The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

Clark, Kenneth, Vendt, Bruce, Smith, Kirk, Freymann, John, Kirby, Justin, Koppel, Paul, Moore, Stephen, Phillips, Stanley +4 more·2013·Journal of Digital Imaging

Cited by (1,012)

Items 401–500 of 1,012

  1. Detecting Malignant Leukemia Cells Using Microscopic Blood Smear Images: A Deep Learning Approach
    Raheel Baig, Abdur Rehman, Abdullah Almuhaimeed, Abdulkareem Alzahrani, Hafiz Tayyab Rauf · 2022 · Applied Sciences
  2. A survey of label-noise deep learning for medical image analysis
    Jialin Shi, Kailai Zhang, Chenyi Guo, Youquan Yang, Yali Xu, Ji Yi Wu · 2024 · Medical Image Analysis
  3. 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
  4. Millisecond speed deep learning based proton dose calculation with Monte Carlo accuracy
    Oscar Pastor‐Serrano, Zoltán Perkó · 2022 · Physics in Medicine and Biology
  5. IIMFCBM: Intelligent Integrated Model for Feature Extraction and Classification of Brain Tumors Using MRI Clinical Imaging Data in IoT-Healthcare
    Amin Ul Haq, Jianping Li, Bless Lord Y. Agbley, Asif Khan, Inayat Ullah Khan, Muhammad Irfan Uddin, Shakir Khan · 2022 · IEEE Journal of Biomedical and Health Informatics
  6. Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework
    Biswajit Jena, Sanjay Saxena, Gopal Krishna Nayak, Antonella Balestrieri, Neha Gupta, Narinder N. Khanna, John R. Laird, Manudeep K. Kalra, Mostafa M. Fouda, Luca Saba et al. · 2022 · Cancers
  7. A Comprehensive Review of Artificial Intelligence Approaches in Omics Data Processing: Evaluating Progress and Challenges
    Ali Mahmoud Ali, Mazin Abed Mohammed · 2023 · International Journal of Mathematics Statistics and Computer Science
  8. Addressing fairness issues in deep learning-based medical image analysis: a systematic review
    Zikang Xu, Jun Li, Qingsong Yao, Han Li, Mingyue Zhao, S. Kevin Zhou · 2024 · npj Digital Medicine
  9. 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
  10. NCI Imaging Data Commons
    Andriy Fedorov, William J.R. Longabaugh, David Pot, David Clunie, Steve Pieper, Hugo J.W.L. Aerts, André Homeyer, Rob Lewis, Afshin Akbarzadeh, Dennis Bontempi et al. · 2021 · Cancer Research
  11. MOB-CBAM: A dual-channel attention-based deep learning generalizable model for breast cancer molecular subtypes prediction using mammograms
    Iqra Nissar, Shahzad Alam, Sarfaraz Masood, Mohammad Kashif · 2024 · Computer Methods and Programs in Biomedicine
  12. VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging
    Yufan He, Pengfei Guo, Yucheng Tang, Andriy Myronenko, Vishwesh Nath, Ziyue Xu, Dong Fang Yang, Can Zhao, Benjamin Simon, Mason J. Belue et al. · 2025 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  13. Dosiomics improves prediction of locoregional recurrence for intensity modulated radiotherapy treated head and neck cancer cases
    Aiqian Wu, Yongbao Li, Mengke Qi, Xingyu Lu, Qiyuan Jia, Futong Guo, Zhenhui Dai, Yuliang Liu, Chaomin Chen, Linghong Zhou et al. · 2020 · Oral Oncology
  14. Machine learning-based pathomics signature could act as a novel prognostic marker for patients with clear cell renal cell carcinoma
    Siteng Chen, Liren Jiang, Feng Gao, Encheng Zhang, Tao Wang, Ning Zhang, Xiang Wang, Junhua Zheng · 2021 · British Journal of Cancer
  15. 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
