriam Cobo, Pablo Menéndez Fernández‐Miranda, Gorka Bastarrika, L. Lloret Iglesias · 2023 · Scientific Data
23. Treatment response prediction using MRI-based pre-, post-, and delta-radiomic features and machine learning algorithms in colorectal cancer
    Shayesteh, Sajad, Nazari, Mostafa, Salahshour, Ali, Sandoughdaran, Saleh, Hajianfar, Ghasem, Khateri, Maziar, Yaghobi Joybari, Ali, Jozian, Fariba, Fatehi Feyzabad, Seyed Hasan, Arabi, Hossein et al. · 2021 · Medical Physics
24. Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?
    Bukowski, Mark, Farkas, Robert, Beyan, Oya, Moll, Lorna, Hahn, Horst, Kiessling, Fabian, Schmitz-Rode, Thomas · 2020 · European Radiology
25. Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation
    Yamashita, Rikiya, Perrin, Thomas, Chakraborty, Jayasree, Chou, Joanne F., Horvat, Natally, Koszalka, Maura A., Midya, Abhishek, Gonen, Mithat, Allen, Peter, Jarnagin, William R. et al. · 2020 · European Radiology
26. Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma
    Markand Dipankumar Patel, J. Zhan, Kal Natarajan, Robert Flintham, Nigel P. Davies, Paul Sanghera, James T. Grist, Vinay Anant Duddalwar, Andrew C. Peet, Vijay Sawlani · 2021 · Clinical Radiology
27. Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age
    Ahmad Chaddad, Christian Desrosiers, Matthew Toews · 2017 · Scientific Reports
28. MR-based radiomics signature in differentiating ocular adnexal lymphoma from idiopathic orbital inflammation
    Jian Guo, Zhenyu Liu, Chen Shen, Li Zheng, Fei Yan, Jie Tian, Junfang Xian · 2018 · European Radiology
29. Dual-Model Radiomic Biomarkers Predict Development of Mild Cognitive Impairment Progression to Alzheimer’s Disease
    Hucheng Zhou, Jiehui Jiang, Jiaying Lu, Min Wang, Huiwei Zhang, Chuantao Zuo, Alzheimer’s Disease Neuroimaging Initiative · 2019 · Frontiers in Neuroscience
30. Radiomics
    Pengpeng Xu, Yi Xue, Uwe Joseph Schoepf, Ákos Varga‐Szemes, Joseph P. Griffith, Basel Yacoub, Fan Zhou, Changsheng Zhou, Yuting Yang, Wei Xing et al. · 2021 · Circulation Cardiovascular Imaging
31. Evolutionary route of nasopharyngeal carcinoma metastasis and its clinical significance
    Lin Mei, Xiao-Long Zhang, Rui You, You‐Ping Liu, Hongmin Cai, Lizhi Liu, Xuefei Liu, Xiong Zou, Yu‐Long Xie, Ruhai Zou et al. · 2023 · Nature Communications
32. Imaging in metastatic breast cancer, CT, PET/CT, MRI, WB-DWI, CCA: review and new perspectives
    Dione Lother, Marie Robert, Elliot Elwood, Sam S. Smith, Nina Tunariu, Stephen R.D. Johnston, Marina Parton, Basrull Bhaludin, Thomas Millard, Kate Downey et al. · 2023 · Cancer Imaging
33. Fusion-based tensor radiomics using reproducible features: Application to survival prediction in head and neck cancer
    Mohammad R. Salmanpour, Mahdi Hosseinzadeh, Seyed Masoud Rezaeijo, Arman Rahmim · 2023 · Computer Methods and Programs in Biomedicine
34. 3D texture analysis for classification of second harmonic generation images of human ovarian cancer
    Bruce L. Wen, Kirby R. Campbell, Karissa Beth Tilbury, Oleg Nadiarnykh, MOLLY A. BREWER, Manish S. Patankar, Vikas Singh, Kevin W. Eliceiri, Paul J. Campagnola · 2016 · Scientific Reports
35. Artificial Intelligence in Radiation Therapy
    Yabo Fu, Hao Zhang, Eric D. Morris, Carri K. Glide‐Hurst, Suraj Pai, Alberto Traverso, Leonard Wee, Ibrahim Hadžić, Per-Ivar Lønne, Chenyang Shen et al. · 2021 · IEEE Transactions on Radiation and Plasma Medical Sciences
36. Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer
    Jeroen Bleker, Thomas Christian Kwee, Rudi A. J. O. Dierckx, Igle Jan de Jong, HenkJan J. Huisman, Derya Yakar · 2019 · European Radiology
37. Combining Molecular, Imaging, and Clinical Data Analysis for Predicting Cancer Prognosis
    Bárbara Lobato-Delgado, Blanca Priego, Daniel Morillo · 2022 · Cancers
38. Multi‐subtype classification model for non‐small cell lung cancer based on radiomics: SLS model
    Jian Liu, Jingjing Cui, Fei Liu, Yixuan Yuan, Feng Guo, Guanglei Zhang · 2019 · Medical Physics
39. Radiomic analysis of multiparametric magnetic resonance imaging for differentiating skull base chordoma and chondrosarcoma.
