| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/jdi/ClarkVSFKKMPMPTP13 |
| P6179 | Dimensions Publication ID | 1044365820 |
| P356 | DOI | 10.1007/S10278-013-9622-7 |
| P3181 | OpenCitations bibliographic resource ID | 1388437 |
| P932 | PMC publication ID | 3824915 |
| P698 | PubMed publication ID | 23884657 |
| P5875 | ResearchGate publication ID | 251878461 |
| P50 | author | Kirk R. Smith | Q6415511 |
| P2093 | author name string | Kenneth Clark | |
| Stephen Moore | |||
| Fred Prior | |||
| Michael Pringle | |||
| John Freymann | |||
| Justin Kirby | |||
| Lawrence Tarbox | |||
| Stanley Phillips | |||
| David Maffitt | |||
| Paul Koppel | |||
| Bruce Vendt | |||
| P2860 | cites work | Biomedical informatics research network: building a national collaboratory to hasten the derivation of new understanding and treatment of disease | Q38457757 |
| GenBank | Q73030975 | ||
| big data: The future of biocuration | Q24650969 | ||
| The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository | Q26253943 | ||
| Informatics and data mining tools and strategies for the human connectome project | Q28743073 | ||
| Silent Cerebral Infarct Transfusion (SIT) trial imaging core: application of novel imaging information technology for rapid and central review of MRI of the brain | Q31152018 | ||
| Collecting 48,000 CT exams for the lung screening study of the National Lung Screening Trial | Q33367598 | ||
| Mining the draft human genome | Q33936722 | ||
| The Human Connectome Project: a data acquisition perspective. | Q34172421 | ||
| Regulatory compliance requirements for an open source electronic image trial management system | Q36024066 | ||
| A national human neuroimaging collaboratory enabled by the Biomedical Informatics Research Network (BIRN). | Q37390876 | ||
| Quantitative imaging for evaluation of response to cancer therapy. | Q37429841 | ||
| P433 | issue | 6 | |
| P407 | language of work or name | English | Q1860 |
| P304 | page(s) | 1045-57 | |
| P577 | publication date | 2013-12-01 | |
| P1433 | published in | Journal of Digital Imaging | Q15749107 |
| P1476 | title | The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository | |
| P478 | volume | 26 |
| Q31136593 | -Omic and Electronic Health Record Big Data Analytics for Precision Medicine |
| Q41690558 | 2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer |
| Q94686791 | 3D-MCN: A 3D Multi-scale Capsule Network for Lung Nodule Malignancy Prediction |
| Q61810504 | 3D-printed breast phantom for multi-purpose and multi-modality imaging |
| Q91673025 | A 3D-Printed Patient-Specific Phantom for External Beam Radiation Therapy of Prostate Cancer |
| Q28647078 | A Query Tool for Investigator Access to the Data and Images of the National Lung Screening Trial |
| Q93081525 | A Radiogenomic Approach for Decoding Molecular Mechanisms Underlying Tumor Progression in Prostate Cancer |
| Q36227810 | A longitudinal four-dimensional computed tomography and cone beam computed tomography dataset for image-guided radiation therapy research in lung cancer. |
| Q61795892 | A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic- and molecular-phenotypes of epithelial ovarian cancer |
| Q90019797 | A novel fused convolutional neural network for biomedical image classification |
| Q90573617 | A quantitative validation of segmented colon in virtual colonoscopy using image moments |
| Q57460329 | A radiogenomic dataset of non-small cell lung cancer |
| Q61948598 | A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study |
| Q110950383 | A rotation and translation invariant method for 3D organ image classification using deep convolutional neural networks |
| Q57210666 | A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data |
| Q47797421 | A versatile method for bladder segmentation in computed tomography two-dimensional images under adverse conditions. |
| Q90172183 | AI-based Prognostic Imaging Biomarkers for Precision Neurooncology: the ReSPOND Consortium |
| Q64115067 | Advancing Semantic Interoperability of Image Annotations: Automated Conversion of Non-standard Image Annotations in a Commercial PACS to the Annotation and Image Markup |
| Q47096364 | Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features |