  16. Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology
    Jun Shao, Jiechao Ma, Qin Zhang, Weimin Li, Chengdi Wang · 2023 · Seminars in Cancer Biology
  17. Application of Deep Neural Networks and Machine Learning algorithms for diagnosis of Brain tumour
    Shaiq Wani, Sachin Ahuja, Abhishek Kumar · 2023 · International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES)
  18. A Hybrid Workflow of Residual Convolutional Transformer Encoder for Breast Cancer Classification Using Digital X-ray Mammograms
    Al-Tam, Riyadh M., Al-Hejri, Aymen M., Narangale, Sachin M., Samee, Nagwan Abdel, Mahmoud, Noha F., Al-masni, Mohammed A., Al-antari, Mugahed A. · 2022 · Biomedicines
  19. 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
  20. 4DCT imaging to assess radiomics feature stability: An investigation for thoracic cancers
    Ruben T. H. M. Larue, Lien Van De Voorde, Janita E. van Timmeren, Ralph T. H. Leijenaar, Maaike Berbée, Meindert Nico Sosef, Wendy M. J. Schreurs, Wouter van Elmpt, Philippe Lambin · 2017 · Radiotherapy and Oncology
  21. Radiomics features of the primary tumor fail to improve prediction of overall survival in large cohorts of CT- and PET-imaged head and neck cancer patients
    Rachel B. Ger, Shouhao Zhou, Baher Elgohari, Hesham M. Elhalawani, Dennis Mackin, Joseph G. Meier, Callistus M. Nguyen, Brian Anderson, Casey Gay, Jing Ning et al. · 2019 · PLoS ONE
  22. Classificatin of Brain Tumors by Machine Learning Algorithms
    Gökalp Çınarer, Bülent Gürsel Emiroğlu · 2019 · International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)
  23. 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
  24. A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification
    Pablo Mesejo, Rubén Martos, Oscar C. Ibáñez, Jorge Novo, Marcos Ortega · 2020 · Applied Sciences
  25. Shadow-Consistent Semi-Supervised Learning for Prostate Ultrasound Segmentation
    Xuanang Xu, Thomas Sanford, Barış Türkbey, Sheng Xu, Bradford J. Wood, Pingkun Yan · 2021 · IEEE Transactions on Medical Imaging
  26. Artificial intelligence for medicine: Progress, challenges, and perspectives
    Tao Huang, Huiyu Xu, Haitao Wang, Haofan Huang, Yongjun Xu, Baohua Li, Shenda Hong, Guoshuang Feng, Shuyi Kui, Guangjian Liu et al. · 2023 · The Innovation Medicine
  27. Hallmarks of artificial intelligence contributions to precision oncology
    Tiangen Chang, Seongyong Park, Alejandro A. Schäffer, Peng Jiang, Eytan Ruppin · 2025 · Nature Cancer
  28. A sophisticated convolutional neural network model for brain tumor classification
    Narmada M. Balasooriya, Ruwan D. Nawarathna · 2017 · IEEE International Conference on Industrial and Information Systems (ICIIS)
  29. Machine Intelligence in Healthcare and Medical Cyber Physical Systems: A Survey
    Omid Rajabi Shishvan, Daphney–Stavroula Zois, Tolga Soyata · 2018 · IEEE Access
  30. A review of breast boundary and pectoral muscle segmentation methods in computer-aided detection/diagnosis of breast mammography
    Mehrdad Moghbel, Chia Yee Ooi, Nordinah Binti Ismail, Yuan Wen Hau, Nogol Memari · 2019 · Artificial Intelligence Review
  31. Progressively Trained Convolutional Neural Networks for Deformable Image Registration
    Koen A. J. Eppenhof, Maxime W. Lafarge, Mitko Veta, Josien P. W. Pluim · 2019 · IEEE Transactions on Medical Imaging