    Longfei Li, Ke Wang, Xiu-jian Ma, Zhen-Yu Liu, Shuo Wang, Jiang Du, Kaibing Tian, Xuezhi Zhou, Wei Wei, Kai Sun et al. · 2019 · European Journal of Radiology
40. “Radio-oncomics”
    Jan C. Peeken, Fridtjof Nüsslin, Stephanie Elisabeth Combs · 2017 · Strahlentherapie und Onkologie
41. CT-based radiomics scores predict response to neoadjuvant chemotherapy and survival in patients with gastric cancer
    Kaiyu Sun, Hang-Tong Hu, Shuling Chen, Jinning Ye, Guanghua Li, Li‐Da Chen, Jianjun Peng, Shi‐Ting Feng, Yujie Yuan, Xun Hou et al. · 2020 · BMC Cancer
42. AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging
    Fereshteh Yousefirizi, Pierre Decazes, Amine Amyar, Su Ruan, Babak Saboury, Arman Rahmim · 2021 · PET Clinics
43. A predictive model integrating deep and radiomics features based on gadobenate dimeglumine-enhanced MRI for postoperative early recurrence of hepatocellular carcinoma
    Wenyu Gao, Wentao Wang, Danjun Song, Chun Yang, Kai Zhu, Mengsu Zeng, Shengxiang Rao, Manning Wang · 2022 · La radiologia medica
44. International Union of Angiology (IUA) consensus paper on imaging strategies in atherosclerotic carotid artery imaging: From basic strategies to advanced approaches
    Luca Saba, Pier Luigi Antignani, Ajay Kumar Gupta, Riccardo Cau, Kosmas I. Paraskevas, Pavel Poredoš, Bruce Alan Wasserman, Hooman Kamel, Efthymios D. Avgerinos, Rodrigo A. Salgado et al. · 2022 · Atherosclerosis
45. Radiomics: A review of current applications and possibilities in the assessment of tumor microenvironment
    Caiqiang Xue, Qing Zhou, Huaze Xi, Junlin Zhou · 2022 · Diagnostic and Interventional Imaging
46. The Integration of Radiomics and Artificial Intelligence in Modern Medicine
    Antonino Maniaci, Salvatore Lavalle, Caterina Gagliano, Mario Lentini, Edoardo Masiello, Federica Maria Parisi, Giannicola Iannella, Nicole Dalia Cilia, Valerio Mario Salerno, Giacomo Cusumano et al. · 2024 · Life
47. CT-based Radiomics Signature to Discriminate High-grade From Low-grade Colorectal Adenocarcinoma
    Xiaomei Huang, Zixuan Cheng, Yanqi Huang, Cuishan Liang, Lan He, Zelan Ma, Xin Chen, Xiaomei Wu, Yexing Li, Changhong Liang et al. · 2018 · Academic Radiology
48. Radiomics: a novel feature extraction method for brain neuron degeneration disease using 18F-FDG PET imaging and its implementation for Alzheimer’s disease and mild cognitive impairment
    Yupeng Li, Jiehui Jiang, Jiaying Lu, Juanjuan Jiang, Huiwei Zhang, Chuantao Zuo · 2019 · Therapeutic Advances in Neurological Disorders
49. The Promise of Digital Biopsy for the Prediction of Tumor Molecular Features and Clinical Outcomes Associated With Immunotherapy
    G. Banna, T. Olivier, F. Rundo, U. Malapelle, F. Fraggetta, M. Libra, A. Addeo · 2019 · Frontiers in Medicine
50. Grading of Gliomas by Using Radiomic Features on Multiple Magnetic Resonance Imaging (MRI) Sequences
