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

Cited by (1,012)

Items 801–900 of 1,012

1. Deep Learning Innovations in the Detection of Lung Cancer: Advances, Trends, and Open Challenges
   Helena Liz, Áurea Anguera de Sojo Hernández, Sergio D’Antonio Maceiras, Miguel Angel Díaz-Martínez, David Camacho · 2025 · Cognitive Computation
2. A novel biomedical image indexing and retrieval system via deep preference learning
   Shuchao Pang, Mehmet Ali Orgun, Zhezhou Yu · 2018 · Computer Methods and Programs in Biomedicine
3. An Appraisal of Nodule Diagnosis for Lung Cancer in CT Images
   Guobin Zhang, Zhiyong Yang, Li Gong, Shan Jiang, Lu Wang, Xi Cao, Lin Wei, Hongyun Zhang, Ziqi Liu · 2019 · Journal of Medical Systems
4. The French glioblastoma biobank (FGB): a national clinicobiological database
   FGB network, Anne Clavreul, Gwénaëlle Soulard, Jean-michel Lemée M. D, Marion Rigot, Pascale Fabbro-Péray, Luc Bauchet, Dominique F. Figarella-Branger, Philippe Meneï · 2019 · Journal of Translational Medicine
5. Quasi-simultaneous 3D printing of muscle-, lung- and bone-equivalent media: a proof-of-concept study
   Tanya Kairn, M. Zahrani, Naasiha Cassim, Alexander Livingstone, Paul Charles, Scott Crowe · 2020 · Physical and Engineering Sciences in Medicine
6. Spatial Pyramid Pooling With 3D Convolution Improves Lung Cancer Detection
   Jason Causey, Keyu Li, Xianghao Chen, Wei Dong, Karl Walker, Jake Qualls, Jonathan Stubblefield, Jason H. Moore, Yuanfang Guan, Xiuzhen Huang · 2020 · IEEE Transactions on Computational Biology and Bioinformatics
7. Integrated Multi-Tumor Radio-Genomic Marker of Outcomes in Patients with High Serous Ovarian Carcinoma
   Harini Veeraraghavan, Herbert Vargas, Alejandro Jiménez-Sánchez, Maura Miccò, Eralda Mema, Yulia Lakhman, Mireia Crispin‐Ortuzar, Erich P. Huang, Douglas A. Levine, Rachel Nicole Grisham et al. · 2020 · Cancers
8. Relationship between visceral adipose tissue and genetic mutations (VHL and KDM5C) in clear cell renal cell carcinoma
   Federico Greco, Carlo Augusto Mallio · 2021 · La radiologia medica
9. Genotype-Guided Radiomics Signatures for Recurrence Prediction of Non-Small Cell Lung Cancer
   Panyanat Aonpong, Yutaro Iwamoto, Xian‐Hua Han, Lanfen Lin, Yen‐Wei Chen · 2021 · IEEE Access
10. DeepMMSA: A Novel Multimodal Deep Learning Method for Non-small Cell Lung Cancer Survival Analysis
    Yujiao Wu, Jie Ma, Xiaoshui Huang, Sai Ho Ling, Steven Weidong Su · 2021 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
11. The relationship between radiomics and pathomics in Glioblastoma patients: Preliminary results from a cross-scale association study
    Valentina Brancato, Carlo Cavaliere, Nunzia Garbino, Francesco Isgrò, Marco Salvatore, Marco Aiello · 2022 · Frontiers in Oncology
12. An annotated test-retest collection of prostate multiparametric MRI
    Andriy Fedorov, Michael Schwier, David Clunie, Christian Herz, Steve Pieper, Ron Kikinis, Clare M. Tempany, Fiona Fennessy · 2018 · Scientific Data
13. LoDoPaB-CT Dataset
    Johannes Leuschner, Maximilian Schmidt, Daniel Otero Baguer · 2019 · Zenodo (CERN European Organization for Nuclear Research)
14. Building reliable radiomic models using image perturbation
    Teng, Xinzhi, Zhang, Jiang, Zwanenburg, Alex, Sun, Jiachen, Huang, Yuhua, Lam, Saikit, Zhang, Yuanpeng, Li, Bing, Zhou, Ta, Xiao, Haonan et al. · 2022 · Scientific Reports