  32. Efficacy evaluation of 2D, 3D U-Net semantic segmentation and atlas-based segmentation of normal lungs excluding the trachea and main bronchi
    Takafumi Nemoto, Natsumi Futakami, Masamichi Yagi, Atsuhiro Kumabe, Atsuya Takeda, Etsuo Kunieda, Naoyuki Shigematsu · 2019 · Journal of Radiation Research
  33. A novel comparative study for detection of Covid-19 on CT lung images using texture analysis, machine learning, and deep learning methods
    Hüseyin Yaşar, Murat Ceylan · 2020 · Multimedia Tools and Applications
  34. Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy
    Sunan Cui, Randall K. Ten Haken, Issam El Naqa · 2021 · International Journal of Radiation Oncology*Biology*Physics
  35. A robust zero-watermarking algorithm for lossless copyright protection of medical images
    Zhiqiu Xia, Xingyuan Wang, Chunpeng Wang, Changxu Wang, Bin Ma, Qi Li, Mingxu Wang, Tingting Zhao · 2021 · Applied Intelligence
  36. 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
  37. Demystifying the Results of RTOG 0617: Identification of Dose Sensitive Cardiac Subregions Associated With Overall Survival
    Alan McWilliam, Azadeh Abravan, Kathryn Banfill, Corinne Faivre Finn, Marcel van Herk · 2023 · Journal of Thoracic Oncology
  38. Large-scale multi-center CT and MRI segmentation of pancreas with deep learning
    Zheyuan Zhang, Elif Keleş, Görkem Durak, Yavuz Bahadır Taktak, Onkar Susladkar, Vandan Gorade, Debesh Jha, Asli C. Ormeci, Alpay Medetalibeyoğlu, Lanhong Yao et al. · 2024 · Medical Image Analysis
  39. 4D robust optimization including uncertainties in time structures can reduce the interplay effect in proton pencil beam scanning radiation therapy
    Erik Engwall, Albin Fredriksson, Lars Glimelius · 2018 · Medical Physics
  40. Towards Efficient COVID-19 CT Annotation: A Benchmark for Lung and Infection Segmentation
    Jun Ma, Yixin Wang, Xingle An, Cheng Ge, Ziqi Yu, Jianan Chen, Qiongjie Zhu, Guoqiang Dong, Jian He, Zhiqiang He et al. · 2020 · arXiv (Cornell University)
  41. Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI
    Yu-Cherng Chang, Ellen Ackerstaff, Yohann Tschudi, Bryan Jimenez, Warren D. Foltz, Carl Fisher, Lothar D. Lilge, HyungJoon Cho, Sean Carlin, Robert J. Gillies et al. · 2017 · Scientific Reports
  42. CT-based Radiomic Signatures for Predicting Histopathologic Features in Head and Neck Squamous Cell Carcinoma
    Pritam Mukherjee, Murilo Bicudo Cintra, Chao Huang, Mu Zhou, Shankuan Zhu, Alexander Dimitrios Colevas, Nancy J. Fischbein, Olivier Gevaert · 2020 · Radiology Imaging Cancer
  43. 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
  44. Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Deep Learning with Integrative Imaging, Molecular and Demographic Data
    Hongyi Duanmu, Pauline Huang, Srinidhi Brahmavar, Stephanie K. Lin, Thomas Ren, Jun Kong, Fusheng Wang, Timothy Q. Duong · 2020 · Lecture notes in computer science
  45. Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas: From Disease Biology to Therapeutic Implications
    Andrea Comba, Syed Mohd Faisal, Maria Luisa Varela, Todd Charles Hollon, Wajd N. Al‐Holou, Yoshie Umemura, Felipe Javier Núñez, Sébastien Motsch, Maria Graciela Castro, Pedro Ricardo Lowenstein · 2021 · Frontiers in Oncology
