Radiomics: Images Are More than Pictures, They Are Data

Gillies, Robert J., Kinahan, Paul E., Hricak, Hedvig·2016·Radiology

DOI 10.1148/radiol.2015151169

Cited by (1,034)

Items 601–700 of 1,034

Artificial Intelligence in Cardiology—A Narrative Review of Current Status
George Koulaouzidis, Tomasz Jadczyk, Dimitris K. Iakovidis, Anastasios Koulaouzidis, Marc Bisnaire, Dafni Charisopoulou · 2022 · Journal of Clinical Medicine
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
Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques
Mohammad R. Salmanpour, Seyed Masoud Rezaeijo, Mahdi Hosseinzadeh, Arman Rahmim · 2023 · Diagnostics
Making Molecular Imaging a Clinical Tool for Precision Oncology
David A. Mankoff, Michael D. Farwell, Amy Sanders Clark, Daniel A. Pryma · 2016 · JAMA Oncology
Role and future of MRI in radiation oncology
Indra J. Das, Kiaran P. McGee, Neelam Tyagi, Hesheng Wang · 2018 · British Journal of Radiology
Development and validation of a radiomics nomogram for identifying invasiveness of pulmonary adenocarcinomas appearing as subcentimeter ground-glass opacity nodules
Wei Zhao, Yanan Xu, Zhiming Yang, Yingli Sun, Cheng Li, Liang Jin, Pan Gao, Wenjie He, Peijun Wang, Hongli Shi et al. · 2019 · European Journal of Radiology
CT imaging features associated with recurrence in non-small cell lung cancer patients after stereotactic body radiotherapy
Qian Li, Jongphil Kim, Yoganand Balagurunathan, Jin Qi, Ying Liu, Kujtim Latifi, Eduardo G. Moros, Matthew B. Schabath, Zhaoxiang Ye, Robert J. Gillies et al. · 2017 · Radiation Oncology
Soft Tissue Sarcomas: Preoperative Predictive Histopathological Grading Based on Radiomics of MRI
Yu Zhang, Yifeng Zhu, Xiaomeng Shi, Juan Tao, Jingjing Cui, Yue Dai, Minting Zheng, Shaowu Wang · 2018 · Academic Radiology
Influence of segmentation margin on machine learning–based high-dimensional quantitative CT texture analysis: a reproducibility study on renal clear cell carcinomas
Burak Koçak, Ece Ateş Kuş, Emine Şebnem Durmaz, Melis Baykara Ulusan, Özgür Kılıçkesmez · 2019 · European Radiology
Unenhanced CT Texture Analysis of Clear Cell Renal Cell Carcinomas: A Machine Learning–Based Study for Predicting Histopathologic Nuclear Grade
Burak Koçak, Emine Şebnem Durmaz, Ece Ateş Kuş, Ozlem Korkmaz Kaya, Özgür Kılıçkesmez · 2019 · American Journal of Roentgenology
Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods
Rogier R. Wildeboer, Ruud J. G. van Sloun, Hessel Wijkstra, Massimo Mischi · 2020 · Computer Methods and Programs in Biomedicine
Radiomics analysis of dual-energy CT-derived iodine maps for diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer
Yan Zhou, Guo-Yi Su, Hao Hu, Yingqian Ge, Yan Si, Meiping Shen, Xiao‐Quan Xu, Fei‐Yun Wu · 2020 · European Radiology
MRI-Based radiomics nomogram for differentiation of benign and malignant lesions of the parotid gland
Ying-mei Zheng, Jian Li, Song Liu, Jiufa Cui, Jinfeng Zhan, Jing Pang, Ruizhi Zhou, Xiao-li Li, Cheng Dong · 2020 · European Radiology
Application of Machine Learning in Translational Medicine: Current Status and Future Opportunities
Nadia Terranova, Karthik Venkatakrishnan, Lisa Jo Benincosa · 2021 · The AAPS Journal
Radiomic Analysis: Study Design, Statistical Analysis, and Other Bias Mitigation Strategies
Chaya S. Moskowitz, Mattea L. Welch, Michael A. Jacobs, Brenda F. Kurland, Amber L. Simpson · 2022 · Radiology
Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis
Meng Liang, Zhengting Cai, Hongmei Zhang, Chencui Huang, Yankai Meng, Li Zhao, Deng‐Feng Li, Xiaohong Ma, Xinming Zhao · 2019 · Academic Radiology
Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success
Thomas E. Yankeelov, Gary C. An, Oliver Saut, E. Georg Luebeck, Aleksander S. Popel, Benjamin Ribba, Paolo Vicini, Xiaobo Zhou, Jared A. Weis, Kaiming Ye et al. · 2016 · Annals of Biomedical Engineering
Effect of machine learning methods on predicting NSCLC overall survival time based on Radiomics analysis
Wenzheng Sun, Mingyan Jiang, Jun Dang, Panchun Chang, F.-F. Yin · 2018 · Radiation Oncology
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
Integrating imaging and omics data: A review
Laura Antonelli, Mario Rosario Guarracino, Lucia Maddalena, Mara Sangiovanni · 2019 · Biomedical Signal Processing and Control
Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction
Yoon Seong Choi, Sung Soo Ahn, Jong Hee Chang, Seok‐Gu Kang, Eui Hyun Kim, Se Hoon Kim, Rajan Jain, Seung‐Koo Lee · 2020 · European Radiology
Artificial Intelligence Applications for Workflow, Process Optimization and Predictive Analytics
Laurent Letourneau Guillon, David Camirand, Francois Guilbert, Reza Forghani · 2020 · Neuroimaging Clinics of North America
Radiomics Study for Predicting the Expression of PD-L1 and Tumor Mutation Burden in Non-Small Cell Lung Cancer Based on CT Images and Clinicopathological Features
Qiang Wen, Zhe Yang, Honghai Dai, Alei Feng, Qiang Li · 2021 · Frontiers in Oncology
Artificial Intelligence in Thyroid Field—A Comprehensive Review
Fabiano Bini, Andrada Pica, Laura Azzimonti, Alessandro Giusti, Lorenzo Ruinelli, Franco Marinozzi, Pierpaolo Trimboli · 2021 · Cancers
Radiomics in neuro-oncological clinical trials
Philipp Lohmann, Enrico Franceschi, Philipp Vollmuth, Frederic G Dhermain, Michael Weller, Matthias Preusser, Marion Smits, Norbert Galldiks · 2022 · The Lancet Digital Health
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
Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy
Roberto Lo Gullo, Sarah Eskreis‐Winkler, Elizabeth Ann Morris, Katja Pinker · 2019 · The Breast
Prediction of age-related macular degeneration disease using a sequential deep learning approach on longitudinal SD-OCT imaging biomarkers
Imon Banerjee, Luís de Sisternes, Joelle Hallak, Theodore Leng, Aaron R Osborne, Philip J. Rosenfeld, Giovanni Gregori, Mary K Durbin, Daniel L. Rubin · 2020 · Scientific Reports
Noninvasive Determination of IDH and 1p19q Status of Lower-grade Gliomas Using MRI Radiomics: A Systematic Review
Abhishta Bhandari, Rebecca Liong, Jarrad Koppen, Shashidhar Venkatesh Murthy, Arian Lasocki · 2020 · American Journal of Neuroradiology
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
Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study
Vito Chianca, Renato Cuocolo, Salvatore Gitto, Domenico Albano, Ilaria Merli, Julietta Badalyan, Maria Cristina Cortese, Carmelo Messina, Alessandro Luzzati, Antonina Parafioriti et al. · 2021 · European Journal of Radiology
Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine
Anahita Fathi Kazerooni, Stephen Joseph Bagley, Hamed Akbari, Sanjay Saxena, Sina Bagheri, Jun Feng Guo, Sanjeev Chawla, Ali Nabavizadeh, Suyash Mohan, Spyridon Bakas et al. · 2021 · Cancers
Automatic detection of pneumonia in chest X-ray images using textural features
César Antonio Ortiz-Toro, Angel Mario Garcia-Pedrero, Mario Lillo‐Saavedra, Consuelo Gonzalo‐Martín · 2022 · Computers in Biology and Medicine
Predicting pancreatic ductal adenocarcinoma using artificial intelligence analysis of pre-diagnostic computed tomography images.
