World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
109
Citations
56238
World Ranking
240
National Ranking
133

Medicine

D-Index
131
Citations
74259
World Ranking
2370
National Ranking
1336

Research.com Recognitions

  • 2016 - Fellow of the Indian National Academy of Engineering (INAE)
  • 2014 - IEEE Fellow For contributions to automatic analysis and interpretation of biomedical multi-dimensional data

Overview

Christos Davatzikos is affiliated with the University of Pennsylvania in the United States. Their research primarily focuses on advancing the field of Medicine, with significant contributions in Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Psychiatry and Mental Health, Genetics, and Molecular Biology.

Their work explores various topics including:

  • Radiomics and Machine Learning in Medical Imaging
  • Functional Brain Connectivity Studies
  • Dementia and Cognitive Impairment Research
  • Advanced Neuroimaging Techniques and Applications
  • Glioma Diagnosis and Treatment
  • Alzheimer's Disease Research and Treatments
  • Advanced MRI Techniques and Applications

Recent notable publications by Christos Davatzikos include:

  • "The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping" (2020, Radiology)
  • "Image segmentations produced by BAMF under the AIMI Annotations initiative" (2024, arXiv (Cornell University))
  • "MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14,468 individuals worldwide" (2020, Brain)
  • "Federated learning enables big data for rare cancer boundary detection" (2022, Nature Communications)
  • "QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data" (2021, Nature Methods)

Their frequent co-authors include Güray Erus, Haochang Shou, Anahita Fathi Kazerooni, Susan M. Resnick, and Russell T. Shinohara, indicating collaboration across multiple projects and studies.

Christos Davatzikos has published extensively in several venues, with the most frequent being:

  • Alzheimer's & Dementia
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Neuro-Oncology
  • arXiv (Cornell University)
  • Biological Psychiatry

Recognitions awarded to Christos Davatzikos include becoming a Fellow of the Indian National Academy of Engineering (INAE) in 2016. Additionally, they were named an IEEE Fellow in 2014 for contributions to automatic analysis and interpretation of biomedical multi-dimensional data.

Best Publications

  • The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

    Alex Zwanenburg;Alex Zwanenburg;Martin Vallières;Mahmoud A. Abdalah;Hugo J. W. L. Aerts;Hugo J. W. L. Aerts

  • Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

    Spyridon Bakas;Hamed Akbari;Aristeidis Sotiras;Michel Bilello

  • Deformable Medical Image Registration: A Survey

    A. Sotiras;C. Davatzikos;N. Paragios

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

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain

    Susan M. Resnick;Dzung L. Pham;Michael A. Kraut;Alan B. Zonderman

  • A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises

    S. Kevin Zhou;Hayit Greenspan;Christos Davatzikos;James S. Duncan

  • HAMMER: hierarchical attribute matching mechanism for elastic registration

    Dinggang Shen;C. Davatzikos

  • Effect of Intensive vs Standard Blood Pressure Control on Probable Dementia: A Randomized Clinical Trial.

    Jeff D. Williamson;Nicholas M. Pajewski;Alexander P. Auchus

  • Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

    Rastko Ciric;Daniel H. Wolf;Jonathan D. Power;David R. Roalf

  • Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme.

    Evangelia I. Zacharaki;Evangelia I. Zacharaki;Sumei Wang;Sanjeev Chawla;Dong Soo Yoo;Dong Soo Yoo

  • Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects.

    Hans W. Müller-Gärtner;Jonathan M. Links;Jerry L. Prince;Robert 'Nick' Bryan

  • Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.

    Geert J. S. Litjens;Robert Toth;Wendy J. M. van de Ven;Caroline Hoeks

  • Imaging cortical association tracts in the human brain using diffusion-tensor-based axonal tracking.

    Susumu Mori;Walter E. Kaufmann;Christos Davatzikos;Bram Stieltjes

  • Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: Results from ADNI

    Chandan Misra;Yong Fan;Christos Davatzikos

  • Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification.

    Christos Davatzikos;Priyanka Bhatt;Leslie M. Shaw;Kayhan N. Batmanghelich

  • One-year Age Changes in MRI Brain Volumes in Older Adults

    Susan M. Resnick;Alberto F. Goldszal;Christos Davatzikos;Stephanie Golski

  • A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages

    Saima Rathore;Mohamad Habes;Muhammad Aksam Iftikhar;Amanda Shacklett

  • Longitudinal pattern of regional brain volume change differentiates normal aging from MCI

    I. Driscoll;C. Davatzikos;Y. An;X. Wu

  • Effects of intensive glucose lowering on brain structure and function in people with type 2 diabetes (ACCORD MIND): A randomised open-label substudy

    Lenore J. Launer;Michael E. Miller;Jeff D. Williamson;Ron M. Lazar

  • Neuroimaging of the Philadelphia neurodevelopmental cohort.

    Theodore D. Satterthwaite;Mark A. Elliott;Kosha Ruparel;James Loughead

  • Classifying spatial patterns of brain activity with machine learning methods: Application to lie detection

    Christos Davatzikos;Kosha Ruparel;Yong Fan;Dinggang Shen

Frequent Co-Authors

Susan M. Resnick
Susan M. Resnick National Institutes of Health
Dinggang Shen
Dinggang Shen ShanghaiTech University
Theodore D. Satterthwaite
Theodore D. Satterthwaite University of Pennsylvania
Ruben C. Gur
Ruben C. Gur University of Pennsylvania
Raquel E. Gur
Raquel E. Gur University of Pennsylvania
Russell T. Shinohara
Russell T. Shinohara University of Pennsylvania
Yong Fan
Yong Fan University of Pennsylvania
Daniel H. Wolf
Daniel H. Wolf University of Pennsylvania
Luigi Ferrucci
Luigi Ferrucci National Institutes of Health
David R. Roalf
David R. Roalf University of Pennsylvania

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