  46. A Cascaded Deep Learning–Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging
    Sherif Mehralivand, Dong Yang, Stephanie A. Harmon, Daguang Xu, Ziyue Xu, Holger R. Roth, Samira Masoudi, Thomas Sanford, Deepak Kesani, Nathan S. Lay et al. · 2021 · Academic Radiology
  47. [18F]FDG-PET/CT Radiomics and Artificial Intelligence in Lung Cancer: Technical Aspects and Potential Clinical Applications
    Reyhaneh Manafi‐Farid, Emran Askari, Isaac Shiri, Christian Pirich, Mahboobeh Asadi, Maziar Khateri, Habib Zaidi, Mohsen Beheshti · 2022 · Seminars in Nuclear Medicine
  48. Enhancement of Deep Learning in Image Classification Performance Using Xception with the Swish Activation Function for Colorectal Polyp Preliminary Screening
    Natinai Jinsakul, Cheng-Fa Tsai, Chia-En Tsai, Pensée Wu · 2019 · Mathematics
  49. MAD‐UNet: A deep U‐shaped network combined with an attention mechanism for pancreas segmentation in CT images
    Weisheng Li, Sheng Qin, Feiyan Li, Linhong Wang · 2020 · Medical Physics
  50. Radiomic features at CT can distinguish pancreatic cancer from noncancerous pancreas
    Chen, Po-Ting, Chang, Dawei, Yen, Huihsuan, Liu, Kao-Lang, Huang, Su-Yun, Roth, Holger, Wu, Ming-Shiang, Liao, Wei-Chih, Wang, Weichung · 2021 · Radiology: Imaging Cancer
  51. Development and Validation of an Efficient MRI Radiomics Signature for Improving the Predictive Performance of 1p/19q Co-Deletion in Lower-Grade Gliomas
    Quang-Hien Kha, Viet-Huan Le, Truong Nguyen Khanh Hung, Nguyen Quoc Khanh Le · 2021 · Cancers
  52. Automated Detection and Characterization of Colon Cancer with Deep Convolutional Neural Networks
    Md Imran Hasan, Md Shahin Ali, Md Habibur Rahman, Md Khairul Islam · 2022 · Journal of Healthcare Engineering
  53. Artificial Intelligence Techniques to Predict the Airway Disorders Illness: A Systematic Review
    Apeksha Koul, Rajesh K. Bawa, Yogesh Kumar · 2022 · Archives of Computational Methods in Engineering
  54. A systematic review of computational approaches to understand cancer biology for informed drug repurposing
    Faheem Ahmed, Anupama Samantasinghar, Afaque Manzoor Soomro, Sejong Kim, Kyung Hyun Choi · 2023 · Journal of Biomedical Informatics
  55. XAI-Based Clinical Decision Support Systems: A Systematic Review
    Se Young Kim, Dae Ho Kim, Min‐Ji Kim, Hyo-Jin Ko, Ok‐Ran Jeong · 2024 · Applied Sciences
  56. A Novel Computer-Aided Lung Cancer Detection Method Based on Transfer Learning from GoogLeNet and Median Intensity Projections
    Tiantian Fang · 2018 · IEEE International Conference on Computer and Communication Engineering Technology (CCET)
  57. Bi-Modality Medical Image Synthesis Using Semi-Supervised Sequential Generative Adversarial Networks
    Xin Yan Yang, Yi Lin, Zhiwei Wang, Xin Shane Li, Kwang-Ting Tim Cheng · 2019 · IEEE Journal of Biomedical and Health Informatics
  58. Tumor immune profiles noninvasively estimated by FDG PET with deep learning correlate with immunotherapy response in lung adenocarcinoma
    Changhee Park, K. J. Na, Hongyoon Choi, C. Ock, Seunggyun Ha, Miso Kim, Samina Park, B. Keam, T. Kim, J. Paeng et al. · 2020 · Theranostics
  59. Machine learning based medical image deepfake detection: A comparative study
    Solaiyappan, Siddharth, Wen, Yuxin · 2022 · Machine Learning with Applications
  60. Multimodal mixed reality visualisation for intraoperative surgical guidance
