Biomedical image reconstruction and analysis
Signal processing and machine learning techniques for imaging (e.g. PET, MRI), graph (e.g. brain network), and time-series (e.g., accelerometry, ECG) datasets; Multimodality information integration for image reconstruction, processing, and analysis
Applications to neurology: Tau and amyloid imaging and graph-based brain network analysis for Alzheimer’s disease; Super-resolution imaging using anatomical priors and deep learning; Machine learning for automatic sleep staging. Applications in oncology: Multimodal image segmentation for cancerous lesions using spectral methods and deep learning; Respiratory motion-compensated reconstruction of pulmonary images. Imaging modalities of interest: PET/CT, PET/MRI, CT, MRI, and optical methods.
Joyita Dutta received her B.Tech. (Honors) in Electronics and Electrical Communication Engineering from the Indian Institute of Technology Kharagpur, India, in 2004 and her M.S. and Ph.D. degrees in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 2006 and 2011 respectively. In 2011, she joined Harvard Medical School and Massachusetts General Hospital (MGH), Boston, MA, as a Research Fellow where she later became an Instructor. She joined the University of Massachusetts Lowell, Lowell, MA, as an Assistant Professor in the Department of Electrical and Computer Engineering in 2015. In 2019, she was promoted to the rank of Associate Professor with tenure. She also holds ranks of Instructor at Harvard Medical School and Assistant in Physics at MGH. Her research interests are signal processing, image analysis, and machine learning with an emphasis on multimodal information integration. In 2013, she received a Young Investigator Award from the Society of Nuclear Medicine and Molecular Imaging (SNMMI). She was also a recipient of the SNMMI Mitzi & William Blahd MD Pilot Research Grant (2013-2014), an American Lung Association Senior Research Training Fellowship (2013-2015), and an NIH K01 Mentored Research Scientist Development Award (2015-2020). In 2016, she received the Tracy Lynn Faber Memorial Award for the advancement of women in biomedical sciences from the SNMMI in recognition of her “outstanding contributions in multimodality and molecular image reconstruction and analysis." She also received the 2016 Bruce Hasegawa Young Investigator Medical Imaging Science Award “for contributions to image reconstruction and analysis for molecular and multimodality imaging in the areas of positron emission tomography (PET/CT and PET/MRI) and fluorescence tomography.”
Selected Awards and Honors
- Bruce Hasegawa Young Investigator Medical Imaging Science Award (2016)
- Tracy Lynn Faber Memorial Award (2016)
- NIH/NIA K01 Career Award (2015)
- American Lung Association Senior Research Training Fellowship (2013)
- Mitzi & William Blahd, MD, Pilot Research Grant (2013)
- SNMMI CaIC Young Investigator Award (2013)
- Academic Achievement Award (2010)
- Merit Scholarship from Women in Science and Engineering, USC (2010)
- Alfred E. Mann Innovation in Engineering Doctoral Fellowship (2009)
- American Society of Engineers of Indian origin (ASEI) Scholarship Award (2006)
- Song, T.A., Chowdhury, S.R., Yang, F., Dutta, J. (2020). PET image super-resolution using generative adversarial networks. Neural networks : the official journal of the International Neural Network Society, 125 83-91.
- Song, T.A., Chowdhury, S.R., Yang, F., Dutta, J. (2020). Super-Resolution PET Imaging Using Convolutional Neural Networks. IEEE transactions on computational imaging, 6 518-528.
- Song, T.A., Yang, F., Chowdhury, S.R., Kim, K., Johnson, K.A., El Fakhri, G., Li , Q., Dutta, J. (2019). PET Image Deblurring and Super-Resolution with an MR-Based Joint Entropy Prior. IEEE transactions on computational imaging, 5(4) 530-539.
- Song, T.A., Chowdhury, S., Yang, F., Jacobs, H., El Fakhri, G., Li , Q., Johnson, K., Dutta, J. (2019). Graph convolutional neural networks for Alzheimer's disease classification. Proceedings. IEEE International Symposium on Biomedical Imaging, 2019 414-417.
- Chowdhury, S.R., Dutta, J. (2019). Higher-order singular value decomposition-based lung parcellation for breathing motion management. SPIE Journal of Medical Imaging, 6(2) 024004.
- Yang, F., Roy Chowdhury, S., Jacobs HIL, ., Johnson, K.A., Dutta, J. (2019). A longitudinal model for tau aggregation in Alzheimer's disease based on structural connectivity. Information processing in medical imaging : proceedings of the ... conference, 11492 384-393.