    Jiang-bo Qin, Zhenyu Liu, Hui Zhang, Chen Shen, Xiaochun Wang, Yan Qin Tan, Shuo Wang, Xiao-feng Wu, Jie Tian · 2017 · Medical Science Monitor
51. Radiomics performs comparable to morphologic assessment by expert radiologists for prediction of response to neoadjuvant chemoradiotherapy on baseline staging MRI in rectal cancer
    Joost J. M. van Griethuysen, Doenja M. J. Lambregts, Stefano Trebeschi, Max J. Lahaye, Frans C. H. Bakers, Roy F. A. Vliegen, Geerard L. Beets, Hugo J.W.L. Aerts, Regina G. H. Beets‐Tan · 2019 · Abdominal Radiology
52. CT-Based Radiomics Score for Distinguishing Between Grade 1 and Grade 2 Nonfunctioning Pancreatic Neuroendocrine Tumors
    Yun Bian, Hui Jiang, Chao Ma, Li Wang, Jianming Zheng, Gang Jin, Jianping Lu · 2020 · American Journal of Roentgenology
53. On the impact of smoothing and noise on robustness of CT and CBCT radiomics features for patients with head and neck cancers
    Hassan Bagher‐Ebadian, Farzan Siddiqui, Chang Liu, Benjamin Movsas, Indrin J. Chetty · 2017 · Medical Physics
54. Open access image repositories: high-quality data to enable machine learning research
    Fred Prior, Jonas S. Almeida, Pradeeban Kathiravelu, Tahsin Kurç, K. Smith, Thomas J. FitzGerald, Joel H. Saltz · 2019 · Clinical Radiology
55. Distributed radiomics as a signature validation study using the Personal Health Train infrastructure
    Zhenwei Shi, Ivan Zhovannik, Alberto Traverso, Frank J. W. M. Dankers, Timo M. Deist, Petros Kalendralis, René Monshouwer, Johan Bussink, Rianne Fijten, Hugo J.W.L. Aerts et al. · 2019 · Scientific Data
56. Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization
    David Molina, Julián Pérez-Beteta, Alicia Martínez‐González, Juan Martino, Carlos Velásquez, Estanislao Arana, Víctor M. Pérez‐García · 2017 · PLoS ONE
57. Comparison between Glioblastoma and Primary Central Nervous System Lymphoma Using MR Image-based Texture Analysis
    Akira Kunimatsu, Natsuko Kunimatsu, Kouhei Kamiya, Takeyuki Watadani, Harushi Mori, Osamu Abe · 2017 · Magnetic Resonance in Medical Sciences
58. Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges
    Stanzione, Arnaldo, Cuocolo, Renato, Ugga, Lorenzo, Verde, Francesco, Romeo, Valeria, Brunetti, Arturo, Maurea, Simone · 2022 · Cancers
59. Classification of Unmedicated Bipolar Disorder Using Whole-Brain Functional Activity and Connectivity: A Radiomics Analysis
    Ying Wang, Kai Sun, Zhenyu Liu, Guanmao Chen, Yanbin Jia, Shuming Zhong, Jiyang Pan, Li Huang, Jie Tian · 2019 · Cerebral Cortex
60. Multiple U-Net-Based Automatic Segmentations and Radiomics Feature Stability on Ultrasound Images for Patients With Ovarian Cancer
    Juebin Jin, Haiyan Zhu, Jindi Zhang, Yao Ai, Ji Zhang, Yinyan Teng, Congying Xie, Xiance Jin · 2021 · Frontiers in Oncology
61. Machine learning based on clinico-biological features integrated 18F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of lung