    João Cartucho, David Shapira, Hutan Ashrafian, Stamatia Giannarou · 2020 · International Journal of Computer Assisted Radiology and Surgery
  61. Joint Imaging Platform for Federated Clinical Data Analytics
    Jonas Scherer, Marco Nolden, Jens Kleesiek, Jasmin Metzger, Klaus Kades, Verena Schneider, Michael Bach, Oliver Sedlaczek, Andreas Michael Bucher, Thomas Joseph Vogl et al. · 2020 · JCO Clinical Cancer Informatics
  62. Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs
    Maria Colomba Comes, Annarita Fanizzi, Samantha Bove, Vittorio Didonna, Sergio Diotaiuti, Daniele La Forgia, Agnese Carmela Latorre, Eugenio Martinelli, Arianna Mencattini, Annalisa Nardone et al. · 2021 · Scientific Reports
  63. CycleGAN denoising of extreme low-dose cardiac CT using wavelet-assisted noise disentanglement
    Jawook Gu, Tae Seong Yang, Jong Chul Ye, Dong Hyun Yang · 2021 · Medical Image Analysis
  64. Molecular subtype classification of low‐grade gliomas using magnetic resonance imaging‐based radiomics and machine learning
    Luu Ho Thanh Lam, Duyen Thi Do, Doan Thi Ngoc Diep, Dang Le Nhu Nguyet, Quang Dinh Truong, Tran Thanh Tri, Huynh Ngoc Thanh, Nguyen Quoc Khanh Le · 2022 · NMR in Biomedicine
  65. Recent advances of Transformers in medical image analysis: A comprehensive review
    Kun Xia, Jinzhuo Wang · 2023 · MedComm – Future Medicine
  66. Automatic detection of pulmonary nodules in CT images by incorporating 3D tensor filtering with local image feature analysis
    Jing Gong, Ji-yu Liu, Li-jia Wang, Xi-wen Sun, Bin Zheng, Sheng-dong Nie · 2018 · Physica Medica
  67. Left Anterior Descending Coronary Artery Radiation Dose Association With All-Cause Mortality in NRG Oncology Trial RTOG 0617
    Elizabeth M. McKenzie, Samuel Zhang, Roja Zakariaee, Christian V. Guthier, Behrooz Hakimian, Amin J. Mirhadi, Mitchell R. Kamrava, Sukhmani Kaur Padda, John Henry Lewis, Andriana Nikolova et al. · 2022 · International Journal of Radiation Oncology*Biology*Physics
  68. A Tumour and Liver Automatic Segmentation (ATLAS) Dataset on Contrast-Enhanced Magnetic Resonance Imaging for Hepatocellular Carcinoma
    Félix Quinton, Romain Popoff, Benoît Presles, Sarah Leclerc, Fabrice Mériaudeau, Guillaume Nodari, Olivier Lopez, Julie Pellegrinelli, Olivier Chevallier, Dominique Ginhac B et al. · 2023 · Data
  69. Deep Semisupervised Transfer Learning for Fully Automated Whole-Body Tumor Quantification and Prognosis of Cancer on PET/CT
    Kevin Leung, Steven P. Rowe, Moe S. Sadaghiani, Jeffrey P. Leal, Esther Mena, Peter L. Choyke, Yong Du, Martin G. Pomper · 2024 · Journal of Nuclear Medicine
  70. Hybrid intelligent approach for diagnosis of the lung nodule from CT images using spatial kernelized fuzzy c-means and ensemble learning
    Farzad V. Farahani, Abbas Ahmadi, Mohammad Hossein Fazel Zarandi · 2018 · Mathematics and Computers in Simulation
  71. A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data
    Zhuo Zhang, Hao Li, Shuai Jiang, Ruijiang Li, Wanying Li, Hebing Chen, Xiaochen Bo · 2018 · Briefings in Bioinformatics
  72. Application and Construction of Deep Learning Networks in Medical Imaging
    Maribel Torres-Velázquez, Weijie Chen, Xue Li, Alan B. McMillan · 2020 · IEEE Transactions on Radiation and Plasma Medical Sciences
