MRI: Acquisition of OCT Imaging System and Deep Learning Workstation for Interdisciplinary Healthcare Research and Education

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This proposal requests acquisition of a swept-source optical coherence tomography (OCT) imaging system and a deep learning workstation (DLW) at California State University, Chico (CSU, Chico). The proposed OCT imaging system and DLW will enable studies on the application of OCT imaging in dentistry to detect early carious lesions, micro-fractures, pulpal inflammation, early dysplastic changes in oral malignancies and signatures of other dental diseases. Acquisition of the OCT imaging system and DLW will significantly enhance current research programs and enable new research directions at CSU, Chico. These instruments will also support the established collaborative research with faculty at the Stony Brook University School of Dental Medicine. Approximately 500 students from the Departments of Electrical and Computer Engineering, Computer Science, and Mechanical and Mechatronic Engineering and Sustainable Manufacturing will be among the major users of the OCT system and DLW and will be available for use by the broader CSU, Chico research community. CSU, Chico is a minority-serving institution with a large proportion of students from underrepresented and underserved groups, including veterans, and Hispanics. This cutting-edge OCT system and DLW will provide these students with hands-on experience. The OCT system and DLW will be used to (1) increase involvement of undergraduate students in research, (2) promote active learning and skills development, (3) train upper-division undergraduate and graduate students on state-of-the-art imaging and algorithm development techniques, and (4) stimulate collaborations with faculty and students across CSU, Chico and from other institutions of higher learning. The proposed swept-source optical coherence tomography (OCT) imaging system and deep learning workstation (DLW) will stimulate interdisciplinary research projects in healthcare and industrial nondestructive testing at CSU, Chico. OCT is a noninvasive optical imaging modality based on low-coherence interferometry that utilizes non-ionizing near-infrared laser to obtain images with 1-10 micrometer resolution. Currently, the major biomedical application of OCT is in ophthalmology. Many other applications of OCT are under investigation as researchers take advantage of the ability to rapidly acquire images noninvasively. Machine learning and deep learning techniques can be used to supplement the OCT images to more accurately identify diseased and damaged tissue. The following research projects at CSU, Chico will utilize the OCT imaging system and DLW: (1) the development of a deep learning model, namely convolutional neural networks (CNN), and quantitative analysis of OCT images for early dental caries detection; (2) the investigation of various deep learning optimization methods and their performances with OCT images to minimize back-propagating errors; (3) the development of signal and image processing algorithms to extract meaningful features from OCT data for image classification; (4) the design of compact and low-cost fiber optic based probe for noninvasive OCT imaging of occlusal caries; and (5) the use of deep learning to analyze and model non-speech sounds, such as music or industrial noise, as well as automatic analysis and classification of musical timbre. The OCT imaging system and DLW will help catalyze interdisciplinary efforts between engineering, science, and agriculture faculty, and develop an undergraduate and graduate research and teaching laboratory at CSU, Chico.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.