15. A segmentation-based method improving the performance of N4 bias field correction on T2weighted MR imaging data of the prostate
    Aikaterini Dovrou, Katerina Nikiforaki, Dimitrios I. Zaridis, Georgios C. Manikis, Eugenia Mylona, Nikolaos S. Tachos, Manolis Tsiknakis, Dimitrios I. Fotiadis, Kostas Marias A · 2023 · Magnetic Resonance Imaging
16. Brain tumor detection and segmentation: Interactive framework with a visual interface and feedback facility for dynamically improved accuracy and trust
    Kashfia Sailunaz, Deniz Beştepe, Sleiman Alhajj, Tansel Özyer, Jon George Rokne, Reda Alhajj · 2023 · PLoS ONE
17. A review of self‐supervised, generative, and few‐shot deep learning methods for data‐limited magnetic resonance imaging segmentation
    Zelong Liu, Komal Kainth, Alexander Zhou, Timothy W. Deyer, Zahi Adel Fayad, Hayit K. Greenspan, Xueyan Mei · 2024 · NMR in Biomedicine
18. Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology
    Haoyang Mi, Shamilene Sivagnanam, Won Jin Ho, Shuming Zhang, Daniel R. Bergman, Atul M. Deshpande, Alexander Spyridon Baras, Elizabeth M. Jaffee, Lisa M. Coussens, Elana Judith Fertig et al. · 2024 · Briefings in Bioinformatics
19. Large models in medical imaging: Advances and prospects
    Mengjie Fang, Zipei Wang, Sitian Pan, Xin Feng, Yunpeng Zhao, Dongzhi Hou, Ling Wu, Xuebin Xie, Xu-Yao Zhang, Jie Tian et al. · 2025 · Chinese Medical Journal
20. Computer aided detection and diagnosis in medical imaging
    Jorge Hernández‐Rodríguez, Francisco Javier Cabrero Fraile, María José Rodríguez Conde, P. L. Gomez Llorente · 2016 · Ninth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM'21)
21. Tumor Metabolic Features Identified by 18F-FDG PET Correlate with Gene Networks of Immune Cell Microenvironment in Head and Neck Cancer
    Kwon Joong Na, Hongyoon Choi · 2017 · Journal of Nuclear Medicine
22. Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes
    on behalf of the TCGA group, Elizabeth Jane Sutton, Erich P. Huang, Karen Drukker, Elizabeth S. Burnside, Hui Li, Jose Net, Arvind U.K. Rao, Gary J. Whitman, Margarita L. Zuley et al. · 2017 · European Radiology Experimental
23. Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma’s grade and IDH status
    Céline De Looze, Alan Beausang, Jane B. Cryan, Teresa Loftus, Patrick G. Buckley, Michael A. Farrell, Seamus T Looby, Richard B. Reilly, Francesca M. Brett, HUGH F. KEARNEY · 2018 · Journal of Neuro-Oncology
24. Proton vs photon: A model-based approach to patient selection for reduction of cardiac toxicity in locally advanced lung cancer
    S. Teoh, Francesca Fiorini, B. George, Katherine A. Vallis, Frank Van den Heuvel · 2019 · Radiotherapy and Oncology
25. Analysis of heterogeneity of peritumoral T2 hyperintensity in patients with pretreatment glioblastoma: Prognostic value of MRI-based radiomics
    Yangsean Choi, Kook Jin Ahn, Yoonho Nam, Jinhee Jang, Na‐Young Shin, Hyun Seok Choi, So Lyung Jung, Bum‐Soo Kim · 2019 · European Journal of Radiology
26. Identification of Novel Transcriptome Signature as a Potential Prognostic Biomarker for Anti-Angiogenic Therapy in Glioblastoma Multiforme
    Shuhua Zheng, Wensi Tao · 2021 · Cancers
27. Impact of feature selection methods and subgroup factors on prognostic analysis with CT-based radiomics in non-small cell lung cancer patients
    Yuto Sugai, Noriyuki Kadoya, Shohei Tanaka, Shunpei Tanabe, Mariko Umeda, Takaya Yamamoto, Kazuya Takeda, Suguru Dobashi, Haruna Ohashi, Ken Takeda et al. · 2021 · Radiation Oncology
