[CCoE Notice] Cullen College Dissertation Announcement- Chalapathi C Gajjela (ECE)

[Hutchinson, Inez A]

[Dissertation Defense Announcement at the Cullen College of Engineering]
PHOTOTHERMAL MID-INFRARED SPECTROSCOPIC
IMAGING AND ITS BIOMEDICAL APPLICATIONS
Chalapathi C Gajjela

December 7, 2023; 2:00 PM - 3:00 PM (CST)
Location: ECE Conference Room

Committee Chair:

Rohith K Reddy, Ph.D.

Committee Members:

David Mayerich, Ph.D. | Saurabh Prasad, Ph.D. | Chandra Mohan, Ph.D. | Oxana Klementieva, Ph.D.

Abstract

The current standard disease diagnosis and  prognosis method primarily utilizes histopathology, but conventional histological methods can be non-quantitative, subjective, and limited to specific biomarkers. However, when combined with modern histology, spectroscopic imaging may provide more precise measurements by overcoming variations in sample preparation and pathological expertise. Mid-infrared (mid-IR) spectroscopic imaging has been widely used in various applications, including cancer grading. However, one of the main limitations of MIRSI is its low spatial resolution due to long mid-infrared wavelengths. To overcome this limitation, we explored a new imaging technique of optical photothermal infrared (O-PTIR) imaging based on vibrational excitation with mid-infrared light and probing the absorption with visible light through the thermal lensing effect. We demonstrated that this technique significantly improves the resolution by an order of magnitude relative to FT-IR imaging. We used this new imaging technique to study ovarian and cervical cancer tissueand compared it to conventional MIRSI using FT-IR microspectroscopy. This dissertation aims to utilize the improved resolution of O-PTIR imaging to study the biomedical applications in two projects, firstly the classification of cells in ovarian and cervical cancer biopsies, which could potentially improve usability in a clinical environment for early diagnosis, and secondly, determining different biomarkers for distinguishing between healthy kidneys and kidneys with lupus nephritis. The third project has been proposed to improve the data collection speed of the O-PTIR system by 10-12 times using sparse data reconstruction and image sharpening via curvelets.

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