Qureshi, Touseef Ahmad, Gaddam, Srinivas, Wachsman, Ashley Max, Wang, Lixia, Azab, Linda, Asadpour, Vahid, Chen, Wansu, Xie, Yibin, Wu, Bechien, Pandol, Stephen Jacob et al. · 2022 · Cancer Biomarkers
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
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
Elaboration of a multisequence MRI-based radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer: a double-center study
Huanjun J. Wang, Xiaopan Xu, Xi Zhang, Yang Liu, Longyuan Y. Ouyang, Peng Du, Shurong Li, Qiang Tian, Jian Ling, Yan Guo et al. · 2020 · European Radiology
Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas
Stefan P. Haider, Barbara Ann Burtness, Wendell Gray Yarbrough, Seyedmehdi Payabvash · 2020 · Cancers of the Head & Neck
Deep learning radiomics in breast cancer with different modalities: Overview and future
Ting Pang, Jeannie Hsiu Ding Wong, Wei Lin Ng, Chee Seng Chan · 2020 · Expert Systems with Applications
Quantitative ultrasound radiomics in predicting response to neoadjuvant chemotherapy in patients with locally advanced breast cancer: Results from multi‐institutional study
Daniel DiCenzo, Karina Quiaoit, Kashuf Fatima, Divya Bhardwaj, Lakshmanan Sannachi, Mehrdad J. Gangeh, Ali Sadeghi Naini, Archya Dasgupta, Michael C. Kolios, Maureen Trudeau et al. · 2020 · Cancer Medicine
Preoperative Assessment for High‐Risk Endometrial Cancer by Developing an MRI ‐ and Clinical‐Based Radiomics Nomogram: A Multicenter Study
Bi Cong Yan, Ying Li, Hua Feng, Feng Feng, Ming Hua Sun, Guang Wu Lin, Guofu Zhang, Jinwei Qiang · 2020 · Journal of Magnetic Resonance Imaging
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
LGE-CMR-derived texture features reflect poor prognosis in hypertrophic cardiomyopathy patients with systolic dysfunction: preliminary results
Sainan Cheng, Mengjie Fang, Chen Cui, Xiuyu Chen, Gang Yin, Sanjay Kumar Prasad, Di Dong, Jie Tian, Shihua Zhao · 2018 · European Radiology
Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer
Sohee Park, Sang Min Lee, Kyung‐Hyun Do, June‐Goo Lee, Woong Bae, Hyunho Park, Kyu-Hwan Jung, Joon Beom Seo · 2019 · Korean Journal of Radiology
A systematic review of radiomics in osteosarcoma: utilizing radiomics quality score as a tool promoting clinical translation
Jingyu Zhong, Yangfan Hu, Liping Si, Geng Jia, Yue Xing, Huan Zhang, Weiwu Yao · 2020 · European Radiology
Whole‐Volume Tumor MRI Radiomics for Prognostic Modeling in Endometrial Cancer
Kristine Eldevik Fasmer, Erlend Hodneland, Julie Andrea Dybvik, Kari Strøno Wagner-Larsen, Jone Trovik, Øyvind Olav Salvesen, Camilla Krakstad, Ingfrid S. Haldorsen · 2020 · Journal of Magnetic Resonance Imaging
Radiomics analysis of 18F-Choline PET/CT in the prediction of disease outcome in high-risk prostate cancer: an explorative study on machine learning feature classification in 94 patients
Pierpaolo Alongi, Alessandro Stefano, Albert Comelli, Riccardo Laudicella, Salvatore Scalisi, Giuseppe Arnone, Stefano Barone, Massimiliano Spada, Pierpaolo Purpura, Tommaso Vincenzo Bartolotta et al. · 2021 · European Radiology
Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy
Qinmei Xu, Zeyu Sun, Xiuli Li, Chen Ye, Changsheng Zhou, Long Jiang Zhang, Guangming Lu · 2021 · European Radiology
Co-clinical FDG-PET Radiomic Signature in Predicting Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer
Sudipta Roy, T. Whitehead, Shun-Qiang Li, F. Ademuyiwa, R. Wahl, F. Dehdashti, K. Shoghi · 2021 · bioRxiv
MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer
Vetri Sudar Jayaprakasam, Viktoriya Paroder, Peter Gibbs, Raazi Bajwa, Natalie C. Gangai, Ramon E. Sosa, Iva Petkovska, Jennifer S. Golia Pernicka, James Louis Fuqua, ‬David D. B. Bates et al. · 2021 · European Radiology
Radiomics applications in cardiac imaging: a comprehensive review
Tiziano Polidori, Domenico De Santis, Carlotta Rucci, Giuseppe Tremamunno, Giulia Piccinni, Luca Pugliese, Marta Zerunian, Gisella Guido, Francesco Pucciarelli, Benedetta Bracci et al. · 2023 · La radiologia medica
Biomarkers and Imaging of Breast Cancer
Olena O. Weaver, Jessica W. T. Leung · 2017 · American Journal of Roentgenology
Convolutional Neural Network–Based Automated Segmentation of the Spinal Cord and Contusion Injury: Deep Learning Biomarker Correlates of Motor Impairment in Acute Spinal Cord Injury
David B. McCoy, Sara M. Dupont, Charley Gros, Julien Cohen‐Adad, John Russell Huie, Adam R. Ferguson, Xuan Duong Fernandez, Leigh H. Thomas, Vineeta Singh, Jared A. Narvid et al. · 2019 · American Journal of Neuroradiology
Integrating Mathematical Modeling into the Roadmap for Personalized Adaptive Radiation Therapy
Heiko Enderling, Juan Carlos López Alfonso, Eduardo G. Moros, Jimmy J. Caudell, Louis Benjamin Harrison · 2019 · Trends in cancer
Imaging-genomics reveals driving pathways of MRI derived volumetric tumor phenotype features in Glioblastoma
Patrick Großmann, David A. Gutman, William D. Dunn, Chad A. Holder, Hugo J.W.L. Aerts · 2016 · BMC Cancer
Multiparametric MRI‐Based Radiomics Nomogram for Predicting Lymph Node Metastasis in Early‐Stage Cervical Cancer
Meiling Xiao, Fenghua Ma, Ying Li, Yongai Li, Mengdie Li, Guofu Zhang, Jinwei Qiang · 2020 · Journal of Magnetic Resonance Imaging
Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets
Michael F. McNitt‐Gray, Sandy A. Napel, Ayush Jaggi, Sarah A. Mattonen, Lubomir M. Hadjiiski, Mark Muzi, Dmitry B. Goldgof, Yoganand Balagurunathan, Larry A. Pierce, Paul E. Kinahan et al. · 2020 · Tomography
Prediction of pituitary adenoma surgical consistency: radiomic data mining and machine learning on T2-weighted MRI
Renato Cuocolo, Lorenzo Ugga, Domenico Solari, Sergio Corvino, Alessandra D’Amico, Daniela Russo, Paolo Cappabianca, Luigi Maria Cavallo, Andrea Elefante · 2020 · Neuroradiology
Radiomics signature of brain metastasis: prediction of EGFR mutation status
Guangyu Wang, Bomin Wang, Zhou Wang, Wenchao Li, Jianjun Xiu, Zhi Liu, Mingyong Han · 2021 · European Radiology
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
Meningioma MRI radiomics and machine learning: systematic review, quality score assessment, and meta-analysis