    Caiyue Ren, Jianping Zhang, Ming Qi, Jiangang Zhang, Yingjian Zhang, Shaoli Song, Yun Sun, Jingyi Cheng · 2020 · European Journal of Nuclear Medicine and Molecular Imaging
62. Clinlabomics: leveraging clinical laboratory data by data mining strategies
    Xiaoxia Wen, Ping Leng, Jiasi Wang, Guishu Yang, Ruiling Zu, Xiaojiong Jia, Kaijiong Zhang, Birga Anteneh Mengesha, Jian Hua Huang, Dongsheng Wang et al. · 2022 · BMC Bioinformatics
63. Core samples for radiomics features that are insensitive to tumor segmentation: method and pilot study using CT images of hepatocellular carcinoma
    Sebastian Echegaray, Olivier Gevaert, Rajesh P. Shah, Aya Kamaya, John D. Louie, Nishita Kothary, Sandy A. Napel · 2015 · Journal of medical imaging
64. Imaging in neuro-oncology
    Hari Nandu, Patrick Yung Wen, Raymond Y. Huang · 2018 · Therapeutic Advances in Neurological Disorders
65. Neuroendocrine neoplasia of the gastrointestinal tract revisited: towards precision medicine
    Guido Rindi, Bertram J. Wiedenmann · 2020 · Nature Reviews Endocrinology
66. Classification of early stage non-small cell lung cancers on computed tomographic images into histological types using radiomic features: interobserver delineation variability analysis
    Akihiro Haga, Wataru Takahashi, Shuri Aoki, Kanabu Nawa, Hideomi Yamashita, Osamu Abe, Keiichi Nakagawa · 2017 · Radiological Physics and Technology
67. NCTN Assessment on Current Applications of Radiomics in Oncology
    Ke Nie, Hania Al‐Hallaq, X. Allen Li, Stanley Benedict, Jason W. Sohn, Jean M. Moran, Yong Fan A, Mi Huang, Michael Vinzenz Knopp, Jeff M. Michalski et al. · 2019 · International Journal of Radiation Oncology*Biology*Physics
68. MRI-based radiomic signature as predictive marker for patients with head and neck squamous cell carcinoma
    Ying Yuan, Jiliang Ren, Yiqian Shi, Xiaofeng Tao · 2019 · European Journal of Radiology
69. Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging
    Vishwa S. Parekh, Michael A. Jacobs · 2020 · Breast Cancer Research and Treatment
70. Advanced quantitative methods in correlating sarcopenic muscle degeneration with lower extremity function biometrics and comorbidities
    Kyle Joseph Edmunds, Magnús Kjartan Gíslason, Sigurdur Oli Sigurdsson, Vilmundur G. Gudnason, Tamara B. Harris, Ugo Carraro, Paolo Gargiulo · 2018 · PLoS ONE
71. Brain Tumor Segmentation Using an Ensemble of 3D U-Nets and Overall Survival Prediction Using Radiomic Features
    Xue Feng, Nicholas James Tustison, Craig H. Meyer · 2019 · Lecture notes in computer science
72. Noncontrast Computed Tomography-Based Radiomics Analysis in Discriminating Early Hematoma Expansion after Spontaneous Intracerebral Hemorrhage
    Zuhua Song, Dajing Guo, Zhuoyue Tang, Huan Liu, Xin Li, Sha Luo, Xueying Yao, Wenlong Song, Junjie Song, Zhiming Zhou · 2020 · Korean Journal of Radiology