28. Machine Learning for Histologic Subtype Classification of Non-Small Cell Lung Cancer: A Retrospective Multicenter Radiomics Study
    Fengchang Yang, Wei Chen, Haifeng Wei, Xianru Zhang, Shuanghu Yuan, Qiao Xu, Yen‐Wei Chen · 2021 · Frontiers in Oncology
29. Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers
    Nathaniel M. Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette Turk, Amit Banwari Gupta et al. · 2022 · Clinical Cancer Research
30. Complete fully automatic detection, segmentation and 3D reconstruction of tumor volume for non-small cell lung cancer using YOLOv4 and region-based active contour model
    Sifundvolesihle Dlamini, Yi-Hsi Chen, Chung-Feng Jeffrey Kuo · 2022 · Expert Systems with Applications
31. Deep learning–based automatic segmentation of cardiac substructures for lung cancers
    Xinru Chen, Raymond P. Mumme, Kelsey L. Corrigan, Yuki Mukai-Sasaki, Efstratios Koutroumpakis, Nicolas L. Palaskas, Callistus M. Nguyen, Yao Jiang Zhao, Kai Huang, Cenji Yu et al. · 2023 · Radiotherapy and Oncology
32. Attention-Based DenseNet for Lung Cancer Classification Using CT Scan and Histopathological Images
    Jia Uddin · 2024 · Designs
33. D3C2-Net: Dual-Domain Deep Convolutional Coding Network for Compressive Sensing
    Weiqi Li, Bin Chen, Shuai Liu, Shijie Zhao, Bowen Du, Yongbing Zhang, Jian Zhang · 2024 · IEEE Transactions on Circuits and Systems for Video Technology
34. A survey of emerging applications of diffusion probabilistic models in MRI
    Yuheng Fan, Hanxi Liao, Shiqi Huang, Yimin Luo, Huazhu Fu, Haikun Qi · 2024 · Meta-Radiology
35. Integrating Multi-Omics and Medical Imaging in Artificial Intelligence-Based Cancer Research: An Umbrella Review of Fusion Strategies and Applications
    A. Marouf, J. Rokne, Reda Alhajj · 2025 · Cancers
36. Multi-orientation geometric medical volumes segmentation using 3D multiresolution analysis
    Shadi Mahmoud Faleh AlZu’bi, Yaser Jararweh, Hassan Al-Zoubi, Mohammed W. Elbes, Tarek Ghazi Kanan, Brij Bhooshan Gupta · 2018 · Multimedia Tools and Applications
37. Local bit-plane decoded convolutional neural network features for biomedical image retrieval
    Shiv Ram Dubey, Swalpa Kumar Roy, Soumendu Chakraborty, Snehasis Mukherjee, B.B. Chaudhuri · 2019 · Neural Computing and Applications
38. Hybrid particle swarm optimization-genetic algorithm trained multi-layer perceptron for classification of human glioma from molecular brain neoplasia data
    Kamanasish Bhattacharjee, Millie Pant · 2019 · Cognitive Systems Research
39. Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology
    Ian R. Duffy, Amanda J. Boyle, Neil Vasdev · 2019 · Molecular Imaging
40. Pancreas Segmentation in CT and MRI via Task-Specific Network Design and Recurrent Neural Contextual Learning
    Jinzheng Cai, Le Lü, Fuyong Xing, Lin Yang · 2019 · Advances in computer vision and pattern recognition
41. Deep learning in biomedical image analysis
    Minjeong Kim, Chenggang Clarence Yan, Defu Yang, Qian Wang, Junbo Ma, Guorong Wu A · 2019 · Elsevier eBooks
42. Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks
    Michael T. McCann, Michael A. Unser · 2019 · Foundations and Trends® in Signal Processing
43. Prediction of post-radiotherapy locoregional progression in HPV-associated oropharyngeal squamous cell carcinoma using machine-learning analysis of baseline PET/CT radiomics