  73. Developing image analysis methods for digital pathology
    Peter Bankhead · 2022 · The Journal of Pathology
  74. Towards computational solutions for precision medicine based big data healthcare system using deep learning models: A review
    Ramkumar Thirunavukarasu, C. George Priya Doss, Gnanasambandan Ramanathan, Mohanraj Gopikrishnan, Venketesh Palanisamy · 2022 · Computers in Biology and Medicine
  75. Brain tumor segmentation and classification on MRI via deep hybrid representation learning
    Nacer Farajzadeh, Nima Sadeghzadeh, Mahdi Hashemzadeh · 2023 · Expert Systems with Applications
  76. BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation
    Tao Chen, Chenhui Wang, Hongming Shan · 2023 · Lecture notes in computer science
  77. Early cancer detection using deep learning and medical imaging: A survey
    Istiak Ahmad, Fahad Abdullah Alqurashi · 2024 · Critical Reviews in Oncology/Hematology
  78. Optimizing non small cell lung cancer detection with convolutional neural networks and differential augmentation
    Vahiduddin Shariff, Chiranjeevi Paritala, Krishna Mohan Ankala · 2025 · Scientific Reports
  79. GIFT-Cloud: A data sharing and collaboration platform for medical imaging research
    Tom Doel, Dzhoshkun I. Shakir, Rosalind Pratt, Michaël Aertsen, James C. Moggridge, Erwin Bellon, Anna Louise David, Jan A. Deprest, Tom K. Vercauteren, Sebastien Ourselin A · 2016 · Computer Methods and Programs in Biomedicine
  80. Feasibility study of a multi-criteria decision-making based hierarchical model for multi-modality feature and multi-classifier fusion: Applications in medical prognosis prediction
    Qiang He, Xin Li, D.W. Nathan Kim, Xun Jia, Xuejun Gu, Xin Zhen, Linghong Zhou · 2019 · Information Fusion
  81. Special Section Guest Editorial: LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned
    Samuel G. Armato, Lubomir M. Hadjiiski, Georgia D. Tourassi, Karen Drukker, Maryellen Lissak Giger, Feng Li, George Redmond, Keyvan Farahani, Justin Kirby, Laurence P. Clarke · 2015 · Journal of medical imaging
  82. Categorized contrast enhanced mammography dataset for diagnostic and artificial intelligence research
    Rana Khaled, Maha Helal, Omar Alfarghaly, Omnia Mokhtar, Abeer ElKorany, Hebatalla El Kassas, Aly Fahmy · 2022 · Scientific Data
  83. Segment Anything in Medical Images
    Ma, Jun, He, Yuting, Li, Feifei, Han, Lin, You, Chenyu, Wang, Bo · 2023 · arXiv
  84. Radiogenomics of lower-grade gliomas: machine learning–based MRI texture analysis for predicting 1p/19q codeletion status
    Burak Koçak, Emine Şebnem Durmaz, Ece Ates, İpek Sel, Saime Turgut Güneş, Ozlem Korkmaz Kaya, Amalya Zeynalova, Özgür Kılıçkesmez · 2019 · European Radiology
  85. A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification
    Ying Ren, Min-Yu Tsai, Liyuan Chen, Jing Wang, Shulong Li, Yufei Liu, Xun Jia, Chenyang Shen · 2019 · International Journal of Computer Assisted Radiology and Surgery
  86. Convolutional neural network for automated mass segmentation in mammography
    Dina Abdelhafiz, Jinbo Bi, Reda A.A. Ammar, Clifford Yang, Sheida Nabavi · 2020 · BMC Bioinformatics
  87. Multi-scale signaling and tumor evolution in high-grade gliomas
    Jingxian Liu, Song Cao, Kathleen J. Imbach, Marina A. Gritsenko, T. Mamie Lih, Jennifer E Kyle, Tomer M. Yaron-Barir, Zev A. Binder, Yize Li, Ilya Strunilin et al. · 2024 · Cancer Cell
