SN
Sandy Napel
Tomography, X-Ray ComputedImage Processing, Computer-AssistedAlgorithmsradiomicsmachine learningArtificial IntelligenceUser-Computer Interfacecs.LGRadiomicsAngiography
On Valency
published · living versionsW_z8wecm87·v1 · currentpublished
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
with Amber L. Simpson, Michela Antonelli, Spyridon Bakas, Michel Bilello +19
1 version
Preprints & journals
178 papers in the corpus · 1978–2025Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case.40813937 · Whitney, Heather M, Baccile, Rachel, Li, Hui et al.2026 · 0 citationsJournal of imaging informatics in medicine. 2026;39(3):2062-2071
Multimodal data curation via interoperability: use cases with the Medical Imaging and Data Resource Center.40750795 · Chen, Weijie, Whitney, Heather M, Kahaki, Seyed et al.2025 · 6 citationsScientific data. 2025;12(1):1340
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare.39909534 · Lekadir, Karim, Frangi, Alejandro F, Porras, Antonio R et al.2026 · 771 citationsBMJ (Clinical research ed.). 2025;388:e081554
Artificial Intelligence in Radiology: Opportunities and Challenges.38403128 · Flory, Marta N, Napel, Sandy, Tsai, Emily B2024 · 29 citationsSeminars in ultrasound, CT, and MR. 2024;45(2):152-160
Machine learning with multimodal data for COVID-19.37483733 · Chen, Weijie, Sá, Rui C, Bai, Yuntong et al.2023 · 26 citationsHeliyon. 2023;9(7):e17934
Performance of alternative manual and automated deep learning segmentation techniques for the prediction of benign and malignant lung nodules.37564098 · Selby, Heather M, Mukherjee, Pritam, Parham, Christopher et al.2024 · 1 citationJournal of medical imaging (Bellingham, Wash.). 2023;10(4):044006
Early Detection of Lung Cancer in the NLST Dataset.36909593 · Mukherjee, Pritam, Brezhneva, Anna, Napel, Sandy et al.2023 · 1 citationmedRxiv : the preprint server for health sciences. 2023
Predicting recurrence risks in lung cancer patients using multimodal radiomics and random survival forests.36388142 · Christie, Jaryd R, Daher, Omar, Abdelrazek, Mohamed et al.2023 · 19 citationsJournal of medical imaging (Bellingham, Wash.). 2022;9(6):066001
Artificial intelligence and machine learning in cancer imaging.36310650 · Koh, Dow-Mu, Papanikolaou, Nickolas, Bick, Ulrich et al.2022 · 316 citationsCommunications medicine. 2022;2:133
The Medical Segmentation Decathlon.35840566 · Antonelli, Michela, Reinke, Annika, Bakas, Spyridon et al.2022 · 1,372 citationsNature communications. 2022;13(1):4128
Machine learning approach to differentiation of peripheral schwannomas and neurofibromas: A multi-center study.34487172 · Zhang, Michael, Tong, Elizabeth, Wong, Sam et al.2022 · 22 citationsNeuro-oncology. 2022;24(4):601-609
Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge.34264825 · Balagurunathan, Yoganand, Beers, Andrew, Mcnitt-Gray, Michael et al.2021 · 39 citationsIEEE transactions on medical imaging. 2021;40(12):3748-3761
Quantitative image features from radiomic biopsy differentiate oncocytoma from chromophobe renal cell carcinoma.34514033 · Jaggi, Akshay, Mastrodicasa, Domenico, Charville, Gregory W et al.2022 · 5 citationsJournal of medical imaging (Bellingham, Wash.). 2021;8(5):054501
Machine-Learning Approach to Differentiation of Benign and Malignant Peripheral Nerve Sheath Tumors: A Multicenter Study.34131749 · Zhang, Michael, Tong, Elizabeth, Hamrick, Forrest et al.2021 · 20 citationsNeurosurgery. 2021;89(3):509-517
Machine Learning Radiomics Model for Early Identification of Small-Cell Lung Cancer on Computed Tomography Scans.34264747 · Shah, Rajesh P, Selby, Heather M, Mukherjee, Pritam et al.2021 · 20 citationsJCO clinical cancer informatics. 2021;5:746-757
MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.33977272 · Tam, Lydia T, Yeom, Kristen W, Wright, Jason N et al.2022 · 43 citationsNeuro-oncology advances. 2021;3(1):vdab042
Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank.33240940 · Cetin, Irem, Raisi-Estabragh, Zahra, Petersen, Steffen E et al.2026 · 61 citationsFrontiers in cardiovascular medicine. 2020;7:591368
The utility of three-dimensional models in complex microsurgical reconstruction.32971594 · Ogunleye, Adeyemi A, Deptula, Peter L, Inchauste, Suzie M et al.2020 · 31 citationsArchives of plastic surgery. 2020;47(5):428-434
A radiomics approach to analyze cardiac alterations in hypertension2007.10717v1 · Irem Cetin, Steffen E. Petersen, Sandy Napel et al.2020 · 14 citationsarXiv
A Mean-Field Theory for Learning the Schönberg Measure of Radial Basis Functions2006.13330v2 · Masoud Badiei Khuzani, Yinyu Ye, Sandy Napel et al.2020 · 0 citationsarXiv
Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features.32548287 · Jaggi, Akshay, Mattonen, Sarah A, McNitt-Gray, Michael et al.2021 · 13 citationsTomography (Ann Arbor, Mich.). 2020;6(2):111-117
Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets.32548288 · McNitt-Gray, M, Napel, S, Jaggi, A et al.2021 · 76 citationsTomography (Ann Arbor, Mich.). 2020;6(2):118-128
Interreader Variability in Semantic Annotation of Microvascular Invasion in Hepatocellular Carcinoma on Contrast-enhanced Triphasic CT Images.32550600 · Bakr, Shaimaa, Gevaert, Olivier, Patel, Bhavik et al.2021 · 15 citationsRadiology. Imaging cancer. 2020;2(3):e190062
A Shallow Convolutional Neural Network Predicts Prognosis of Lung Cancer Patients in Multi-Institutional CT-Image Data.33791593 · Mukherjee, Pritam, Zhou, Mu, Lee, Edward et al.2024 · 101 citationsNature machine intelligence. 2020;2(5):274-282
Quantitative imaging feature pipeline: a web-based tool for utilizing, sharing, and building image-processing pipelines.32206688 · Mattonen, Sarah A, Gude, Dev, Echegaray, Sebastian et al.2023 · 27 citationsJournal of medical imaging (Bellingham, Wash.). 2020;7(4):042803
The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.32154773 · Zwanenburg, Alex, Vallières, Martin, Abdalah, Mahmoud A et al.2020 · 4,158 citationsRadiology. 2020;295(2):328-338
A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI1909.11854v1 · Irem Cetin, Gerard Sanroma, Steffen E. Petersen et al.2019 · 55 citationsarXiv
Stability and reproducibility of computed tomography radiomic features extracted from peritumoral regions of lung cancer lesions.31494946 · Tunali, Ilke, Hall, Lawrence O, Napel, Sandy et al.2020 · 75 citationsMedical physics. 2019;46(11):5075-5085
Bone Marrow and Tumor Radiomics at 18F-FDG PET/CT: Impact on Outcome Prediction in Non-Small Cell Lung Cancer.31526257 · Mattonen, Sarah A, Davidzon, Guido A, Benson, Jalen et al.2020 · 64 citationsRadiology. 2019;293(2):451-459
[18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non-Small Cell Lung Cancer.30854452 · Mattonen, Sarah A, Davidzon, Guido A, Bakr, Shaimaa et al.2020 · 35 citationsTomography (Ann Arbor, Mich.). 2019;5(1):145-153
A large annotated medical image dataset for the development and evaluation of segmentation algorithms1902.09063v1 · Amber L. Simpson, Michela Antonelli, Spyridon Bakas et al.2019 · 684 citationsarXivon Valency
Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats.30383900 · Napel, Sandy, Mu, Wei, Jardim-Perassi, Bruna V et al.2019 · 229 citationsCancer. 2018;124(24):4633-4649
A radiogenomic dataset of non-small cell lung cancer.30325352 · Bakr, Shaimaa, Gevaert, Olivier, Echegaray, Sebastian et al.2019 · 315 citationsScientific data. 2018;5:180202
Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer.30176944 · Wu, Jia, Li, Xuejie, Teng, Xiaodong et al.2019 · 53 citationsBreast cancer research : BCR. 2018;20(1):101
Quantitative Image Feature Engine (QIFE): an Open-Source, Modular Engine for 3D Quantitative Feature Extraction from Volumetric Medical Images.28993897 · Echegaray, Sebastian, Bakr, Shaimaa, Rubin, Daniel L et al.2019 · 53 citationsJournal of digital imaging. 2018;31(4):403-414
Radiogenomics is the future of treatment response assessment in clinical oncology.29863785 · El Naqa, Issam, Napel, Sandy, Zaidi, Habib2018 · 10 citationsMedical physics. 2018;45(10):4325-4328
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?29994302 · Bernard, Olivier, Lalande, Alain, Zotti, Clement et al.2019 · 2,402 citationsIEEE transactions on medical imaging. 2018;37(11):2514-2525
GFPT2-Expressing Cancer-Associated Fibroblasts Mediate Metabolic Reprogramming in Human Lung Adenocarcinoma.29760045 · Zhang, Weiruo, Bouchard, Gina, Yu, Alice et al.2019 · 122 citationsCancer research. 2018;78(13):3445-3457
Intratumoral Spatial Heterogeneity at Perfusion MR Imaging Predicts Recurrence-free Survival in Locally Advanced Breast Cancer Treated with Neoadjuvant Chemotherapy.29714680 · Wu, Jia, Cao, Guohong, Sun, Xiaoli et al.2018 · 217 citationsRadiology. 2018;288(1):26-35
Erratum: Semi-automated pulmonary nodule interval segmentation using the NLST data.29894564 · Balagurunathan, Yoganand, Beers, Andrew, Kalpathy-Cramer, Jayashree et al.2024 · 1 citationMedical physics. 2018;45(6):2689-2690
Semi-automated pulmonary nodule interval segmentation using the NLST data.29363773 · Balagurunathan, Yoganand, Beers, Andrew, Kalpathy-Cramer, Jayashree et al.2018 · 19 citationsMedical physics. 2018;45(3):1093-1107
Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches.28982791 · Zhou, M, Scott, J, Chaudhury, B et al.2019 · 416 citationsAJNR. American journal of neuroradiology. 2018;39(2):208-216
Noninvasive radiomics signature based on quantitative analysis of computed tomography images as a surrogate for microvascular invasion in hepatocellular carcinoma: a pilot study.28840174 · Bakr, Shaimaa, Echegaray, Sebastian, Shah, Rajesh et al.2020 · 78 citationsJournal of medical imaging (Bellingham, Wash.). 2017;4(4):041303
Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications.28727543 · Zhou, Mu, Leung, Ann, Echegaray, Sebastian et al.2018 · 190 citationsRadiology. 2018;286(1):307-315
Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer.28708462 · Wu, Jia, Li, Bailiang, Sun, Xiaoli et al.2017 · 124 citationsRadiology. 2017;285(2):401-413
Variations in the functional visual field for detection of lung nodules on chest computed tomography: Impact of nodule size, distance, and local lung complexity.28419484 · Ebner, Lukas, Tall, Martin, Choudhury, Kingshuk Roy et al.2018 · 20 citationsMedical physics. 2017;44(7):3483-3490
Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative 18F FDG-PET/CT metrics.28881771 · Minamimoto, Ryogo, Jamali, Mehran, Gevaert, Olivier et al.2017 · 42 citationsOncotarget. 2017;8(32):52792-52801
Predictive radiogenomics modeling of EGFR mutation status in lung cancer.28139704 · Gevaert, Olivier, Echegaray, Sebastian, Khuong, Amanda et al.2018 · 160 citationsScientific reports. 2017;7:41674
Adaptive local window for level set segmentation of CT and MRI liver lesions.28157660 · Hoogi, Assaf, Beaulieu, Christopher F, Cunha, Guilherme M et al.2018 · 79 citationsMedical image analysis. 2017;37:46-55
Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features.28149958 · Kalpathy-Cramer, Jayashree, Mamomov, Artem, Zhao, Binsheng et al.2026 · 127 citationsTomography (Ann Arbor, Mich.). 2016;2(4):430-437
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