    Stefan P. Haider, Kariem Sharaf, Tal Zeevi, Philipp Baumeister, Christoph Andreas Reichel, Reza Forghani, Benjamin Harris Kann, Alexandra Petukhova, Benjamin L. Judson, Manju Lata Prasad et al. · 2020 · Translational Oncology
44. A blind and high-capacity data hiding of DICOM medical images based on fuzzification concepts
    Ahmed Elhadad, A. Ghareeb, Safia Abbas · 2021 · Alexandria Engineering Journal
45. Artificial intelligence in oncology: From bench to clinic
    Jamal A. Elkhader, Olivier Elemento · 2021 · Seminars in Cancer Biology
46. The Role of Radiomics in Lung Cancer: From Screening to Treatment and Follow-Up
    R. El Ayachy, N. Giraud, Paul Giraud, C. Durdux, P. Giraud, A. Burgun, J. Bibault · 2021 · Frontiers in Oncology
47. Fast 3D Registration with Accurate Optimisation and Little Learning for Learn2Reg 2021
    Hanna Siebert, Lasse Hansen, Mattias P. Heinrich‬ · 2022 · Lecture notes in computer science
48. Deep Learning-Based Cancer Detection-Recent Developments, Trend and Challenges
    Gulshan Kumar, Hamed Alqahtani · 2021 · Computer Modeling in Engineering & Sciences
49. A deep learning model for molecular label transfer that enables cancer cell identification from histopathology images
    Andrew Su, HoJoon Lee, Xiao Tan, Carlos Jose Suarez, Noemi Andor, Quan Hoang Nguyen, Hanlee P. Ji · 2022 · npj Precision Oncology
50. Deep learning features encode interpretable morphologies within histological images
    Ali Foroughi pour, Brian S. White, Jonghanne Park, Todd Sheridan, Jeffrey H. Chuang · 2022 · Scientific Reports
51. Transfer Learning-Based Multi-Scale Denoising Convolutional Neural Network for Prostate Cancer Detection
    Kwok Tai Chui, Brij Bhooshan Gupta, Hao Ran Chi, Varsha Arya, Wadee Alhalabi, Miguel Jesus Torres-Ruiz, Chien-wen Shen · 2022 · Cancers
52. Artificial intelligence in the radiomic analysis of glioblastomas: A review, taxonomy, and perspective
    Ming Zhu, Sijia Li, Yu Kuang, Virginia B. Hill, Amy B. Heimberger, Lijie Zhai, Shengjie Zhai · 2022 · Frontiers in Oncology
53. Physical imaging parameter variation drives domain shift
    Oz Kilim, Alex Olar, Tamás Joó, Tamás Palicz, Péter Pollner, István Csabai · 2022 · Scientific Reports
54. Patient Graph Deep Learning to Predict Breast Cancer Molecular Subtype
    Isaac Furtney, Ray M. Bradley, Mansur R. Kabuka · 2023 · IEEE Transactions on Computational Biology and Bioinformatics
55. Enhanced MRI-based brain tumour classification with a novel Pix2pix generative adversarial network augmentation framework
    Efe Precious Onakpojeruo, Mubarak Taiwo Mustapha, Dilber Uzun Ozsahin, İlker Özşahin · 2024 · Brain Communications
56. Prospects for AI clinical summarization to reduce the burden of patient chart review
    Chanseo Lee, Kimon A. Vogt, Sonu Kumar · 2024 · Frontiers in Digital Health
57. Artificial intelligence for chimeric antigen receptor-based therapies: a comprehensive review of current applications and future perspectives
    Muqadas Shahzadi, Hamad Rafique, Ahmad Waheed, Hina Naz, Atifa Waheed, Feruza Ravshanovna Zokirova, Humera Khan · 2024 · Therapeutic Advances in Vaccines and Immunotherapy
58. Genomics of Brain Tumor Imaging
    Whitney B. Pope · 2014 · Neuroimaging Clinics of North America
59. Identification of biomarkers for pseudo and true progression of GBM based on radiogenomics study
    Xiaohua Qian, Hua Tan, Jian Zhang, Keqin Liu, Tie‐Lin Yang, Maode Wang, Waldemar Debinskie, Weilin Zhao, Michael David Chan, Xiaobo Zhou · 2016 · Oncotarget