Lorenzo Ugga, Teresa Perillo, Renato Cuocolo, Arnaldo Stanzione, Valeria Romeo, Roberta Green, Valeria Cantoni, Arturo Brunetti · 2021 · Neuroradiology
Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19
Navchetan Awasthi, Aveen Dayal, Linga Reddy Cenkeramaddi, Phaneendra Kumar Yalavarthy · 2021 · IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control
CT and MRI radiomics of bone and soft-tissue sarcomas: a systematic review of reproducibility and validation strategies
Salvatore Gitto, Renato Cuocolo, Domenico Albano, Francesco Morelli, Lorenzo Pescatori, Carmelo Messina, Massimo Imbriaco, Luca Maria Sconfienza · 2021 · Insights into Imaging
CT radiomics-based machine learning classification of atypical cartilaginous tumours and appendicular chondrosarcomas
Salvatore Gitto, Renato Cuocolo, Alessio Annovazzi, Vincenzo Anelli, Marzia Acquasanta, Antonino Cincotta, Domenico Albano, Vito Chianca, Virginia Ferraresi, Carmelo Messina et al. · 2021 · EBioMedicine
Artificial intelligence-based public healthcare systems: G2G knowledge-based exchange to enhance the decision-making process
Omar A. Nasseef, Abdullah Mohammed Baabdullah, Ali Abdallah Alalwan, Banita Lal, Yogesh Kumar Dwivedi · 2021 · Government Information Quarterly
Artificial Intelligence in Brain Tumour Surgery—An Emerging Paradigm
Simon C. Williams, Hugo Layard Horsfall, Jonathan Perry Funnell, JOHN GERRARD HANRAHAN, Danyal Zaman Khan, William R. Muirhead, Danail V. Stoyanov, Hani Joseph Marcus · 2021 · Cancers
High-dimensional role of AI and machine learning in cancer research
Enrico Capobianco · 2022 · British Journal of Cancer
Integration of artificial intelligence in lung cancer: Rise of the machine
Colton John Ladbury, Arya Amini, Ameish Govindarajan, Isa Mambetsariev, Dan J. Raz, Erminia Massarelli, Terence Marques Williams, Andréi S. Rodin, Ravi Salgia · 2023 · Cell Reports Medicine
Deep learning-based segmentation of breast masses in dedicated breast CT imaging: Radiomic feature stability between radiologists and artificial intelligence
Marco Caballo, Domenico R. Pangallo, Ritse M. Mann, Ioannis Sechopoulos · 2020 · Computers in Biology and Medicine
Machine learning in prostate MRI for prostate cancer: current status and future opportunities
Li, Huanye, Lee, Chau Hung, Chia, David, Lin, Zhiping, Huang, Weimin, Tan, Cher Heng · 2022 · Diagnostics
Machine Learning-Based Differentiation of Benign and Premalignant Colorectal Polyps Detected with CT Colonography in an Asymptomatic Screening Population: A Proof-Of-Concept Study
Grosu, Sergio, Wesp, Philipp, Graser, Anno, Maurus, Stefan, Schulz, Christian, Knösel, Thomas, Cyran, Clemens C., Ricke, Jens, Ingrisch, Michael, Kazmierczak, Philipp M. · 2021 · Radiology
Learning from scanners: Bias reduction and feature correction in radiomics
Zhovannik, Ivan, Bussink, Johan, Traverso, Alberto, Shi, Zhenwei, Kalendralis, Petros, Wee, Leonard, Dekker, Andre, Fijten, Rianne, Monshouwer, René · 2019 · Clinical and Translational Radiation Oncology
Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas
Paul Eichinger, Esther Alberts, Claire Delbridge, Stefano Trebeschi, Alexander Valentinitsch, Stefanie J. Bette, Thomas S. Huber, Jens Gempt, Bernhard Meyer, Jürgen Schlegel et al. · 2017 · Scientific Reports
