Shen, Dinggang

Deep learning in medical image analysis

Shen, D., Wu, G., & Suk, H.-I. (2017) · Annual Review of Biomedical Engineering

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 4,968

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · Apollo - University of Cambridge Repository

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,441

Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · arXiv

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,441

Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19

Shi, F., Wang, J., Shi, J., Wu, Z., Wang, Q., Tang, Z., He, K., Shi, Y., & Shen, D. (2021) · IEEE Reviews in Biomedical Engineering

COVID-19 diagnosis using AIArtificial Intelligence in Healthcare and Education

Cited by 1,404

Hierarchical Feature Representation and Multimodal Fusion with Deep Learning for AD/MCI Diagnosis

Suk, H.-I., Lee, S.-W., & Shen, D. (2014) · NeuroImage

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 968

Deep convolutional neural networks for multi-modality isointense infant brain image segmentation

Zhang, W., Li, R., Deng, H., Wang, L., Lin, W., Ji, S., & Shen, D. (2015) · NeuroImage

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 817

Computer-aided diagnosis with deep learning architecture: applications to breast lesions in US images and pulmonary nodules in CT scans

Cheng, J.-Z., Ni, D., Chou, Y.-H., Qin, J., Tiu, C.-M., Chang, Y.-C., Huang, C.-S., Shen, D., & Chen, C.-M. (2016) · Scientific Reports

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 755

A deep learning system for detecting diabetic retinopathy across the disease spectrum

Dai, L., Wu, L., Li, H., Cai, C., Wu, Q., Kong, H., Liu, R., Wang, X., Hou, X., Liu, Y., et al. (2021) · Nature Communications

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 620

Evidence on the emergence of the brain's default network from 2-week-old to 2-year-old healthy pediatric subjects

Gao, W., Zhu, H., Giovanello, K. S., Smith, J. K., Shen, D., Gilmore, J. H., & Lin, W. (2009) · Proceedings of the National Academy of Sciences

Functional Brain Connectivity StudiesMind wandering and attention

Cited by 601

Hierarchical fully convolutional network for joint atrophy localization and Alzheimer’s disease diagnosis using structural MRI

Lian, C., Liu, M., Zhang, J., & Shen, D. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Dementia and Cognitive Impairment ResearchMedical Image Segmentation Techniques

Cited by 544

Longitudinal Development of Cortical and Subcortical Gray Matter from Birth to 2 Years

Gilmore, J. H., Shi, F., Woolson, S. L., Knickmeyer, R. C., Short, S. J., Lin, W., Zhu, H., Hamer, R. M., Styner, M., & Shen, D. (2012) · Cerebral Cortex

Functional Brain Connectivity StudiesFetal and Pediatric Neurological Disorders

Cited by 456

Family Poverty Affects the Rate of Human Infant Brain Growth

Hanson, J. L., Hair, N., Shen, D. G., Shi, F., Gilmore, J. H., Wolfe, B. L., & Pollak, S. D. (2013) · PLoS ONE

Child Nutrition and Water AccessChild Abuse and Trauma

Cited by 430

Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging

Davatzikos, C., Fan, Y., Wu, X., Shen, D., & Resnick, S. M. (2008) · Neurobiology of Aging

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 385

Dynamic Development of Regional Cortical Thickness and Surface Area in Early Childhood

Lyall, A. E., Shi, F., Geng, X., Woolson, S., Li, G., Wang, L., Hamer, R. M., Shen, D., & Gilmore, J. H. (2015) · Cerebral Cortex

Fetal and Pediatric Neurological DisordersNeurogenesis and neuroplasticity mechanisms

Cited by 376

A deep learning system for predicting time to progression of diabetic retinopathy

Dai, L., Sheng, B., Chen, T., Wu, Q., Liu, R., Cai, C., Wu, L., Yang, D., Hamzah, H., Liu, Y., et al. (2024) · Nature Medicine

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 339

Fully convolutional networks for multi-modality isointense infant brain image segmentation

Nie, D., Wang, L., Gao, Y., & Shen, D. (2016) · 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 304

Puberty-related influences on brain development

Giedd, J. N., Clasen, L. S., Lenroot, R., Greenstein, D., Wallace, G. L., Ordaz, S., Molloy, E. A., Blumenthal, J. D., Tossell, J. W., Stayer, C., et al. (2006) · Molecular and Cellular Endocrinology

Sexual Differentiation and DisordersHypothalamic control of reproductive hormones

Cited by 300

Birnet: Brain image registration using dual-supervised fully convolutional networks

Fan, J., Cao, X., Yap, P.-T., & Shen, D. (2019) · Medical Image Analysis

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 297

3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients

Nie, D., Zhang, H., Adeli, E., Liu, L., & Shen, D. (2016) · Lecture Notes in Computer Science

Radiomics and Machine Learning in Medical ImagingGlioma Diagnosis and Treatment

Cited by 282

Temporal and spatial evolution of brain network topology during the first two years of life

Gao, W., Gilmore, J. H., Giovanello, K. S., Smith, J. K., Shen, D., Zhu, H., & Lin, W. (2011) · PLoS ONE

Functional Brain Connectivity StudiesComplex Network Analysis Techniques

Cited by 272

Mapping Longitudinal Development of Local Cortical Gyrification in Infants from Birth to 2 Years of Age

Li, G., Wang, L., Shi, F., Lyall, A. E., Lin, W., Gilmore, J. H., & Shen, D. (2014) · The Journal of Neuroscience

Fetal and Pediatric Neurological DisordersAdvanced Neuroimaging Techniques and Applications

Cited by 251

Brain anatomical networks in early human brain development

Fan, Y., Shi, F., Smith, J. K., Lin, W., Gilmore, J. H., & Shen, D. (2011) · NeuroImage

Functional Brain Connectivity StudiesAdvanced Neuroimaging Techniques and Applications

Cited by 225

A novel relational regularization feature selection method for joint regression and classification in ad diagnosis

Zhu, X., Suk, H.-I., Wang, L., Lee, S.-W., & Shen, D. (2017) · Medical Image Analysis

Dementia and Cognitive Impairment ResearchArtificial Intelligence in Healthcare

Cited by 224

Mapping Region-Specific Longitudinal Cortical Surface Expansion from Birth to 2 Years of Age

Li, G., Nie, J., Wang, L., Shi, F., Lin, W., Gilmore, J. H., & Shen, D. (2013) · Cerebral Cortex

Fetal and Pediatric Neurological DisordersAdvanced Neuroimaging Techniques and Applications

Cited by 220