Yushkevich, Paul A.

User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability.

Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006) · NeuroImage

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 8,868

Multi-Atlas Segmentation with Joint Label Fusion

Wang, H., Suh, J. W., Das, S. R., Pluta, J. B., Craige, C., & Yushkevich, P. A. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 796

The optimal template effect in hippocampus studies of diseased populations

Avants, B. B., Yushkevich, P., Pluta, J., Minkoff, D., Korczykowski, M., Detre, J., & Gee, J. C. (2010) · NeuroImage

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 640

Early stages of tau pathology and its associations with functional connectivity, atrophy and memory

Berron, D., Vogel, J. W., Insel, P. S., Pereira, J. B., Xie, L., Wisse, L. E. M., Yushkevich, P. A., Palmqvist, S., Mattsson-Carlgren, N., Stomrud, E., et al. (2021) · Brain

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 240

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

Wang, H., & Yushkevich, P. A. (2013) · Frontiers in Neuroinformatics

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 218

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

Davatzikos, C., Rathore, S., Bakas, S., Pati, S., Bergman, M., Kalarot, R., Sridharan, P., Gastounioti, A., Jahani, N., Cohen, E., et al. (2018) · Journal of Medical Imaging

Radiomics and Machine Learning in Medical ImagingMRI in cancer diagnosis

Cited by 204

A learning-based wrapper method to correct systematic errors in automatic image segmentation: Consistently improved performance in hippocampus, cortex and brain segmentation

Wang, H., Das, S. R., Suh, J. W., Altinay, M., Pluta, J., Craige, C., Avants, B., & Yushkevich, P. A. (2011) · NeuroImage

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 177

User-Guided Segmentation of Multi-modality Medical Imaging Datasets with ITK-SNAP

Yushkevich, P. A., Pashchinskiy, A., Oguz, I., Mohan, S., Schmitt, J. E., Stein, J. M., Zukić, D., Vicory, J., McCormick, M., Yushkevich, N., et al. (2019) · Neuroinformatics

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 175

In vivo Analysis of Hippocampal Subfield Atrophy in Mild Cognitive Impairment via Semi-Automatic Segmentation of T2-Weighted MRI

Pluta, J., Yushkevich, P., Das, S., & Wolk, D. (2012) · Journal of Alzheimer's Disease

Dementia and Cognitive Impairment ResearchMedical Image Segmentation Techniques

Cited by 107

The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview

Pati, S., Singh, A., Rathore, S., Gastounioti, A., Bergman, M., Ngo, P., Ha, S. M., Bounias, D., Minock, J., Murphy, G., et al. (2020) · Lecture Notes in Computer Science

Radiomics and Machine Learning in Medical ImagingMedical Image Segmentation Techniques

Cited by 94

Overview of ADNI MRI

Jack, C. R., Arani, A., Borowski, B. J., Cash, D. M., Crawford, K., Das, S. R., DeCarli, C., Fletcher, E., Fox, N. C., Gunter, J. L., et al. (2024) · Alzheimer's & Dementia

Dementia and Cognitive Impairment ResearchAdvanced MRI Techniques and Applications

Cited by 82

Suspected non-AD pathology in mild cognitive impairment

Wisse, L. E. M., Butala, N., Das, S. R., Davatzikos, C., Dickerson, B. C., Vaishnavi, S. N., Yushkevich, P. A., & Wolk, D. A. (2015) · Neurobiology of Aging

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 78

Assessing atrophy measurement techniques in dementia: results from the MIRIAD atrophy challenge

Cash, D. M., Frost, C., Iheme, L. O., Ünay, D., Kandemir, M., Fripp, J., Salvado, O., Bourgeat, P., Reuter, M., Fischl, B., et al. (2015) · NeuroImage