60. Early detection of lung cancer from CT images: nodule segmentation and classification using deep learning
    Jignesh S. Bhatt, Manjunath V. Joshi, Manu Sharma · 2018 · International Conference on Machine Vision
61. Symmetric convolutional neural network for mandible segmentation
    Ming Yan, Jixiang Guo, Weidong Tian, Yi Zhang · 2018 · Knowledge-Based Systems
62. ROI-based reversible watermarking scheme for ensuring the integrity and authenticity of DICOM MR images
    Asaad F. Qasim, Rob Aspin, Farid Meziane, Peter Hogg · 2018 · Multimedia Tools and Applications
63. Deep multi-modality collaborative learning for distant metastases predication in PET-CT soft-tissue sarcoma studies
    Yige Peng, Lei Bi, Yuyu Guo, Dagan D. Feng, MICHAEL J. FULHAM, Jinman Kim · 2019 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
64. Homology‐based radiomic features for prediction of the prognosis of lung cancer based on CT‐based radiomics
    Noriyuki Kadoya, Shohei Tanaka, Tomohiro Kajikawa, Shunpei Tanabe, Kota Abe, Y. Nakajima, Takaya Yamamoto, Noriyoshi Takahashi, Kazuya Takeda, Suguru Dobashi et al. · 2020 · Medical Physics
65. Unsupervised Multi-Discriminator Generative Adversarial Network for Lung Nodule Malignancy Classification
    Kuang Yan, Tian Lan, Xueqiao Peng, Gati Elvis Selasi, Qiao Liu, Junyi Zhang · 2020 · IEEE Access
66. The Exceptional Responders Initiative: Feasibility of a National Cancer Institute Pilot Study
    Barbara A. Conley, Lou Staudt, Naoko Takebe, David A. Wheeler, Linghua Wang, Maria Cardenas, Viktoriya Korchina, Jean Claude Zenklusen, Lisa M. McShane, James V. Tricoli et al. · 2020 · JNCI Journal of the National Cancer Institute
67. A multi‐objective radiomics model for the prediction of locoregional recurrence in head and neck squamous cell cancer
    Kai Wang, Zhiguo Zhou, Rongfang Wang, Liyuan Chen, Qiongwen Zhang, David Jonathan Sher, Jing Wang · 2020 · Medical Physics
68. Three-dimensional visualization of brain tumor progression based accurate segmentation via comparative holographic projection
    Rania M. Abdelazeem, Doaa Youssef, Jala M. El-Azab, Salah Hassab-Elnaby, Mostafa Agour · 2020 · PLoS ONE
69. C-NMC: B-lineage acute lymphoblastic leukaemia: A blood cancer dataset
    Ritu Gupta, Shiv Gehlot, Anubha Gupta · 2022 · Medical Engineering & Physics
70. National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence
    Fedorov, Andrey, Longabaugh, William J. R., Pot, David, Clunie, David A., Pieper, Steven D., Gibbs, David L., Bridge, Christopher, Herrmann, Markus D., Homeyer, André, Lewis, Rob et al. · 2023 · Radiographics
71. Assesment of Tumor in Breast MRI using Kapur's Thresholding and Active Contour Segmentation
    A. Kirthika, Nadaradjane Sri Madhava Raja, R. Sivakumar, S. Arunmozhi · 2020 · International Conference on System, Computation, Automation and Networking (ICSCAN)
72. Photoacoustic imaging with limited sampling: a review of machine learning approaches
    Ruofan Wang, Jing Zhu, Jun Xia, Junjie Yao, Junhui Shi, Chiye Li · 2023 · Biomedical Optics Express
73. Efficient pulmonary nodules classification using radiomics and different artificial intelligence strategies
    Mohamed Saied, Mourad Raafat Mouhamed, Sherif Yehia, Magdy Mohamed Khalil · 2023 · Insights into Imaging
74. One-Shot Weakly-Supervised Segmentation in 3D Medical Images
    Wenhui Lei, Qi Su, Tianyu Jiang, Ran Gu, Na Wang, Xinglong Liu, Guotai Wang, Xiaofan Zhang, Shaoting Zhang · 2023 · IEEE Transactions on Medical Imaging
