World's Best Scientists 2026 revealed!

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Computer Science

D-Index
38
Citations
5607
World Ranking
10314
National Ranking
4324

Overview

Yuankai Huo is affiliated with Vanderbilt University in the United States. Their research spans primarily the fields of Medicine and Computer Science, with a focus on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, and Artificial Intelligence. These areas underpin their contributions to biomedical imaging and computational methods in medical contexts.

The scientist's main topics of work include:

  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Medical Image Segmentation Techniques
  • Advanced Neural Network Applications
  • Cell Image Analysis Techniques
  • Advanced Neuroimaging Techniques and Applications
  • Advanced MRI Techniques and Applications

Some of the frequent publication venues where Yuankai Huo has contributed are:

  • arXiv (Cornell University)
  • Journal of Medical Imaging
  • Lecture Notes in Computer Science
  • Electronic Imaging
  • Medical Image Analysis

Yuankai Huo's recent published papers include:

  • "Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking," 2021, Medical Image Analysis
  • "Deep multimodal fusion of image and non-image data in disease diagnosis and prognosis: a review," 2023, Progress in Biomedical Engineering
  • "3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation," 2022, arXiv (Cornell University)
  • "Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging," 2023, arXiv (Cornell University)
  • "Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results," 2020, NeuroImage

Collaborations are a significant part of Yuankai Huo's work. Frequent co-authors include Bennett A. Landman, Ruining Deng, Shunxing Bao, Tianyuan Yao, and Yucheng Tang.

Yuankai Huo has contributed to book publications under the Springer Science+Business Media banner, with titles such as:

  • "Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops," 2023
  • "Multiscale Multimodal Medical Imaging," 2022
  • "Medical Optical Imaging and Virtual Microscopy Image Analysis," 2022

Best Publications

  • SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

    Yuankai Huo;Zhoubing Xu;Hyeonsoo Moon;Shunxing Bao

  • 3D whole brain segmentation using spatially localized atlas network tiles

    Yuankai Huo;Zhoubing Xu;Yunxi Xiong;Katherine Aboud

  • Synthesized b0 for diffusion distortion correction (Synb0-DisCo).

    Kurt G. Schilling;Justin Blaber;Yuankai Huo;Allen Newton

  • Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking.

    Mengyang Zhao;Aadarsh Jha;Quan Liu;Bryan A. Millis

  • Adversarial synthesis learning enables segmentation without target modality ground truth

    Yuankai Huo;Zhoubing Xu;Shunxing Bao;Albert Assad

  • Consistent cortical reconstruction and multi-atlas brain segmentation.

    Yuankai Huo;Andrew J. Plassard;Aaron Carass;Susan M. Resnick

  • FEATURE EXTRACTION OF BRAIN MRI BY STATIONARY WAVELET TRANSFORM AND ITS APPLICATIONS

    Yudong Zhang;Shuihua Wang;Yuankai Huo;Lenan Wu

  • 3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation

    Unknown

  • An adaptive threshold for the Canny Operator of edge detection

    Yuan-Kai Huo;Gen Wei;Yu-Dong Zhang;Le-Nan Wu

  • VoxelEmbed: 3D Instance Segmentation and Tracking with Voxel Embedding based Deep Learning.

    Mengyang Zhao;Quan Liu;Aadarsh Jha;Ruining Deng

  • Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results

    Lipeng Ning;Lipeng Ning;Elisenda Bonet-Carne;Francesco Grussu;Farshid Sepehrband

  • AI applications in renal pathology.

    Yuankai Huo;Ruining Deng;Quan Liu;Agnes B. Fogo

  • Circle Representation for Medical Object Detection.

    Ethan H. Nguyen;Haichun Yang;Ruining Deng;Yuzhe Lu

  • High-resolution 3D abdominal segmentation with random patch network fusion

    Yucheng Tang;Riqiang Gao;Ho Hin Lee;Shizhong Han

  • Vascular burden and APOE ε4 are associated with white matter microstructural decline in cognitively normal older adults.

    Owen A. Williams;Yang An;Lori Beason-Held;Yuankai Huo

  • Fully Convolutional Neural Networks Improve Abdominal Organ Segmentation.

    Meg F. Bobo;Shunxing Bao;Yuankai Huo;Yuang Yao

  • Distanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection.

    Riqiang Gao;Yuankai Huo;Shunxing Bao;Yucheng Tang

  • Splenomegaly Segmentation on Multi-Modal MRI Using Deep Convolutional Networks

    Yuankai Huo;Zhoubing Xu;Shunxing Bao;Camilo Bermudez

  • Tractography Reproducibility Challenge With Empirical Data (TraCED): The 2017 ISMRM Diffusion Study Group Challenge

    Vishwesh Nath;Kurt G. Schilling;Prasanna Parvathaneni;Yuankai Huo

  • Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging.

    Nai-Ming Cheng;Jiawen Yao;Jinzheng Cai;Xianghua Ye

  • Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks

    Yuankai Huo;Zhoubing Xu;Shunxing Bao;Camilo Bermudez

  • Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images

    Zhoubing Xu;Yuankai Huo;Jin Hyeong Park;Bennett A. Landman

  • Multi-channel Diffusion Tensor Image Registration via Adaptive Chaotic PSO

    Yudong Zhang;Shuihua Wang;Lenan Wu;Yuankai Huo

Frequent Co-Authors

Bennett A. Landman
Bennett A. Landman Vanderbilt University
Susan M. Resnick
Susan M. Resnick National Institutes of Health
Agnes B. Fogo
Agnes B. Fogo Vanderbilt University Medical Center
Le Lu
Le Lu Alibaba Group (China)
Yudong Zhang
Yudong Zhang University of Leicester
Catherine Lebel
Catherine Lebel University of Calgary
Laurie E. Cutting
Laurie E. Cutting Vanderbilt University
Shuihua Wang
Shuihua Wang Xi’an Jiaotong-Liverpool University
Catie Chang
Catie Chang Vanderbilt University
Lenan Wu
Lenan Wu Southeast University

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