  88. Predicting Genotype and Survival in Glioma Using Standard Clinical MR Imaging Apparent Diffusion Coefficient Images: A Pilot Study from The Cancer Genome Atlas
    Chih‐Chun Wu, Rajan Jain, Alireza Radmanesh, Laila Poisson, Wan‐Yuo Guo, David Zagzag, Matija Snuderl, Dimitris G. Placantonakis, John G. Golfinos, Andrew S. Chi · 2018 · American Journal of Neuroradiology
  89. Non-Invasive Tumor Genotyping Using Radiogenomic Biomarkers, a Systematic Review and Oncology-Wide Pathway Analysis
    Jansen, Robin W., van Amstel, Paul, Martens, Roland M., Kooi, Irsan E., Wesseling, Pieter, de Langen, Adrianus J., Menke-Van der Houven van Oordt, Catharina W., Jansen, Bernard H.E., Moll, Annette C., Dorsman, Josephine C. et al. · 2018 · Oncotarget
  90. 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
  91. Overall Survival Prediction in Renal Cell Carcinoma Patients Using Computed Tomography Radiomic and Clinical Information
    Zahra Khodabakhshi, Mehdi Amini, Shayan Mostafaei, Atlas Haddadi Avval, Mostafa Nazari, Mehrdad Oveisi, Isaac Shiri, Habib Zaidi · 2021 · Journal of Imaging Informatics in Medicine
  92. Impact of GAN-based lesion-focused medical image super-resolution on the robustness of radiomic features
    Erick Costa de Farias, Christian di Noia, Changhee Han, Evis Sala, Mauro Castelli, Leonardo Rundo · 2021 · Scientific Reports
  93. Quantum-classical convolutional neural networks in radiological image classification
    Andrea Matic, Maureen Monnet, Jeanette Miriam Lorenz, Balthasar Maria Schachtner, Thomas Messerer · 2022 · IEEE International Conference on Quantum Computing and Engineering (QCE)
  94. A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicron
    Asifullah Khan, Saddam Hussain Khan, Mahrukh Saif, Asiya Batool, Anabia Sohail, Muhammad Waleed Khan · 2023 · Journal of Experimental & Theoretical Artificial Intelligence
  95. Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival “early on” in neoadjuvant treatment of breast cancer
    Karen Drukker, Hui Li, Natalia Antropova, Alexandra V. Edwards, John Papaioannou, Maryellen Lissak Giger · 2018 · Cancer Imaging
  96. Radiogenomics for Precision Medicine With a Big Data Analytics Perspective
    Panayides, Andreas S., Pattichis, Marios S., Leandrou, Stephanos, Pitris, Costas, Constantinidou, Anastasia, Pattichis, Constantinos S. · 2019 · IEEE Journal of Biomedical and Health Informatics
  97. Deep Lesion Graph in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database
    Ke Yan, Xiaosong Wang, Le Lü, Ling Zhang, Adam P. Harrison, Mohammadhadi H. Bagheri, Ronald M. Summers · 2019 · Advances in computer vision and pattern recognition
  98. Brain Tumor Classification Using MRI Images with K-Nearest Neighbor Method
    Rafi Haidar Ramdlon, Entin Martiana Kusumaningtyas, Tita Karlita · 2019 · International Electronics Symposium (IES)
  99. SDCT-AuxNet : DCT augmented stain deconvolutional CNN with auxiliary classifier for cancer diagnosis
    Shiv Gehlot, Anubha Gupta, Ritu Gupta · 2020 · Medical Image Analysis
  100. 3D-MCN: A 3D Multi-scale Capsule Network for Lung Nodule Malignancy Prediction
    Parnian Afshar, Anastasia Oikonomou, Farnoosh Naderkhani, Pascal N. Tyrrell, Konstantinos N. Plataniotis, Keyvan Farahani, Arash Mohammadi · 2020 · Scientific Reports