75. Clinical Use of a Commercial Artificial Intelligence-Based Software for Autocontouring in Radiation Therapy: Geometric Performance and Dosimetric Impact
    S M Hasibul Hoque, Giovanni Pirrone, Fabio Matrone, Alessandra Donofrio, Giuseppe Fanetti, Angela Caroli, Rahnuma Shahrin Rista, Roberto Bortolus, Michele Avanzo, Annalisa Drigo et al. · 2023 · Cancers
76. FLASH radiotherapy sparing effect on the circulating lymphocytes in pencil beam scanning proton therapy: impact of hypofractionation and dose rate
    Antje Galts, Abdelkhalek Hammi · 2023 · Physics in Medicine and Biology
77. Comprehensive Review on MRI-Based Brain Tumor Segmentation: A Comparative Study from 2017 Onwards
    Amit Verma, Shiv Naresh Shivhare, Shailendra Pratap Singh, Naween Kumar, Anand Nayyar · 2024 · Archives of Computational Methods in Engineering
78. Comprehensive multimodal deep learning survival prediction enabled by a transformer architecture: A multicenter study in glioblastoma
    Ahmed Gomaa, Yixing Huang, Amr Hagag, Charlotte Schmitter, Daniel Höfler, Thomas Weißmann, Katharina Breininger, Manuel Alexander Schmidt, Jenny Stritzelberger, Daniel Delev et al. · 2024 · Neuro-Oncology Advances
79. A secure medical image encryption algorithm for IoMT using a Quadratic-Sine chaotic map and pseudo-parallel confusion-diffusion mechanism
    Ali Mansouri, Pin Sun, Chengzhi Lv, Yinghua Zhu, Xudong Zhao, Hongwei Ge, Changkai Sun · 2025 · Expert Systems with Applications
80. [18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non–Small Cell Lung Cancer
    Sarah A. Mattonen, Guido Davidzon, Shaimaa H. Bakr, Sebastian Echegaray, Ann N. C. Leung, Minal Vasanawala, George Horng, Sandy A. Napel, Viswam S. Nair · 2019 · Tomography
81. Machine Learning based System for Automatic Detection of Leukemia Cancer Cell
    Supriya Mandal, Vani Daivajna, Rajagopalan V. · 2019 · IEEE India Conference
82. IDH1 mutation prediction using MR-based radiomics in glioblastoma: comparison between manual and fully automated deep learning-based approach of tumor segmentation
    Yangsean Choi, Yoonho Nam, Youn Soo Lee, Jiwoong Kim, Kook Jin Ahn, Jinhee Jang, Na‐Young Shin, Bum‐Soo Kim, Sin-Soo Jeon · 2020 · European Journal of Radiology
83. Combination of generative adversarial network and convolutional neural network for automatic subcentimeter pulmonary adenocarcinoma classification
    Yunpeng Wang, Lingxiao Zhou, Mingming Wang, Cheng Shao, Lili Shi, Shuyi Yang, Zhiyong Zhang, Mingxiang Feng, Fei Shan, Lei Liu · 2020 · Quantitative Imaging in Medicine and Surgery
84. A data constrained approach for brain tumour detection using fused deep features and SVM
    Prabira Kumar Sethy, Santi Kumari Behera · 2021 · Multimedia Tools and Applications
85. Comparative study of the methodologies used for subjective medical image quality assessment
    Lucie Lévêque, Meriem Outtas, Hantao Liu, Lu Zhang · 2021 · Physics in Medicine and Biology
86. Radiomic Features Associated With HPV Status on Pretreatment Computed Tomography in Oropharyngeal Squamous Cell Carcinoma Inform Clinical Prognosis
    Bolin Song, Kailin Yang, Jonathan C. Garneau, Cheng Youn Lu, Lin Li, Jonathan K. Lee, Sarah Jane Stock, Nathaniel M. Braman, Can Koyuncu, Paula Toro et al. · 2021 · Frontiers in Oncology
87. A Combined Radiomics and Machine Learning Approach to Distinguish Clinically Significant Prostate Lesions on a Publicly Available MRI Dataset
