overview

Technological advances in magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) provide unprecedented opportunities for revealing the anatomical, pathological, and functional information of biological systems and improving our understanding of the biological processes. During the last two decades, MR hardware and sequence design have been significantly improved, which make MRI and MRSI faster and finer than they have ever been. However, dynamic imaging of 3D objects, a beating heart or a working brain, for examples, is still a big challenge.



The research in our group is to develop 3-D, real-time imaging capability to visualize biological events as they are happening, and advanced analysis techniques to extract the desired information from biological images automatically, accurately and consistently.

selected publications
Academic Articles58
  • Guo, B., Yang, M., & Xiuquan Ji, J. (2022). Efficient image-based soiling quantification using histograms of a checkered pattern. Solar Energy. 242, 392-396.
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  • Alic, L., Griffin, J. F., Eresen, A., Kornegay, J. N., & Ji, J. X. (2021). Using MRI to quantify skeletal muscle pathology in Duchenne muscular dystrophy: A systematic mapping review.. Muscle Nerve. 64(1), 8-22.
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  • Yang, M., Ji, J., & Guo, B. (2020). Soiling Quantification Using an Image-Based Method: Effects of Imaging Conditions. IEEE Journal of Photovoltaics. 10(6), 1780-1787.
  • Basavaraju, A., Du, J., Zhou, F., & Ji, J. (2020). A Machine Learning Approach to Road Surface Anomaly Assessment Using Smartphone Sensors. IEEE Sensors Journal. 20(5), 2635-2647.
  • Eresen, A., Alic, L., Birch, S. M., Friedeck, W., Griffin, J. F., Kornegay, J. N., & Ji, J. X. (2019). Texture as an imaging biomarker for disease severity in golden retriever muscular dystrophy.. Muscle Nerve. 59(3), 380-386.
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Chapters1
  • TSAO, J., JI, J. X., & LIANG, Z. (2005). INTERPOLATION TECHNIQUES IN MULTIMODALITY IMAGE REGISTRATION AND THEIR APPLICATION. Medical Imaging Systems Technology. 255-295. World Scientific Publishing Company.
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Conference Papers54
  • Jia, X., Wang, S., Liang, X., Balagopal, A., Nguyen, D., Yang, M., ... Jiang, S. (2019). Cone-Beam Computed Tomography (CBCT) Segmentation by Adversarial Learning Domain Adaptation. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2019, PT VI. 11769, 567-575.
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  • Eresen, A., Alic, L., Kornegay, J., & Ji, J. X. (2018). Assessment of disease severity in a Canine Model of Duchenne Muscular Dystrophy: Classification of Quantitative MRI.. Annu Int Conf IEEE Eng Med Biol Soc, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2018, 648-651.
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  • Dhulipala, P. V., Shi, C., Xie, G., Wang, H., & Ji, J. X. (2018). MARBLES - Metal Artifact Based Landmark Enhanced Susceptibility Weighted Imaging For Interventional Device Localization In MRI.. Annu Int Conf IEEE Eng Med Biol Soc, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2018, 2611-2614.
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  • Shahin, M., Ahmed, B., Ji, J. X., & Ballard, K. (2018). Anomaly Detection Approach for Pronunciation Verification of Disordered Speech Using Speech Attribute Features. Interspeech 2018, Interspeech 2018. 2018-September, 1671-1675.
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  • Shahin, M., Ji, J. X., & Ahmed, B. (2018). One-Class SVMs Based Pronunciation Verification Approach. 2018 24th International Conference on Pattern Recognition (ICPR), 2018 24th International Conference on Pattern Recognition (ICPR). 00, 2881-2886.
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chaired theses and dissertations
Email
jimji@tamu.edu
First Name
Jim
Last Name
Ji
mailing address
Texas A&M University; Qatar Campus; 4251 TAMUQ
College Station, TX 77843-3128
USA