| Q50422224 | Agile convolutional neural network for pulmonary nodule classification using CT images. |
| Q61450839 | An Appraisal of Lung Nodules Automatic Classification Algorithms for CT Images |
| Q64249123 | An Efficient Framework for Accurate Arterial Input Selection in DSC-MRI of Glioma Brain Tumors |
| Q47413003 | An Efficient Pipeline for Abdomen Segmentation in CT Images. |
| Q58693277 | An Evaluation of HTML5 and WebGL for Medical Imaging Applications |
| Q59794433 | An annotated test-retest collection of prostate multiparametric MRI |
| Q64246693 | An overview of publicly available patient-centered prostate cancer datasets |
| Q51734181 | Analysis of Vestibular Labyrinthine Geometry and Variation in the Human Temporal Bone. |
| Q47431417 | Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT. |
| Q94546141 | Applications of radiomics in precision diagnosis, prognostication and treatment planning of head and neck squamous cell carcinomas |
| Q36997737 | Approaches to uncovering cancer diagnostic and prognostic molecular signatures |
| Q96584151 | Artificial intelligence and mechanistic modeling for clinical decision making in oncology |
| Q98726059 | Artificial intelligence in radiation oncology |
| Q57248306 | Artificial intelligence in radiology |
| Q61444720 | Assessing robustness of radiomic features by image perturbation |
| Q88222414 | Assessing the Effects of Software Platforms on Volumetric Segmentation of Glioblastoma |
| Q64100789 | Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy for HER2 (ERBB2)-Positive Breast Cancer |
| Q33899089 | Associations between gene expression profiles of invasive breast cancer and Breast Imaging Reporting and Data System MRI lexicon |
| Q36731923 | Auto Diagnostics of Lung Nodules Using Minimal Characteristics Extraction Technique |
| Q56333971 | Auto-segmentation for Thoracic Radiation Treatment Planning: A Grand Challenge at AAPM 2017 |
| Q47251502 | Automated image quality assessment for chest CT scans |
| Q56895411 | Automatic Multi-Organ Segmentation on Abdominal CT With Dense V-Networks |
| Q55266284 | Automatic Prostate Cancer Segmentation Using Kinetic Analysis in Dynamic Contrast-Enhanced MRI. |
| Q92691751 | Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement |
| Q38979518 | Automatic intensity windowing of mammographic images based on a perceptual metric |
| Q51738687 | Automatic interstitial photodynamic therapy planning via convex optimization. |
| Q94237696 | Automatic mass detection in mammograms using deep convolutional neural networks |
| Q91954724 | Automatic multiorgan segmentation in thorax CT images using U-net-GAN |
| Q99637170 | Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net |
| Q45945284 | Big data management challenges in health research-a literature review. |
| Q64278990 | Biobanking in health care: evolution and future directions |
| Q46478772 | Biomechanical model for computing deformations for whole-body image registration: A meshless approach |
| Q30353922 | Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging. |
| Q90128222 | Bone Marrow and Tumor Radiomics at 18F-FDG PET/CT: Impact on Outcome Prediction in Non-Small Cell Lung Cancer |
| Q62698703 | Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets |
| Q56764250 | Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes |
| Q90569829 | Bringing radiomics into a multi-omics framework for a comprehensive genotype-phenotype characterization of oncological diseases |
| Q101574005 | CT-ORG, a new dataset for multiple organ segmentation in computed tomography |
| Q91958609 | Call for Data Standardization: Lessons Learned and Recommendations in an Imaging Study |
| Q102379309 | Chest imaging representing a COVID-19 positive rural U.S. population |
| Q92132871 | Classification of Lung Nodules Based on Deep Residual Networks and Migration Learning |
| Q64122547 | Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks |
| Q92167597 | Classification of suspicious lesions on prostate multiparametric MRI using machine learning |
| Q59333040 | Classification of the glioma grading using radiomics analysis |
| Q104485892 | Clinical deployment of AI for prostate cancer diagnosis |