- Kim, K., Dutta, J., Groll, A., El Fakhri, G., Meng, L.J., Li , Q. (2018). A novel depth-of-interaction rebinning strategy for ultrahigh resolution PET. Physics in medicine and biology, 63(16) 165011.
- Kim, K., Wu, D., Gong, K., Dutta, J., Kim, J.H., Son, Y.D., Kim, H.K., El Fakhri, G., Li , Q. (2018). Penalized PET reconstruction using deep learning prior and local linear fitting. IEEE Transactions on Medical Imaging, 37(6) 1478-1487.
- Yang, J., Hu, C., Guo, N., Dutta, J., Vaina, L.M., Johnson, K.A., Sepulcre, J., Fakhri, G.E., Li , Q. (2017). Partial volume correction for PET quantification and its impact on brain network in Alzheimer's disease. Scientific reports, 7(1) 13035.
- Groll, A., Kim, K., Bhatia, H., Zhang, J.C., Wang, J.H., Shen, Z.M., Cai, L., Dutta, J., Li , Q., Meng, L.J. (2017). Hybrid pixel-waveform (HPWF) enabled CdTe detectors for small animal gamma-ray imaging applications. IEEE Transactions on Radiation and Plasma Medical Sciences, 1(1) 3-14.
- Ying, J., Dutta, J., Guo, N., Xia, L., Sitek, A., Li, Q. (2016). Gold classification of COPDGene cohort based on deep learning (2016-May: pp. 2474 - 2478). ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
- Ying, J., Dutta, J., Guo, N., Hu, C., Zhou, D., Sitek, A., Li , Q. (2016). Classification of exacerbation frequency in the COPDGene cohort with deep belief networks. IEEE journal of biomedical and health informatics.
- Dutta, J., Fakhri, G.E., Zhu, X., Li, Q. (2015). PET point spread function modeling and image deblurring using a PET/MRI joint entropy prior (pp. 1423-1426).
- Dutta, J., Huang, C., Li , Q., El Fakhri, G. (2015). Pulmonary imaging using respiratory motion compensated simultaneous PET/MR. Medical physics, 42(7) 4227-40.
- Dutta, J., Leahy, R.M., Li , Q. (2013). Non-local means denoising of dynamic PET images. PloS one, 8(12) e81390.
- Dutta, J., Ahn, S., Li , Q. (2013). Quantitative statistical methods for image quality assessment. Theranostics, 3(10) 741-56.
- Dutta, J., Ahn, S., Li , C., Cherry, S.R., Leahy, R.M. (2012). Joint L1 and total variation regularization for fluorescence molecular tomography. Physics in medicine and biology, 57(6) 1459-76.
- Joshi, A.A., Chaudhari, A.J., Li , C., Dutta, J., Cherry, S.R., Shattuck, D.W., Toga, A.W., Leahy, R.M. (2010). DigiWarp: a method for deformable mouse atlas warping to surface topographic data. Physics in medicine and biology, 55(20) 6197-214.
- Dutta, J., Ahn, S., Joshi, A.A., Leahy, R.M. (2010). Illumination pattern optimization for fluorescence tomography: theory and simulation studies. Physics in medicine and biology, 55(10) 2961-82.
- Joshi, A.A., Chaudhari, A.J., Li , C., Shattuck, D.W., Dutta, J., Leahy, R.M., Toga, A.W. (2009). POSTURE MATCHING AND ELASTIC REGISTRATION OF A MOUSE ATLAS TO SURFACE TOPOGRAPHY RANGE DATA. Proceedings. IEEE International Symposium on Biomedical Imaging, 2009 366-369.
- Dutta, J., Ahn, S., Joshi, A.A., Leahy, R.M. (2009). Optimal Illumination Patterns for Fluorescence Tomography. Proceedings. IEEE International Symposium on Biomedical Imaging, 2009 1275-1278.
- Li , C., Mitchell, G.S., Dutta, J., Ahn, S., Leahy, R.M., Cherry, S.R. (2009). A three-dimensional multispectral fluorescence optical tomography imaging system for small animals based on a conical mirror design. Optics express, 17(9) 7571-85.
Selected Intellectual Property
- Patent - Dutta, J."Systems and methods for motion correction in positron emission tomography imaging," 9495771 United States
Selected Contracts, Fellowships, Grants and Sponsored Research
- Sleep metrics from machine learning for Alzheimer's disease diagnostics (2020), Grant - NIH/NIA
Dutta, J. (Principal)
- Tau quantitation in AD with high resolution MRI and PET (2015), Grant - NIH/NIA
Dutta, J. (Principal)