World's Best Scientists 2026 revealed!
Xiang Sean Zhou

Xiang Sean Zhou

D-Index & Metrics

Computer Science

D-Index
50
Citations
9935
World Ranking
5626
National Ranking
261

Overview

Xiang Sean Zhou is affiliated with Siemens in Germany and has contributed extensively to the fields of medicine and computer science. Their research mainly intersects radiology, nuclear medicine, imaging, and computer vision, with a focus on the application of artificial intelligence and machine learning in medical imaging.

Their recent publications cover a range of topics, including medical image segmentation, cancer detection, and radiotherapy planning. Key papers include:

  • Learning Hierarchical Attention for Weakly-Supervised Chest X-Ray Abnormality Localization and Diagnosis, 2020, IEEE Transactions on Medical Imaging
  • Deep learning empowered volume delineation of whole-body organs-at-risk for accelerated radiotherapy, 2022, Nature Communications
  • uRP: An integrated research platform for one-stop analysis of medical images, 2023, Frontiers in Radiology
  • Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches, 2023, Seminars in Cancer Biology
  • Data-driven risk stratification and precision management of pulmonary nodules detected on chest computed tomography, 2024, Nature Medicine

Xiang Sean Zhou frequently collaborates with several researchers, including:

  • Dinggang Shen
  • Yiqiang Zhan
  • Feng Shi
  • Jiaojiao Wu
  • Zhong Xue

The scientist's work has been published in various venues, with multiple contributions to:

  • Nature Communications
  • IEEE Transactions on Medical Imaging
  • arXiv (Cornell University)
  • Complementary Therapies in Medicine
  • Frontiers in Radiology

Their main fields of study include:

  • Medicine
  • Computer Science

Xiang Sean Zhou's subfields of study comprise:

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

The primary topics of their research work focus on:

  • Radiomics and Machine Learning in Medical Imaging
  • Medical Imaging Techniques and Applications
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Advanced X-ray and CT Imaging
  • Medical Image Segmentation Techniques
  • Lung Cancer Diagnosis and Treatment

Best Publications

  • Relevance feedback in image retrieval: A comprehensive review

    Xiang Sean Zhou;Thomas S. Huang

  • One-class SVM for learning in image retrieval

    Yunqiang Chen;Xiang Sean Zhou;T.S. Huang

  • Total variation models for variable lighting face recognition

    T. Chen;Wotao Yin;Xiang Sean Zhou;D. Comaniciu

  • Small sample learning during multimedia retrieval using BiasMap

    Xiang Sean Zhou;T.S. Huang

  • Feature selection using principal feature analysis

    Yijuan Lu;Ira Cohen;Xiang Sean Zhou;Qi Tian

  • Towards robust and effective shape prior modeling: sparse shape composition

    Dimitris N. Metaxas;Shaoting Zhang

  • Unifying keywords and visual contents in image retrieval

    Xiang Sean Zhou;T.S. Huang

  • Multi-Instance Deep Learning: Discover Discriminative Local Anatomies for Bodypart Recognition

    Zhennan Yan;Yiqiang Zhan;Zhigang Peng;Shu Liao

  • CBIR: from low-level features to high-level semantics

    Xiang Sean Zhou;Thomas S. Huang

  • Edge-based structural features for content-based image retrieval

    Xiang Sean Zhou;Thomas S. Huang

  • Database-guided segmentation of anatomical structures with complex appearance

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

  • Image based regression using boosting method

    Shaohua Kevin Zhou;B. Georgescu;Xiang Sean Zhou;D. Comaniciu

  • System and Method for Detecting and Matching Anatomical Structures Using Appearance and Shape

    Xiang Sean Zhou;Bogdan Georgescu;Dorin Comaniciu;R. Bharat Rao

  • An information fusion framework for robust shape tracking

    Xiang Sean Zhou;A. Gupta;D. Comaniciu

  • Comparing discriminating transformations and SVM for learning during multimedia retrieval

    Xiang Sean Zhou;Thomas S. Huang

  • System and method for performing probabilistic classification and decision support using multidimensional medical image databases

    Xiang Sean Zhou;Dorin Comaniciu;Alok Gupta;Visvanathan Ramesh

  • Robust real-time myocardial border tracking for echocardiography: an information fusion approach

    D. Comaniciu;X.S. Zhou;S. Krishnan

  • Systems and methods for automated diagnosis and decision support for heart related diseases and conditions

    Sriram Krishnan;Alok Gupta;R. Bharat Rao;Dorin Comaniciu

  • Image retrieval with relevance feedback: from heuristic weight adjustment to optimal learning methods

    T.S. Huang;Xiang Sean Zhou

  • Systems and methods providing automated decision support for medical imaging

    Sriram Krishnan;Dorin Comaniciu;Xiang Sean Zhou;Michael G. Cannon

Frequent Co-Authors

Dorin Comaniciu
Dorin Comaniciu Siemens (United States)
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Arun Krishnan
Arun Krishnan Microsoft (United States)
Bogdan Georgescu
Bogdan Georgescu Princeton University
Yong Rui
Yong Rui Lenovo (China)
Feng Shi
Feng Shi United Imaging Intelligence (China)
Dimitris N. Metaxas
Dimitris N. Metaxas Rutgers, The State University of New Jersey
Ashutosh Garg
Ashutosh Garg Google (United States)
Shaoting Zhang
Shaoting Zhang University of Electronic Science and Technology of China
Wotao Yin
Wotao Yin Alibaba Group (China)

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