Research & Dev. Intrest: Healthcare IT Information Management, Medical Image Computing, Information Retrieval and Computer Vision.
Short Bio
I am currently with Microsoft Health Solutions Group, working in the domain of Healthcare IT for Microsoft Amalga Unified Intelligence System.
I graduated from the Dept. of Electrical and Computer Engineering at Virginia Tech University. I worked with Prof. Shih-Chung Ben Lo in the research area of medical image computing, and computer-aided detection and diagnosis .
During my graduate study, I also spent one year (from 2008 to 2009) as a research intern with Dr. Xiang Sean Zhou and Dr. Marcos Salganicoff at CAD R&D, Siemens Healthcare USA. We worked on several exciting medical image computing projects for real CAD product and prototype systems.I got my M.S. degree in 2006 and B.E. degree in 2003, both from the Dept. of Biomedical Engineering of Southeast University, China.
Research & Dev. Intrest: Healthcare IT Information Management, Medical Image Computing, Information Retrieval and Computer Vision.
Short Bio
I got my M.S. degree in 2006 and B.E. degree in 2003, both from the Dept. of Biomedical Engineering of Southeast University, China.
Education
2003, B.S., Biomedical Engineering and Computer Engineering (minor), Southeast University, China.
2006, M.S., Biomedical Engineering, Southeast University, China.
2009, M.S. (original Ph.D track), Electrical and Computer Engineering, Virginia Tech University
Patent
1. Systems and Methods for Robust Learning based Annotation of Medical Radiographs (pending
U.S. Patent 12/787,916, with Siemens Medical Solutions USA, Inc,
2010
) (link)
Project
Medical Image Retrieval and Annotation
- Mammographic mass characterization and retrieval (ISIS, Georgetown Univ., funded by NIH, demo presented at CAD workshop at SPIE07-09)(PPT)
- Content-based medical image retrieval
- Robust Learning based Annotation of Medical Radiographs (CAD R&D, Siemens Healthcare, 2009 Spring): Our algorithm has been integrated with Siemens image workstation product enabling content-sensitive hanging-protocols and auto-invocation of computer aided detection algorithms.
Medical Image Analysis
- Joint segmentation and spiculation detection for mammographic mass
- Mouse fat pad and glandular tissue segmentation & visualization for MRI Images (PPT)
Computer-aided Detection and Diagnosis (ISIS & Lombardi Cancer Center, Georgetown Univ.)
- Lung Nodule Detection System
- Mammographic Mass Viewer
- 3D Image Search Engine for Interactive Diffuse Parenchymal Lung Disease Quantification (CAD R&D, Siemens Healthcare, 2008 Summer)
- Ground Glass Nodule Detection and Segmentation in Lung CT Images (CAD R&D, Siemens Healthcare, 2009 Spring)
Natural Language Processing (Microsoft Research, Asia, 2005 Spring & Summer)
All algorithms have been integrated into Text-To-Speech component for Microsoft Vista.
- English to Katakana automatic-transliteration based on decision tree. (PPT)
- Grapheme-to-Phoneme conversion of Japanese/Chinese polyphone words using stochastic-based rule list (Tech Report, last updated 2/22/2007)
Others
- Web based remote education system (Southeast Univ., 2003 Spring)
Course Project
1. Curvature scale space descriptor for medical image analysis (Computer Vision, 2006 Fall, Tech Report)
2. Multi-resolution learning paradigm for classification (Data Mining, 2007 Spring, Tech Report, Java & Matlab code)
3. Texton based object recognition and categorization (Statistical learning, 2007 Fall, PPT, Matlab code, [Shotton 07] )
Others
All the source code of the following demo are available upon request.
Matlab Code,
[Criminisi 05])
2. Level Set Segmentation Package (Matlab Code)
Some algorithms are extended on the algrithms provied by Dr. Li Chunming. This package includes Multi-phase level set, Local binary fit [Li 07], Geodesic aided CV, Mixture model based level set.
3. Steerable Filters for Feature Detection
(Matlab Code,
[Jacob 04])
4. OCR (Optical character recognition) (C# Code)
5. M-tree: An efficient access method for similarity search in metric spaces (C# code, [Hellerstein 95], [Ciaccia 97])
This is a C# version I implementd. For introduction see The M-Tree Project and Wikipedia
Publication List
Conference:
1. Yimo Tao, Shih-Chung Ben Lo, Matthew T. Freedman, and Jianhua Xuan, "A Preliminary Study of Content-based Mammographic Masses Retrieval", SPIE Medical Imging 2007.(
pdf)
2. Yimo Tao, Shih-Chung Ben Lo, Matthew T. Freedman, Erini Makariou, and Jianhua Xuan, "Automatic Categorization of Mammographic Masses Using BI-RADS as a Guidance", SPIE Medical Imging 2008. (pdf)
3. Yimo Tao, Jianhua Xuan, Matthew T. Freedman, Chepko Gloria, Peter G. Shields, and Yue Wang, "Imaging Biomarker Analysis of Rat Mammary Fat Pads and Glandular Tissues in MRI Images", ICPR 2008. (Oral presentation, pdf)
4. Yimo Tao, Xiang Sean Zhou, Jinbo Bi, Anna Jerebko, Matthias Wolf, Marcos Salganicoff, and Arun Krishnan, "An Adaptive, Knowledge-Driven Medical Image Search Engine for Interactive Diffuse Parenchymal Lung Disease Quantification", SPIE Medical Imaging 2009. (Oral presentation, pdf)
5. Yimo Tao, Le Lu, Dewan Maneesh, Albert. Y Chen, Jason Corso, Jianhua Xuan, Marcos Salganicoff, and Arun Krishnan, "Multi-level Ground Glass Nodule Detection and Segmentation in CT Lung Images", MICCAI 2009. (pdf)
6. Yimo Tao, Zhigang Peng, Bing Jian, Jianhua Xuan, Arun Krishnan, and Xiang Sean Zhou, "Robust Learning-based Annotation of Medical Radiographs", International Workshop on Medical Content-based Retrieval for Clinical Decision Support, in conjunction with MICCAI 2009. (Oral presentation, pdf)
7. Yimo Tao, Shih-Chung Ben Lo, Matthew T. Freedman, and Jianhua Xuan,
"
Joint Segmentation and Spiculation Detection for Ill-defined and Spiculated Mammographic Masses", SPIE Medical Imaging 2010, (Oral presentation,