Dementia and Cognitive Impairment ResearchMedical Image Segmentation Techniques

Cited by 72

Staging tau pathology with tau PET in Alzheimer’s disease: a longitudinal study

Chen, S.-D., Lu, J.-Y., Li, H.-Q., Yang, Y.-X., Jiang, J.-H., Cui, M., Zuo, C.-T., Tan, L., Dong, Q., Yu, J.-T., et al. (2021) · Translational Psychiatry

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 71

White matter abnormalities and cognition in aging and Alzheimer disease

Peter, C., Sathe, A., Shashikumar, N., Pechman, K. R., Workmeister, A. W., Jackson, T. B., Huo, Y., Mukherjee, S., Mez, J., Dumitrescu, L. C., et al. (2025) · JAMA Neurology

Dementia and Cognitive Impairment ResearchAdvanced Neuroimaging Techniques and Applications

Cited by 59

Neural and behavioral correlates of episodic memory are associated with temporal discounting in older adults

Lempert, K. M., Mechanic-Hamilton, D. J., Xie, L., Wisse, L. E. M., de Flores, R., Wang, J., Das, S. R., Yushkevich, P. A., Wolk, D. A., & Kable, J. W. (2020) · Neuropsychologia

Memory Processes and InfluencesDementia and Cognitive Impairment Research

Cited by 38

A tract-specific approach to assessing white matter in preterm infants

Pecheva, D., Yushkevich, P., Batalle, D., Hughes, E., Aljabar, P., Wurie, J., Hajnal, J. V., Edwards, A. D., Alexander, D. C., Counsell, S. J., et al. (2017) · NeuroImage

Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies

Cited by 33

Automated Segmentation and Geometrical Modeling of the Tricuspid Aortic Valve in 3D Echocardiographic Images

Pouch, A. M., Wang, H., Takabe, M., Jackson, B. M., Sehgal, C. M., Gorman, J. H., Gorman, R. C., & Yushkevich, P. A. (2013) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesCardiac Valve Diseases and Treatments

Cited by 25

Towards cascading genetic risk in Alzheimer’s disease

Altmann, A., Aksman, L. M., Oxtoby, N. P., Young, A. L., ADNI, Weiner, M., Aisen, P., Petersen, R., Weiner, M., Aisen, P., et al. (2024) · Brain

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 18

Deep learning to quantify the pace of brain aging in relation to neurocognitive changes

Yin, C., Imms, P., Chowdhury, N. F., Chaudhari, N. N., Ping, H., Wang, H., Bogdan, P., Irimia, A., Initiative, T. A. D. N., Weiner, M., et al. (2025) · Proceedings of the National Academy of Sciences

Dementia and Cognitive Impairment ResearchAdvanced MRI Techniques and Applications

Cited by 18

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data

Jo, T., Kim, J., Bice, P., Huynh, K., Wang, T., Arnold, M., Meikle, P. J., Giles, C., Kaddurah-Daouk, R., Saykin, A. J., et al. (2023) · eBioMedicine

Dementia and Cognitive Impairment ResearchMetabolomics and Mass Spectrometry Studies

Cited by 15

Combining Deep Learning and Multi-atlas Label Fusion for Automated Placenta Segmentation from 3DUS

Oguz, B. U., Wang, J., Yushkevich, N., Pouch, A., Gee, J., Yushkevich, P. A., Schwartz, N., & Oguz, I. (2018) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 13

Minimally interactive placenta segmentation from three-dimensional ultrasound images

Oguz, I., Yushkevich, N., Pouch, A. M., Oguz, B. U., Wang, J., Parameshwaran, S., Gee, J. C., Yushkevich, P. A., & Schwartz, N. (2020) · Journal of Medical Imaging

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 13

Fully Automated Placental Volume Quantification From 3D Ultrasound for Prediction of Small‐for‐Gestational‐Age Infants

Schwartz, N., Oguz, I., Wang, J., Pouch, A., Yushkevich, N., Parameshwaran, S., Gee, J., Yushkevich, P., & Oguz, B. (2022) · Journal of Ultrasound in Medicine

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 11