3D Face Modeling | 3D Human Reconstruction | 3D Object Detection | 3D Shape Correspondence | 3D Shape Generation | 3D Shape Reconstruction | Activity Recognition | Application | Biometrics | Body Matching | Camera Calibration | Camera+LiDAR+Radar | Data Imputation | Database | DeepFake | Depth Completion | Depth Prediction | Domain Adaptation | Expression Recognition | Face Alignment | Face Antispoofing | Face Deidentification | Face Recognition | Face Reconstruction | Face Relighting | Face Synthesis | Forecasting | Gait Recognition | Generic Object 3D Reconstruction | Image Alignment | Image Manipulation | Image Segmentation | Low-level Vision | Medical Imaging | Motion Compensation | Multi-modality | Multimedia Retrieval | Object Detection | Pedestrian Detection | Person Re-identification | Plant Vision | Semantic Segmentation | Surveillance | Tracking | Typing Behavior | Vision-language

Medical Imaging

  1. summary image

    Image Segmentation of Mesenchymal Stem Cells in Diverse Culturing Conditions

    Muhammad Jamal Afridi, Chun Liu, Christina Chan, Seungik Baek, Xiaoming Liu

    Researchers in the areas of regenerative medicine and tissue engineering have an enormous interest in understanding the relationship of different sets of culturing conditions and applied mechanical stimuli on the behavior of Mesenchymal Stem Cells (MSCs). However, it remains a challenge to design a general tool to perform automatic cell ...

    Continue reading

    Keywords: Medical Imaging, Image Segmentation, Application, Semantic Segmentation

2021

  • TURNIP: TIME-SERIES U-NET WITH RECURRENCE FOR NIR IMAGING PPG
    Armand Comas, Tim K. Marks, Hassan Mansour, Suhas Lohit, Yechi Ma, Xiaoming Liu
    IEEE International Conference on Image Processing (ICIP 2021), Anchorage, AK, Aug. 2021
    Bibtex | PDF
  • @inproceedings{ turnip-time-series-u-net-with-recurrence-for-nir-imaging-ppg,
      author = { Armand Comas and Tim K. Marks and Hassan Mansour and Suhas Lohit and Yechi Ma and Xiaoming Liu },
      title = { TURNIP: TIME-SERIES U-NET WITH RECURRENCE FOR NIR IMAGING PPG },
      booktitle = { IEEE International Conference on Image Processing },
      address = { Anchorage, AK },
      month = { August },
      year = { 2021 },
    }

2017

  • Intelligent and Automatic in vivo Detection and Quantification of Transplanted Cells in MRI
    Muhammad Jamal Afridi, Arun Ross, Xiaoming Liu, Margaret Bennewitz, Dorela Shuboni, Erik M Shapiro
    Magnetic Resonance in Medicine, Vol. 78, No. 5, pp.1991-2002, , Jan. 2017
    Bibtex | PDF | Supplemental
  • @article{ intelligent-and-automatic-in-vivo-detection-and-quantification-of-transplanted-cells-in-mri,
      author = { Muhammad Jamal Afridi and Arun Ross and Xiaoming Liu and Margaret Bennewitz and Dorela Shuboni and Erik M Shapiro },
      title = { Intelligent and Automatic in vivo Detection and Quantification of Transplanted Cells in MRI },
      journal = { Magnetic Resonance in Medicine },
      volume = { 78 },
      number = { 5 },
      month = { January },
      year = { 2017 },
      pages = { 1991--2002 },
    }

2015

  • Automatic in vivo Cell Detection in MRI
    Muhammad Jamal Afridi, Xiaoming Liu, Erik M Shapiro, Arun Ross
    Proc. 18th Medical Image Computing and Computer Assisted Intervention (MICCAI 2015), Munich, Germany, Oct. 2015
    Bibtex | PDF
  • @inproceedings{ automatic-in-vivo-cell-detection-in-mri,
      author = { Muhammad Jamal Afridi and Xiaoming Liu and Erik M Shapiro and Arun Ross },
      title = { Automatic in vivo Cell Detection in MRI },
      booktitle = { Proc. 18th Medical Image Computing and Computer Assisted Intervention },
      address = { Munich, Germany },
      month = { October },
      year = { 2015 },
    }

2014

  • Image Segmentation of Mesenchymal Stem Cells in Diverse Culturing Conditions
    Muhammad Jamal Afridi, Chun Liu, Christina Chan, Seungik Baek, Xiaoming Liu
    Proc. IEEE Winter Conference on Application of Computer Vision (WACV 2014), Steamboat Springs, USA, Mar. 2014
    Bibtex | PDF | Project Webpage
  • @inproceedings{ image-segmentation-of-mesenchymal-stem-cells-in-diverse-culturing-conditions,
      author = { Muhammad Jamal Afridi and Chun Liu and Christina Chan and Seungik Baek and Xiaoming Liu },
      title = { Image Segmentation of Mesenchymal Stem Cells in Diverse Culturing Conditions },
      booktitle = { Proc. IEEE Winter Conference on Application of Computer Vision },
      address = { Steamboat Springs, USA },
      month = { March },
      year = { 2014 },
    }

2013

  • Parsing Radiographs by Integrating Landmark Set Detection and Multi-object Active Appearance Models
    Albert Montillo, Qi Song, Xiaoming Liu, James Miller
    Proc. SPIE Medical Imaging on Image Processing, Florida, USA, Feb. 2013 (Oral presentation)
    Bibtex | PDF
  • @inproceedings{ parsing-radiographs-by-integrating-landmark-set-detection-and-multi-object-active-appearance-models,
      author = { Albert Montillo and Qi Song and Xiaoming Liu and James Miller },
      title = { Parsing Radiographs by Integrating Landmark Set Detection and Multi-object Active Appearance Models },
      booktitle = { Proc. SPIE Medical Imaging on Image Processing },
      address = { Florida, USA },
      month = { February },
      year = { 2013 },
    }

2012

  • Learning-based Scan Plane Identification From Fetal Head Ultrasound Images
    Xiaoming Liu, Pavan Annangi, Mithun Gupta, Bing Yu, Dirk Padfield, Jyotirmoy Banerjee, Kajoli Krishnan
    Proc. SPIE Medical Imaging on Ultrasonic Imaging, Tomography, and Therapy, California, USA, Feb. 2012
    Bibtex | PDF
  • @inproceedings{ learning-based-scan-plane-identification-from-fetal-head-ultrasound-images,
      author = { Xiaoming Liu and Pavan Annangi and Mithun Gupta and Bing Yu and Dirk Padfield and Jyotirmoy Banerjee and Kajoli Krishnan },
      title = { Learning-based Scan Plane Identification From Fetal Head Ultrasound Images },
      booktitle = { Proc. SPIE Medical Imaging on Ultrasonic Imaging, Tomography, and Therapy },
      address = { California, USA },
      month = { February },
      year = { 2012 },
    }