    Leandro Donisi, Giuseppe Cesarelli, Anna Castaldo, Davide Raffaele De Lucia, Francesca Nessuno, Gaia Spadarella, Carlo Ricciardi · 2021 · Journal of Imaging
88. A blockchain-based protocol for tracking user access to shared medical imaging
    Erikson J. de Aguiar, Alyson J. dos Santos, Rodolfo I. Meneguette, Robson E. De Grande, Jó Ueyama · 2022 · Future Generation Computer Systems
89. Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy
    Raffaella Massafra, Maria Colomba Comes, Samantha Bove, Vittorio Didonna, Gianluca Gatta, Francesco Giotta, Annarita Fanizzi, Daniele La Forgia, Agnese Carmela Latorre, Maria Irene Pastena et al. · 2022 · Journal of Personalized Medicine
90. The diagnosis, classification, and treatment of sarcoma in this era of artificial intelligence and immunotherapy
    Amandine Crombé, Matthieu Roulleaux Dugage, Antoîne Italiano · 2022 · 癌症：英文版
91. RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention–Guided Disease Classification
    Moinak Bhattacharya, Shubham Jain, Prateek Prasanna · 2022 · Lecture notes in computer science
92. Computational Identification of Tumor Anatomic Location Associated with Survival in 2 Large Cohorts of Human Primary Glioblastomas
    Tiffany Ting Liu, Achal Singh Achrol, Lex A. Mitchell, W.A. Du, Joshua J. Loya, Scott Rodriguez, Abdullah Hamid Feroze, Erick M. Westbroek, Kristen W. Yeom, Joshua M. Stuart et al. · 2016 · American Journal of Neuroradiology
93. Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice
    Bakas, Spyridon, Vollmuth, Philipp, Galldiks, Norbert, Booth, Thomas C, Aerts, Hugo J W L, Bi, Wenya Linda, Wiestler, Benedikt, Tiwari, Pallavi, Pati, Sarthak, Baid, Ujjwal et al. · 2024 · The Lancet Oncology
94. Automated Detection Model in Classification of B-Lymphoblast Cells from Normal B-Lymphoid Precursors in Blood Smear Microscopic Images Based on the Majority Voting Technique
    Mustafa Ghaderzadeh, Azamossadat Hosseini, Farkhondeh Asadi, Hassan Abolghasemi, Davood Bashash, Arash Roshanpoor · 2022 · Scientific Programming
95. A Series-Based Deep Learning Approach to Lung Nodule Image Classification
    Mehmet Ali Balcı, Larissa M. Batrancea, Ömer Akgüller, Anca Nichita · 2023 · Cancers
96. Consistency and adversarial semi-supervised learning for medical image segmentation
    Yongqiang Tang, Shilei Wang, Yuxun Qu, Zhihua Cui, Wensheng Zhang · 2023 · Computers in Biology and Medicine
97. A comprehensive review of extreme learning machine on medical imaging
    Yoleidy Huérfano, Marco Mora, Karina Vilches-Ponce, Ruber Hernández-García, Rodrigo Gutiérrez, Miguel Ángel Vera · 2023 · Neurocomputing
98. Impact of signal intensity normalization of MRI on the generalizability of radiomic-based prediction of molecular glioma subtypes
    Martha Foltyn‐Dumitru, Marianne Schell, Aditya Rastogi, Felix Sahm, Tobias Keßler, Wolfgang Wick, Martin Bendszus, Gianluca Brugnara, Philipp Vollmuth · 2023 · European Radiology
99. AI approaches for the discovery and validation of drug targets
    Aaron Wenteler, Claudia Cabrera, Wei Wei, Victor Neduva, Michael R. Barnes · 2024 · Cambridge Prisms Precision Medicine
100. CT-based radiomics nomogram to predict proliferative hepatocellular carcinoma and explore the tumor microenvironment
     Gongzheng Wang, Feier Ding, Kaige Chen, Zhuoshuai Liang, Pengxi Han, Linxiang Wang, Fengyun Cui, Qiang Zhu, Zhaoping Cheng, Xingzhi Chen et al. · 2024 · Journal of Translational Medicine