| Q38378703 | Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research. |
| Q96128464 | Comparative study of preclinical mouse models of high-grade glioma for nanomedicine research: the importance of reproducing blood-brain barrier heterogeneity |
| Q36235803 | Comparison of Safety Margin Generation Concepts in Image Guided Radiotherapy to Account for Daily Head and Neck Pose Variations |
| Q41683896 | Comparison of novel multi-level Otsu (MO-PET) and conventional PET segmentation methods for measuring FDG metabolic tumor volume in patients with soft tissue sarcoma |
| Q36803764 | Computational Identification of Tumor Anatomic Location Associated with Survival in 2 Large Cohorts of Human Primary Glioblastomas |
| Q64934477 | Computational assessment of stomach tumor volume from multi-slice computerized tomography images in presence of type 2 cancer. |
| Q92316743 | Computed Tomography (CT) Image Quality Enhancement via a Uniform Framework Integrating Noise Estimation and Super-Resolution Networks |
| Q45943371 | Computer-aided biomarker discovery for precision medicine: data resources, models and applications. |
| Q55129712 | Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization. |
| Q58558944 | Content-Based Image Retrieval System for Pulmonary Nodules Using Optimal Feature Sets and Class Membership-Based Retrieval |
| Q102053817 | Context aware deep learning for brain tumor segmentation, subtype classification, and survival prediction using radiology images |
| Q64956383 | Convolutional neural networks: an overview and application in radiology. |
| Q38369579 | Creation and Curation of the Society of Imaging Informatics in Medicine Hackathon Dataset. |
| Q98284689 | DICOM Re-encoding of Volumetrically Annotated Lung Imaging Data Consortium (LIDC) Nodules |
| Q24658635 | DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research |
| Q62490299 | Data Engineering for Machine Learning in Women's Imaging and Beyond |
| Q90115402 | Data-driven translational prostate cancer research: from biomarker discovery to clinical decision |
| Q28646296 | De-identification of Medical Images with Retention of Scientific Research Value |
| Q35861706 | Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma |
| Q55120753 | Deep Learning data integration for better risk stratification models of bladder cancer. |
| Q90084880 | Deep Learning for Low-Dose CT Denoising Using Perceptual Loss and Edge Detection Layer |
| Q92438483 | Deep learning based image reconstruction algorithm for limited-angle translational computed tomography |
| Q64103201 | Deep learning in head & neck cancer outcome prediction |
| Q104485977 | Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation |
| Q60636540 | Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas |
| Q90407262 | DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning |
| Q38603036 | Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI |
| Q90318803 | Development of a radiomics nomogram based on the 2D and 3D CT features to predict the survival of non-small cell lung cancer patients |
| Q60355518 | Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules |
| Q90884148 | Distributed radiomics as a signature validation study using the Personal Health Train infrastructure |
| Q91920053 | Domain-Based Analysis of Colon Polyp in CT Colonography Using Image-Processing Techniques |
| Q92273685 | Dynamic conformal arcs for lung stereotactic body radiation therapy: A comparison with volumetric-modulated arc therapy |
| Q37490121 | Effect of color visualization and display hardware on the visual assessment of pseudocolor medical images. |
| Q57022953 | Effect of machine learning methods on predicting NSCLC overall survival time based on Radiomics analysis |
| Q92934519 | Effective Diagnosis and Treatment through Content-Based Medical Image Retrieval (CBMIR) by Using Artificial Intelligence |
| Q92734093 | Effects of Focused-Ultrasound-and-Microbubble-Induced Blood-Brain Barrier Disruption on Drug Transport under Liposome-Mediated Delivery in Brain Tumour: A Pilot Numerical Simulation Study |
| Q89644741 | Efficacy evaluation of 2D, 3D U-Net semantic segmentation and atlas-based segmentation of normal lungs excluding the trachea and main bronchi |
