Browsing by Subject "Multimodal imaging"
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Item Open Access Development of Coherence-Gated and Resolution-Multiplexed Optical Imaging Systems(2010) Tao, Yuankai KennyOptical interrogation techniques are particularly well-suited for imaging tissue morphology, biological dynamics, and disease pathogenesis by providing noninvasive access to subcellular-resolution diagnostic information. State-of-the-art spectral domain optical coherence tomography (SDOCT) systems provide real-time optical biopsies of in vivo tissue, and have demonstrated clinical potential, particularly for applications in ophthalmology.
Recent advances in microscopy and endoscopy have led to improved resolution and compact optical designs, beyond those of conventional imaging systems. Application of encoded and multiplexed illumination and detection schemes may allow for the development of optical tools that surpass classical imaging limitations. Furthermore, complementary technologies can be combined to create multimodal optical imaging tools with advantages over current-generation systems.
In this dissertation, the development of coherence-gated and resolution-multiplexed technologies, aimed towards applications in human vitreoretinal imaging is described. Technology development in coherence-gated systems included increasing the imaging range of SDOCT by removing the complex conjugate artifact, improving acquisition speed using a scanning spectrometer design and a two-dimensional detector array, and hardware and algorithmic implementations that facilitated imaging of Doppler flow.
Structured illumination microscopy techniques were applied for resolution enhancement, and a spectrally encoded ophthalmic imaging system was developed for en face confocal fundus imaging through a single-mode fiber. These devices were resolution-multiplexed extensions of existing ophthalmic imaging devices, such as scanning laser ophthalmoscopes (SLO), which demonstrated improved resolution and more compact optical designs as compared to their conventional counterparts.
Finally, several multimodal ophthalmic diagnostic tools were developed that combined the advantages of OCT with existing imaging devices. These included a combined SLO-OCT system and a vitreoretinal surgical microscope combined with OCT. These devices allowed for concurrent ophthalmic imaging using complementary modalities for improved visualization and clinical utility.
Item Open Access Development of Swept Source Optical Coherence Tomography and Adaptive Optics Scanning Laser Ophthalmoscopy: Improved Imaging Speed and Handheld Applications(2016) Nankivil, DerekOptical coherence tomography (OCT) is a noninvasive three-dimensional interferometric imaging technique capable of achieving micrometer scale resolution. It is now a standard of care in ophthalmology, where it is used to improve the accuracy of early diagnosis, to better understand the source of pathophysiology, and to monitor disease progression and response to therapy. In particular, retinal imaging has been the most prevalent clinical application of OCT, but researchers and companies alike are developing OCT systems for cardiology, dermatology, dentistry, and many other medical and industrial applications.
Adaptive optics (AO) is a technique used to reduce monochromatic aberrations in optical instruments. It is used in astronomical telescopes, laser communications, high-power lasers, retinal imaging, optical fabrication and microscopy to improve system performance. Scanning laser ophthalmoscopy (SLO) is a noninvasive confocal imaging technique that produces high contrast two-dimensional retinal images. AO is combined with SLO (AOSLO) to compensate for the wavefront distortions caused by the optics of the eye, providing the ability to visualize the living retina with cellular resolution. AOSLO has shown great promise to advance the understanding of the etiology of retinal diseases on a cellular level.
Broadly, we endeavor to enhance the vision outcome of ophthalmic patients through improved diagnostics and personalized therapy. Toward this end, the objective of the work presented herein was the development of advanced techniques for increasing the imaging speed, reducing the form factor, and broadening the versatility of OCT and AOSLO. Despite our focus on applications in ophthalmology, the techniques developed could be applied to other medical and industrial applications. In this dissertation, a technique to quadruple the imaging speed of OCT was developed. This technique was demonstrated by imaging the retinas of healthy human subjects. A handheld, dual depth OCT system was developed. This system enabled sequential imaging of the anterior segment and retina of human eyes. Finally, handheld SLO/OCT systems were developed, culminating in the design of a handheld AOSLO system. This system has the potential to provide cellular level imaging of the human retina, resolving even the most densely packed foveal cones.
Item Embargo Development of X-ray Fan Beam Coded Aperture Diffraction Imaging for Improving Breast Cancer Diagnostics(2021) Stryker, StefanX-ray imaging technology has been used for a multitude of medical applications over the years. The typically measured X-ray transmission data, which records shape and density information by measuring the differences in X-ray attenuation throughout a material, have been used in the imaging modalities of radiography and computed tomography (CT), but there are cases where this information alone is not enough for diagnosis. In contrast, X-ray diffraction (XRD) is another X-ray measurement modality, one that typically does not produce spatially resolved 2D/3D images, but instead investigates small spatial spots for assessing material properties/molecular structures based on scattered X-rays. While XRD measurements of human breast tissue have previously suggested differences between signatures of cancerous and benign tissues, the typical diffraction system architectures do not support fast, large field of view imaging that is necessary for medical applications.In this work, an XRD imaging system was developed that can scan a 15x15 cm2 field of view in minutes with an XRD spatial resolution of 1.4 mm2 and momentum transfer (q) resolution of 0.02 Å-1. An X-ray fan beam was used to collect a 15 cm line of XRD measurements in a single snapshot, while a coded aperture is placed between imaged objects and detector, enabling XRD spectra for individual pixels along the fan beam extent to be recovered from the multiplexed measurement. Simulations were used to identify a suitable geometry for the system, while newly designed phantoms and test objects were used to evaluate the resolution/measurement quality. Upon finishing the design, construction, and characterization of the imaging system, studies on cancerous and benign tissue simulant phantoms were conducted to develop and identify top performing machine learning classification algorithms in a well-controlled study. With a shallow neural network (SNN) developed that achieved ≈99% accuracy on XRD image data, studies progressed to real human tissues. With these developments achieved, the final study was conducted where 22 human breast lumpectomy specimens were scanned and the SNN algorithm was modified for identification of human breast cancer. For 15 primary lumpectomy cases used for training and testing, an accuracy of 99.7% was achieved, with an ROC curve AUC of 0.953 and precision-recall curve AUC of 0.771. On the remaining 7 corner/rare cases present that were held out from initial training/testing (as an external dataset), an accuracy of 99.3% was achieved by the SNN, suggesting high performance along with a need for further representation of rare tissue cases in the training process to improve classifier generalization to new lumpectomy cases. This work demonstrates that fast, large field of view XRD imaging of thin samples on a millimeter spatial scale can be achieved using coded apertures. Further, the work shows that machine learning algorithms can complement this imaging modality by making great use of the multitude of input features available when each image pixel contains a full spectrum of XRD intensity vs angle values, allowing for algorithms to differentiate between cancerous and healthy tissue with higher accuracy (99.7%) compared to simple classification approaches (97.3%). Due to this promising potential, future work should seek to further the technology, by improving the spatial/spectral resolution, scan speed, and adding depth resolution, while applying the technology to useful medical tasks including (but not limited to) intraoperative surgical margin assessment, in-vivo imaging for biopsy vetting, and improved radiation therapy tumor localization.