CT-based radiomics signature for differentiating solitary granulomatous nodules from solid lung adenocarcinoma
Xinguan Yang, Jianxing He, Jiao Wang, Weiwei Li, Chunbo Liu, Dashan Gao, Yubao Guan · 2018 · Lung Cancer
Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI
Yi Kyung Kim, Hwan-ho Cho, Sung Tae Kim, Hyunjin Park, Do‐Hyun Nam, Doo‐Sik Kong · 2018 · Neuroradiology
Integrative nomogram of CT imaging, clinical, and hematological features for survival prediction of patients with locally advanced non-small cell lung cancer
Linlin Wang, Taotao Dong, Bowen Xin, Chong‐Rui Xu, Meiying Guo, Huaqi Zhang, Dagan D. Feng, Xiuying Wang, Jinming Yu · 2019 · European Radiology
Development and assessment of an individualized nomogram to predict colorectal cancer liver metastases
Mingyang Li, Xueyan Li, Guo Yu, Zheng Miao, Xiaoming Liu, Shuxu Guo, Huimao Zhang · 2020 · Quantitative Imaging in Medicine and Surgery
Prognostic value of FDG-PET radiomics with machine learning in pancreatic cancer
Toyama, Yoshitaka, Hotta, Masatoshi, Motoi, Fuyuhiko, Takanami, Kentaro, Minamimoto, Ryogo, Takase, Kei · 2020 · Scientific Reports
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
State-of-the-Art Imaging in Human Chordoma of the Skull Base
R.G.C. Santegoeds, Yasin Temel, Jan C. Beckervordersandforth, Jacobus J. van Overbeeke, M. Christianne Hoeberigs · 2018 · Current Radiology Reports
Prospects of deep learning for medical imaging
Jonghoon Kim, Jisu Hong, Hyunjin Park · 2018 · Precision and Future Medicine
Radiomics for the prediction of EGFR mutation subtypes in non‐small cell lung cancer
Shu Li, Changwei Ding, Hao Zhang, Jiangdian Song, Lei Wu · 2019 · Medical Physics
Stability and reproducibility of computed tomography radiomic features extracted from peritumoral regions of lung cancer lesions
I. Tunali, L. Hall, S. Napel, Dmitry Cherezov, A. Guvenis, R. Gillies, M. Schabath · 2019 · Medical Physics (Lancaster)
Identification of suspicious invasive placentation based on clinical MRI data using textural features and automated machine learning
Huaiqiang Sun, Haibo Qu, Chen Lü, Wei Wang, Yi Liao, Ling Zou, Ziyi Zhou, Xiaodong Wang, Shu Zhou · 2019 · European Radiology
Exploring Tumor Heterogeneity Using PET Imaging: The Big Picture
Clément Bailly, Caroline Bodet‐Milin, Mickaël Bourgeois, Sébastien Gouard, Catherine Ansquer, Matthieu Barbaud, Jean-Charles Sébille, Michel Chérel, Françoise Kraeber‐Bodéré, Thomas Carlier · 2019 · Cancers
Subregional Radiomics Analysis of PET/CT Imaging with Intratumor Partitioning: Application to Prognosis for Nasopharyngeal Carcinoma
Hui Xu, Wenbing Lv, Hui Feng, Dongyang Du, Qingyu Yuan, Quanshi Wang, Zhenhui Dai, Wei Yang, Qianjin Feng, Jianhua Ma et al. · 2019 · Molecular Imaging and Biology
Prediction of acute coronary syndrome within 3 years using radiomics signature of pericoronary adipose tissue based on coronary computed tomography angiography
Jin Shang, Shaowei Ma, Yan Guo, Linlin Yang, Qian Zhang, Fuchun Xie, Yue Ma, Quanmei Ma, Yuxue Dang, Ke Zhou et al. · 2021 · European Radiology