| Q91844569 | Efficient CT Image Reconstruction in a GPU Parallel Environment |
| Q91996027 | Eliminating biasing signals in lung cancer images for prognosis predictions with deep learning |
| Q62491509 | Emerging Applications of Artificial Intelligence in Neuro-Oncology |
| Q92664328 | Enhancing Clinical Data and Clinical Research Data with Biomedical Ontologies - Insights from the Knowledge Representation Perspective |
| Q58947476 | Evolutionary image simplification for lung nodule classification with convolutional neural networks |
| Q31121923 | Exploring cancer genomic data from the cancer genome atlas project |
| Q47940788 | Fast and robust brain tumor segmentation using level set method with multiple image information |
| Q91856172 | Feasibility of synthetic computed tomography generated with an adversarial network for multi-sequence magnetic resonance-based brain radiotherapy |
| Q98158614 | Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data |
| Q55002416 | Finding relevant biomedical datasets: the UC San Diego solution for the bioCADDIE Retrieval Challenge. |
| Q35843978 | Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features |
| Q27319225 | G-DOC Plus - an integrative bioinformatics platform for precision medicine. |
| Q31161185 | GIFT-Cloud: A data sharing and collaboration platform for medical imaging research |
| Q58785727 | Glioblastoma Recurrence Correlates With Increased APE1 and Polarization Toward an Immuno-Suppressive Microenvironment |
| Q90078939 | Gross tumor volume segmentation for head and neck cancer radiotherapy using deep dense multi-modality network |
| Q104478942 | Handcrafted versus deep learning radiomics for prediction of cancer therapy response |
| Q38881075 | High-resolution anatomic correlation of cyclic motor patterns in the human colon: Evidence of a rectosigmoid brake |
| Q55317389 | Highly accurate model for prediction of lung nodule malignancy with CT scans. |
| Q35900753 | How Will Big Data Improve Clinical and Basic Research in Radiation Therapy? |
| Q39598112 | Identification of biomarkers for pseudo and true progression of GBM based on radiogenomics study |
| Q90413974 | Identifying BAP1 Mutations in Clear-Cell Renal Cell Carcinoma by CT Radiomics: Preliminary Findings |
| Q89926672 | Identifying relationships between imaging phenotypes and lung cancer-related mutation status: EGFR and KRAS |
| Q57814701 | Image descriptors in radiology images: a systematic review |
| Q58764044 | Imaging and clinical data archive for head and neck squamous cell carcinoma patients treated with radiotherapy |
| Q48071853 | Imaging biobanks in oncology: European perspective |
| Q92273911 | Impact of image preprocessing methods on reproducibility of radiomic features in multimodal magnetic resonance imaging in glioblastoma |
| Q92720701 | Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology |
| Q39233163 | Increased robustness in reference region model analysis of DCE MRI using two-step constrained approaches |
| Q89560738 | Individual-patient prediction of meningioma malignancy and survival using the Surveillance, Epidemiology, and End Results database |
| Q47723749 | Influence of Contrast Administration on Computed Tomography-Based Analysis of Visceral Adipose and Skeletal Muscle Tissue in Clear Cell Renal Cell Carcinoma. |
| Q62490697 | Influence of segmentation margin on machine learning-based high-dimensional quantitative CT texture analysis: a reproducibility study on renal clear cell carcinomas |
| Q55347904 | Inhibition of Wnt/beta-catenin signaling downregulates expression of aldehyde dehydrogenase isoform 3A1 (ALDH3A1) to reduce resistance against temozolomide in glioblastoma in vitro. |
| Q58886331 | Integrating Open Data on Cancer in Support to Tumor Growth Analysis |
| Q95267906 | Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation |
| Q31113520 | Integrative analysis of diffusion-weighted MRI and genomic data to inform treatment of glioblastoma |
| Q54997338 | Integrative analysis of imaging and transcriptomic data of the immune landscape associated with tumor metabolism in lung adenocarcinoma: Clinical and prognostic implications. |
| Q40007526 | Integrative radiogenomic analysis for multicentric radiophenotype in glioblastoma |