73. Artificial intelligence with deep learning in nuclear medicine and radiology
    Milan Decuyper, Jens Maebe, Roel Van Holen, Stefaan Vandenberghe · 2021 · EJNMMI Physics
74. Moddicom: a complete and easily accessible library for prognostic evaluations relying on image features
    N. Dinapoli, A.R. Alitto, Mauro Vallati, Roberto Gatta, Rosa Autorino, Luca Boldrini, Andrea Damiani, Vincenzo Valentini · 2015 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
75. Computer-aided Detection of Prostate Cancer with MRI
    Lizhi Liu, Zhiqiang Tian, Zhenfeng Zhang, Baowei Fei · 2016 · Academic Radiology
76. Radiomics and radiogenomics of prostate cancer
    Clayton P. Smith, Marcin Czarniecki, Sherif Mehralivand, Radka S. Stoyanova, Peter L. Choyke, Stephanie A. Harmon, Barış Türkbey · 2018 · Abdominal Radiology
77. A Systematic Review of PET Textural Analysis and Radiomics in Cancer
    Manuel Piñeiro-Fiel, Alexis Moscoso, Virginia Pubul Núñez, Á. Ruibal, Jesús Silva‐Rodríguez, Pablo Aguiar · 2021 · Diagnostics
78. CT-based radiomics features in the prediction of thyroid cartilage invasion from laryngeal and hypopharyngeal squamous cell carcinoma
    Ran Guo, Jian Guo, Lichen Zhang, Xiaoxia Qu, Shuangfeng Dai, Ruchen Peng, Vincent F Chong, Junfang Xian · 2020 · Cancer Imaging
79. Radiomics-Based Method for Predicting the Glioma Subtype as Defined by Tumor Grade, IDH Mutation, and 1p/19q Codeletion
    Yingping Li, Samy Ammari, Littisha Lawrance, Arnaud Quillent, Tarek Assi, Nathalie Lassau, Émilie Chouzenoux · 2022 · Cancers
80. The role of quantitative PET in predicting cancer treatment outcomes
    Issam El Naqa · 2014 · Clinical and Translational Imaging
81. An Update on Novel Quantitative Techniques in the Context of Evolving Whole-Body PET Imaging
    Sina Houshmand, Ali Salavati, Søren Hess, Thomas J. Werner, Abass A. Alavi, Habib Zaidi · 2014 · PET Clinics
82. Use of Radiomics Combined With Machine Learning Method in the Recurrence Patterns After Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma: A Preliminary Study
    Shuangshuang Li, Kongcheng Wang, Zhen Hou, Ju Yang, Wei Ren, Shanbao Gao, Fanyan Meng, Puyuan Wu, Baorui Liu, Juan Liu et al. · 2018 · Frontiers in Oncology
83. Radiomics Analysis for Clinical Decision Support in Nuclear Medicine
    Abdalla Ibrahim, Martin Vallières, Henry C. Woodruff, Sergey P. Primakov, Mohsen Beheshti, Simon Andreas Keek, Turkey Refaee, Sebastian Sanduleanu, Seán Walsh, Olivier Morin et al. · 2019 · Seminars in Nuclear Medicine
84. Prediction of outcome in anal squamous cell carcinoma using radiomic feature analysis of pre-treatment FDG PET-CT
    P. J. Brown, Jim Zhong, Russell Thomas Frood, Stuart Currie, Alexandra Gilbert, Ane Lindegaard Appelt, David Sebag‐Montefiore, Andrew Frederick Scarsbrook · 2019 · European Journal of Nuclear Medicine and Molecular Imaging
