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 Articles53
  • 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.
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  • 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.
  • Abbas, H. T., Alic, L., Erraguntla, M., Ji, J. X., Abdul-Ghani, M., Abbasi, Q. H., & Qaraqe, M. K. (2019). Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test. PLoS ONE. 14(12), e0219636-e0219636.
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  • Eresen, A., Hafsa, N. E., Alic, L., Birch, S. M., Griffin, J. F., Kornegay, J. N., & Ji, J. X. (2019). Muscle percentage index as a marker of disease severity in golden retriever muscular dystrophy. Muscle & Nerve. 60(5), 621-628.
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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: Analysis and Computational Methods. 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. ADVANCES IN NEURAL NETWORKS - ISNN 2014. 11769, 567-575.
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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. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. 2018-September, 1671-1675.
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  • Shahin, M., Ji, J. X., & Ahmed, B. (2018). One-Class SVMs Based Pronunciation Verification Approach. 16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL II, PROCEEDINGS. 00, 2881-2886.
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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. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 00, 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. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. 00, 2611-2614.
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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