| Q64114042 | Inter-rater agreement in glioma segmentations on longitudinal MRI |
| Q94550456 | Isocitrate dehydrogenase (IDH) status prediction in histopathology images of gliomas using deep learning |
| Q52600762 | Joint solution for PET image segmentation, denoising, and partial volume correction. |
| Q38374617 | LUNGx Challenge for computerized lung nodule classification |
| Q35810830 | LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned |
| Q44648729 | Learning to Compose Domain-Specific Transformations for Data Augmentation |
| Q90205962 | Lung Cancer Radiomics: Highlights from the IEEE Video and Image Processing Cup 2018 Student Competition |
| Q36185827 | MIRMAID: A Content Management System for Medical Image Analysis Research |
| Q37348196 | MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays |
| Q38438803 | MRI features predict survival and molecular markers in diffuse lower-grade gliomas |
| Q47108716 | MRI to MGMT: predicting methylation status in glioblastoma patients using convolutional recurrent neural networks |
| Q64246173 | Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas |
| Q55457066 | Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status. |
| Q51068702 | Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment. |
| Q61800828 | Mass Effect Deformation Heterogeneity (MEDH) on Gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility study |
| Q59465622 | Medical 3D printing for vascular interventions and surgical oncology: a primer for the 2016 radiological society of North America (RSNA) hands-on course in 3D printing |
| Q39096214 | Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree |
| Q39172977 | Mesoscopic imaging of glioblastomas: Are diffusion, perfusion and spectroscopic measures influenced by the radiogenetic phenotype? |
| Q55260399 | Methylation of L1RE1, RARB, and RASSF1 function as possible biomarkers for the differential diagnosis of lung cancer. |
| Q49662236 | Modification of population based arterial input function to incorporate individual variation. |
| Q52589507 | Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival "early on" in neoadjuvant treatment of breast cancer. |
| Q92535511 | Multi-Disease Segmentation of Gliomas and White Matter Hyperintensities in the BraTS Data Using a 3D Convolutional Neural Network |
| Q47169617 | Multi-field query expansion is effective for biomedical dataset retrieval. |
| Q36282168 | Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data |
| Q93089261 | Multi-stage Association Analysis of Glioblastoma Gene Expressions with Texture and Spatial Patterns |
| Q35707516 | Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival |
| Q55456990 | Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project. |
| Q30810414 | Multisite Image Data Collection and Management Using the RSNA Image Sharing Network |
| Q46868946 | Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
| Q92535499 | Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients |
| Q92540152 | Non-invasive classification of non-small cell lung cancer: a comparison between random forest models utilising radiomic and semantic features |
| Q54948216 | Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis. |
| Q90035749 | Noninvasive O6 Methylguanine-DNA Methyltransferase Status Prediction in Glioblastoma Multiforme Cancer Using Magnetic Resonance Imaging Radiomics Features: Univariate and Multivariate Radiogenomics Analysis |
| Q110949660 | On the classification of simple and complex biological images using Krawtchouk moments and Generalized pseudo-Zernike moments: a case study with fly wing images and breast cancer mammograms |
| Q35849051 | Optimising delineation accuracy of tumours in PET for radiotherapy planning using blind deconvolution |
| Q28595690 | Overview of the American Society for Radiation Oncology-National Institutes of Health-American Association of Physicists in Medicine Workshop 2015: Exploring Opportunities for Radiation Oncology in the Era of Big Data |
| Q92167793 | PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images |
| Q47421539 | Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration. |