Radiomics and machine learning applications in rectal cancer: Current update and future perspectives
Arnaldo Stanzione, Francesco Verde, Valeria Romeo, Francesca Boccadifuoco, Pier Paolo Mainenti, Simone Maurea · 2021 · World Journal of Gastroenterology
Harmonization Strategies in Multicenter MRI-Based Radiomics
Elisavet Stamoulou, Constantinos Spanakis, Georgios C. Manikis, Georgia S. Karanasiou, Grigoris I. Grigoriadis, Theodoros Foukakis, Manolis Tsiknakis, Dimitrios I. Fotiadis, Kostas Marias A · 2022 · Journal of Imaging
Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future
Michaela Iva Cellina, Maurizio Cè, Giovanni Irmici, Velio Ascenti, Natallia Khenkina, Marco Toto‐Brocchi, Carlo Maria Andrea Martinenghi, Sergio Papa, Gianpaolo Carrafiello · 2022 · Diagnostics
Radiomic Biomarkers to Refine Risk Models for Distant Metastasis in HPV-related Oropharyngeal Carcinoma
Jennifer Y. Y. Kwan, Jie Susie Su, Shao Hui Huang, Laleh Soltan Ghoraie, Wei Xu, Biu Chan, Kenneth W. Yip, Meredith Giuliani, Andrew Bayley, John Kim et al. · 2018 · International Journal of Radiation Oncology*Biology*Physics
Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer
Wen Juan Yu, Chad Z. Tang, Brian Paul Hobbs, Xiao Li, Eugene Jon Koay, Ignacio Ivan Wistuba, Boris Sepesi, Carmen Behrens, Jaime Rodriguez Canales, Edwin Roger Parra et al. · 2017 · International Journal of Radiation Oncology*Biology*Physics
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
Association between CT-texture-derived tumor heterogeneity, outcomes, and BRCA mutation status in patients with high-grade serous ovarian cancer
Andreas Meier, Harini Veeraraghavan, Stéphanie Nougaret, Yulia Lakhman, Ramon E. Sosa, Robert A. Soslow, Elizabeth Jane Sutton, Hedvig Hricak, Evis Sala, Hebert Alberto Vargas · 2018 · Abdominal Radiology
Imaging biomarkers in oncology: Basics and application to MRI
Isabel Dregely, Davide Prezzi, Christian Kelly‐Morland, Elisa Roccia, Radhouène Neji, Vicky Goh · 2018 · Journal of Magnetic Resonance Imaging
Pre-treatment 18F-FDG PET-based radiomics predict survival in resected non-small cell lung cancer
Hee Kyung Ahn, H. Lee, Shinhyeong Kim, Seung Hyup Hyun · 2019 · Clinical Radiology
Improving survival prediction of high-grade glioma via machine learning techniques based on MRI radiomic, genetic and clinical risk factors
Yan Qin Tan, Wei Mu, Xiaochun Wang, Guoqiang Yang, Robert J. Gillies, Hui Zhang · 2019 · European Journal of Radiology
Radiomic Features of Primary Rectal Cancers on Baseline T2‐Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study
Jacob T. Antunes, Asya Ofshteyn, Kaustav Bera, Erik Y. Wang, Justin T. Brady, Joseph E. Willis, Kenneth A. Friedman, Eric L. Marderstein, Matthew F. Kalady, Sharon Lisa Stein et al. · 2020 · Journal of Magnetic Resonance Imaging
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
The Evolution of Artificial Intelligence in Medical Imaging: From Computer Science to Machine and Deep Learning
Michele Avanzo, Joseph Stancanello, Giovanni Pirrone, Annalisa Drigo, Alessandra Retico · 2024 · Cancers