World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
13274
World Ranking
3262
National Ranking
1582

Overview

Bogdan Georgescu is affiliated with Princeton University in the United States and has contributed extensively to the intersections of medicine and computer science, focusing particularly on medical imaging and artificial intelligence applications within healthcare.

Their recent publications cover significant topics in medical image analysis, lung cancer diagnosis, and COVID-19 diagnosis using AI. Noteworthy papers include:

  • The Liver Tumor Segmentation Benchmark (LiTS), 2022, Medical Image Analysis
  • Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT, 2020, Radiology Artificial Intelligence
  • Business Model Innovation Through the Use of Digital Technologies: Managing Risks and Creating Sustainability, 2020, Amfiteatru Economic
  • No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting With Adversarial Attacks, 2020, IEEE Transactions on Medical Imaging
  • Contrastive self-supervised learning from 100 million medical images with optional supervision, 2022, Journal of Medical Imaging

The primary areas of study for Bogdan Georgescu include Medicine, with a strong focus on Radiology, Nuclear Medicine and Imaging, complemented by Computer Science. Their work spans several subfields such as:

  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Pulmonary and Respiratory Medicine
  • Computer Vision and Pattern Recognition
  • Neurology

Their main research topics are diverse and specialized, including:

  • Radiomics and Machine Learning in Medical Imaging
  • COVID-19 diagnosis using AI
  • Lung Cancer Diagnosis and Treatment
  • AI in cancer detection
  • Advanced Neural Network Applications
  • Medical Imaging and Analysis
  • Anomaly Detection Techniques and Applications

Bogdan collaborates frequently with a core group of co-authors, reflecting interdisciplinary teamwork and consistent research partnerships. Frequent collaborators include:

  • Saša Grbić
  • Dorin Comaniciu
  • Florin C. Ghesu
  • Awais Mansoor
  • Thomas J. Re

The scientist has published repeatedly in several academic venues, underscoring a focused engagement with specific scholarly communities. The most common publication venues are:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • Radiology Artificial Intelligence
  • Scientific Reports
  • Amfiteatru Economic

Best Publications

  • Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features

    Yefeng Zheng;A. Barbu;B. Georgescu;M. Scheuering

  • Edge detection with embedded confidence

    P. Meer;B. Georgescu

  • Synergism in low level vision

    C.M. Christoudias;B. Georgescu;P. Meer

  • A machine-learning approach for computation of fractional flow reserve from coronary computed tomography.

    Lucian Itu;Saikiran Rapaka;Tiziano Passerini;Bogdan Georgescu

  • Combo loss: Handling input and output imbalance in multi-organ segmentation

    Saeid Asgari Taghanaki;Saeid Asgari Taghanaki;Yefeng Zheng;S. Kevin Zhou;Bogdan Georgescu

  • Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

    Florin-Cristian Ghesu;Bogdan Georgescu;Yefeng Zheng;Sasa Grbic

  • Detection and Measurement of Fetal Anatomies from Ultrasound Images using a Constrained Probabilistic Boosting Tree

    G. Carneiro;B. Georgescu;S. Good;D. Comaniciu

  • Patient-Specific Modeling and Quantification of the Aortic and Mitral Valves From 4-D Cardiac CT and TEE

    Razvan Ioan Ionasec;Ingmar Voigt;Bogdan Georgescu;Yang Wang

  • Fast Automatic Heart Chamber Segmentation from 3D CT Data Using Marginal Space Learning and Steerable Features

    Yefeng Zheng;A. Barbu;B. Georgescu;M. Scheuering

  • 3D Deep Learning for Efficient and Robust Landmark Detection in Volumetric Data

    Yefeng Zheng;David Liu;Bogdan Georgescu;Hien Nguyen

  • Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

    Dong Yang;Daguang Xu;S. Kevin Zhou;Bogdan Georgescu

  • Hierarchical, learning-based automatic liver segmentation

    Haibin Ling;S.K. Zhou;Yefeng Zheng;B. Georgescu

  • Complete valvular heart apparatus model from 4D cardiac CT

    Sasa Grbic;Sasa Grbic;Razvan Ioan Ionasec;Dime Vitanovski;Ingmar Voigt

  • Method and system for anatomical object detection using marginal space deep neural networks

    Bogdan Georgescu;Yefeng Zheng;Hien Nguyen;Vivek Kumar Singh

  • 3D ultrasound tracking of the left ventricle using one-step forward prediction and data fusion of collaborative trackers

    Lin Yang;B. Georgescu;Yefeng Zheng;P. Meer

  • Database-guided segmentation of anatomical structures with complex appearance

    B. Georgescu;X.S. Zhou;D. Comaniciu;A. Gupta

  • Automatic Liver Segmentation Using Adversarial Image-to-Image Network

    Dong Yang;Daguang Xu;Shaohua Kevin Zhou;Bogdan Georgescu

  • Learning to Recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks

    Sebastian Gündel;Sasa Grbic;Bogdan Georgescu;Siqi Liu

  • An Artificial Agent for Anatomical Landmark Detection in Medical Images

    Florin C. Ghesu;Bogdan Georgescu;Tommaso Mansi;Dominik Neumann

  • Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing

    Florin C. Ghesu;Edward Krubasik;Bogdan Georgescu;Vivek Singh

  • Learning to recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks

    Sebastian Guendel;Sasa Grbic;Bogdan Georgescu;Kevin Zhou

  • Four-Chamber Heart Modeling and Automatic Segmentation for 3D Cardiac CT Volumes

    Yefeng Zheng;Bogdan Georgescu;Adrian Barbu;Michael Scheuering

Frequent Co-Authors

Dorin Comaniciu
Dorin Comaniciu Siemens (United States)
Yefeng Zheng
Yefeng Zheng Tencent (China)
Joachim Hornegger
Joachim Hornegger University of Erlangen-Nuremberg
Nassir Navab
Nassir Navab Technical University of Munich
Xiang Sean Zhou
Xiang Sean Zhou Siemens (Germany)
Peter Meer
Peter Meer Rutgers, The State University of New Jersey
S. Kevin Zhou
S. Kevin Zhou University of Science and Technology of China
Benjamin Meder
Benjamin Meder Heidelberg University
Gustavo Carneiro
Gustavo Carneiro University of Surrey
Daguang Xu
Daguang Xu Nvidia (United Kingdom)

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