| Q90752608 | Pragmatic randomised clinical trial of proton versus photon therapy for patients with non-metastatic breast cancer: the Radiotherapy Comparative Effectiveness (RadComp) Consortium trial protocol |
| Q58135337 | Predicting Genotype and Survival in Glioma Using Standard Clinical MR Imaging Apparent Diffusion Coefficient Images: A Pilot Study from The Cancer Genome Atlas |
| Q89459336 | Predicting the ISUP grade of clear cell renal cell carcinoma with multiparametric MR and multiphase CT radiomics |
| Q92649427 | Prediction of 1p/19q Codeletion in Diffuse Glioma Patients Using Pre-operative Multiparametric Magnetic Resonance Imaging |
| Q92735165 | Prediction of Treatment Response to Neoadjuvant Chemotherapy for Breast Cancer via Early Changes in Tumor Heterogeneity Captured by DCE-MRI Registration |
| Q31042155 | Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data |
| Q92132606 | Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis |
| Q100733720 | Prediction of post-radiotherapy locoregional progression in HPV-associated oropharyngeal squamous cell carcinoma using machine-learning analysis of baseline PET/CT radiomics |
| Q89145868 | Prediction of survival with multi-scale radiomic analysis in glioblastoma patients |
| Q92110425 | Preliminary Clinical Study of the Differences Between Interobserver Evaluation and Deep Convolutional Neural Network-Based Segmentation of Multiple Organs at Risk in CT Images of Lung Cancer |
| Q98771130 | Preoperative CT Radiomics Predicting the SSIGN Risk Groups in Patients With Clear Cell Renal Cell Carcinoma: Development and Multicenter Validation |
| Q89754794 | Preparing Medical Imaging Data for Machine Learning |
| Q30992145 | Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images |
| Q38635505 | Prognostic value and molecular correlates of a CT image-based quantitative pleural contact index in early stage NSCLC. |
| Q98170174 | Prognostic value of baseline [18F]-fluorodeoxyglucose positron emission tomography parameters MTV, TLG and asphericity in an international multicenter cohort of nasopharyngeal carcinoma patients |
| Q91899181 | Quantifying the incremental value of deep learning: Application to lung nodule detection |
| Q60919520 | Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid Tumors |
| Q28658385 | Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive |
| Q31142731 | Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set |
| Q90613088 | Quantitative imaging feature pipeline: a web-based tool for utilizing, sharing, and building image-processing pipelines |
| Q47192935 | Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma |
| Q89807657 | Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma |
| Q38608781 | Radiology and Enterprise Medical Imaging Extensions (REMIX). |
| Q104073665 | Radiomic features based on Hessian index for prediction of prognosis in head-and-neck cancer patients |
| Q36173696 | Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings. |
| Q89741643 | Radiomic profiles in diffuse glioma reveal distinct subtypes with prognostic value |
| Q98164432 | Radiomics feature reproducibility under inter-rater variability in segmentations of CT images |
| Q90178665 | 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 |
| Q38599041 | Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer. |
| Q64232652 | Radiomics-based machine learning methods for isocitrate dehydrogenase genotype prediction of diffuse gliomas |
| Q34502075 | Radiomics: Images Are More than Pictures, They Are Data |
| Q59329059 | Radiomics: the facts and the challenges of image analysis |
| Q95804720 | Radtools: R utilities for convenient extraction of medical image metadata |
| Q64054964 | Radtools: R utilities for smooth navigation of medical image data |
| Q46034873 | Real-time tomosynthesis for radiation therapy guidance. |
| Q99630278 | Reciprocal change in Glucose metabolism of Cancer and Immune Cells mediated by different Glucose Transporters predicts Immunotherapy response |
| Q56394952 | Reengineering Workflow for Curation of DICOM Datasets |
| Q57132557 | Relationships Between Human-Extracted MRI Tumor Phenotypes of Breast Cancer and Clinical Prognostic Indicators Including Receptor Status and Molecular Subtype |