85. Towards Generation, Management, and Exploration of Combined Radiomics and Pathomics Datasets for Cancer Research.
    Joel Haskin Saltz, Jonas S. Almeida, Yi Gao, Ashish Sharma, Erich Bremer, Tammy DiPrima, Mary Morrison Saltz, Jayashree Kalpathy–Cramer, Tahsin Kurç · 2017 · PubMed Central
86. Radiomics in gliomas: clinical implications of computational modeling and fractal-based analysis
    Kevin Jang, Carlo Russo, Antonio Di Ieva · 2020 · Neuroradiology
87. Machine intelligence in non-invasive endocrine cancer diagnostics
    Nicole M. Thomasian, Ihab R. Kamel, Harrison Xiao Bai · 2021 · Nature Reviews Endocrinology
88. Diagnostic Accuracy of Deep Learning and Radiomics in Lung Cancer Staging: A Systematic Review and Meta-Analysis
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89. Random forest dissimilarity based multi-view learning for Radiomics application
    Hongliu Cao, Simon Bernard, Robert Sabourin, Laurent Heutte · 2018 · Pattern Recognition
90. Identification of the presence of ischaemic stroke lesions by means of texture analysis on brain magnetic resonance images
    Rafael Ortiz-Ramón, Maria del Carmen Valdés Hernández, Víctor González‐Castro, Stephen Makin, Paul A. Armitage, Benjamin S. Aribisala, Mark E. Bastin, Ian J. Deary, Joanna Marguerite Wardlaw, David Moratal · 2019 · Computerized Medical Imaging and Graphics
91. MRI-derived radiomics: methodology and clinical applications in the field of pelvic oncology
    Ulrike Schick, François Lucia, Gurvan Dissaux, Dimitris Visvikis, Bogdan Badic, Ingrid Masson, Olivier Pradier, Vincent Bourbonne, Mathieu Hatt · 2019 · British Journal of Radiology
92. Deep CNN Model Using CT Radiomics Feature Mapping Recognizes EGFR Gene Mutation Status of Lung Adenocarcinoma
    Baihua Zhang, Shouliang Qi, Xiaohuan Pan, Chen Li, Yudong Yao, Wei Qian, Yubao Guan · 2021 · Frontiers in Oncology
93. Influence of gray level and space discretization on brain tumor heterogeneity measures obtained from magnetic resonance images
    David Molina, Julián Pérez-Beteta, Alicia Martínez‐González, Juan Martino, Carlos Velásquez, Estanislao Arana, Víctor M. Pérez‐García · 2016 · Computers in Biology and Medicine
94. Radiomics in paediatric neuro‐oncology: A multicentre study on MRI texture analysis
    Ahmed E. Fetit, Jan Novák, Daniel Rodriguez Gutierrez, Dorothee P. Auer, Chris A. Clark, Richard Guy Grundy, Andrew C. Peet, Theodoros N. Arvanitis · 2017 · NMR in Biomedicine
95. Prediction of Response to Stereotactic Radiosurgery for Brain Metastases Using Convolutional Neural Networks
    Yu Jin Cha, Won Il Jang, Mi‐Sook Kim, Hyung Jun Yoo, Eun Kyung Paik, Hee Kyung Jeong, Sang-Min Youn · 2018 · Anticancer Research
96. Association of pre-treatment radiomic features with lung cancer recurrence following stereotactic body radiation therapy
    Kyle Jon Lafata, Julian C. Hong, Ruiqi Geng, Bradley G. Ackerson, Jian‐Guo Liu, Zhennan Zhou, Jordan A. Torok, Chris R. Kelsey, F.-F. Yin · 2018 · Physics in Medicine and Biology
97. Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole‐brain white matter
    Zhen-Yu Shu, Sijia Cui, Xiao Wu, Yu-Yun Xu, Pei-Yu Huang, P. Pang, Min-Ming Zhang · 2020 · Magnetic Resonance in Medicine
98. Relationship Between Radiomics and Risk of Lymph Node Metastasis in Pancreatic Ductal Adenocarcinoma
    Yun Bian, Shiwei Guo, Hui Jiang, Suizhi Gao, Chenwei Shao, Kai Cao, Xu Fang, Jing Li, Li Wang, Wenda Hua et al. · 2019 · Pancreas
99. Radiomics in Differentiated Thyroid Cancer and Nodules: Explorations, Application, and Limitations
    Yuan Cao, Xiao Zhong, Wei Diao, Jingshi Mu, Yue Cheng, Zhiyun Jia · 2021 · Cancers
100. Artificial Intelligence in Bariatric Surgery: Current Status and Future Perspectives
     Mustafa Bektaş, Beata M. M. Reiber, Jaime Costa Pereira, George Louis Burchell, Donald Leonard van der Peet · 2022 · Obesity Surgery