| Q57049453 | Reliable gene mutation prediction in clear cell renal cell carcinoma through multi-classifier multi-objective radiogenomics model |
| Q90407243 | Reproducing two-dimensional mammograms with three-dimensional printed phantoms |
| Q47208595 | Residual Convolutional Neural Network for Determination of IDH Status in Low- and High-grade Gliomas from MR Imaging |
| Q90175822 | Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches |
| Q96305377 | Segmentation of the Prostatic Gland and the Intraprostatic Lesions on Multiparametic Magnetic Resonance Imaging Using Mask Region-Based Convolutional Neural Networks |
| Q38376392 | Semantic Technologies and Bio-Ontologies |
| Q92612586 | Simultaneous emission and attenuation reconstruction in time-of-flight PET using a reference object |
| Q28607337 | Somatic mutations associated with MRI-derived volumetric features in glioblastoma |
| Q38927317 | Spatiotemporal genomic architecture informs precision oncology in glioblastoma |
| Q36509010 | Special Section Guest Editorial:Radiomics and Imaging Genomics: Quantitative Imaging for Precision Medicine |
| Q89973820 | Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study |
| Q97681259 | Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics |
| Q93204966 | Technical Note: More accurate and efficient segmentation of organs-at-risk in radiotherapy with convolutional neural networks cascades |
| Q89564649 | Textural radiomic features and time-intensity curve data analysis by dynamic contrast-enhanced MRI for early prediction of breast cancer therapy response: preliminary data |
| Q62489353 | The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges |
| Q35066321 | The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge |
| Q26253943 | The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository |
| Q64097313 | The French glioblastoma biobank (FGB): a national clinicobiological database |
| Q90184582 | The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping |
| Q89896130 | The Impact of Normalization Approaches to Automatically Detect Radiogenomic Phenotypes Characterizing Breast Cancer Receptors Status |
| Q94528683 | The Impact of Obesity on Tumor Glucose Uptake in Breast and Lung Cancer |
| Q100439783 | The future of digital health with federated learning |
| Q47962305 | The public cancer radiology imaging collections of The Cancer Imaging Archive |
| Q98170178 | Three-dimensional visualization of brain tumor progression based accurate segmentation via comparative holographic projection |
| Q48212426 | To share or not to share? Expected pros and cons of data sharing in radiological research |
| Q91912539 | Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning |
| Q92140365 | Towards Advanced Interactive Visualization for Virtual Atlases |
| Q59468710 | Training and validation of a novel 4-miRNA ratio model (MiCaP) for prediction of postoperative outcome in prostate cancer patients |
| Q92906986 | Tumor Transcriptome Reveals High Expression of IL-8 in Non-Small Cell Lung Cancer Patients with Low Pectoralis Muscle Area and Reduced Survival |
| Q99419185 | Tumor immune profiles noninvasively estimated by FDG PET with deep learning correlate with immunotherapy response in lung adenocarcinoma |
| Q57192726 | Tumor-aware, Adversarial Domain Adaptation from CT to MRI for Lung Cancer Segmentation |
| Q104487894 | Universal scaling laws rule explosive growth in human cancers |
| Q30394115 | Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging. |
| Q61796722 | Ventricular-Subventricular Zone Contact by Glioblastoma is Not Associated with Molecular Signatures in Bulk Tumor Data |
| Q93104282 | Visual Interpretation of Convolutional Neural Network Predictions in Classifying Medical Image Modalities |
| Q92110416 | Volumetric and Voxel-Wise Analysis of Dominant Intraprostatic Lesions on Multiparametric MRI |
| Q96230216 | Weakly-supervised learning for lung carcinoma classification using deep learning |
| Q99716373 | Web-Based Technology for Remote Viewing of Radiological Images: App Validation |
| Q99562785 | XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype Glioblastoma |
| Q64085072 | [18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non-Small Cell Lung Cancer |
Search more.