Browsing by Subject "Ophthalmic imaging"

Diagnosis, prognosis, and treatment of many ocular and neurodegenerative diseases, including achromatopsia (ACHM), require the visualization of microscopic structures in the eye. The development of adaptive optics ophthalmic imaging systems has made high resolution visualization of ocular microstructures possible. These systems include the confocal and split detector adaptive optics scanning light ophthalmoscope (AOSLO), which can visualize human cone and rod photoreceptors in vivo. However, the avalanche of data generated by such imaging systems is often too large, costly, and time consuming to be evaluated manually, making automation necessary. The few currently available automated cone photoreceptor identification methods are unable to reliably identify rods and cones in low-quality images of diseased eyes, which are common in clinical practice.

This dissertation describes the development of automated methods for the analysis of AOSLO images, specifically focusing on cone and rod photoreceptors which are the most commonly studied biomarker using these systems. A traditional image processing approach, which requires little training data and takes advantage of intuitive image features, is presented for detecting cone photoreceptors in split detector AOSLO images. The focus is then shifted to deep learning using convolutional neural networks (CNNs), which have been shown in other image processing tasks to be more adaptable and produce better results than classical image processing approaches, at the cost of requiring more training data and acting as a “black box”. A CNN based method for detecting cones is presented and validated against state-of-the-art cone detections methods for confocal and split detector images. The CNN based method is then modified to take advantage of multimodal AOSLO information in order to detect cones in images of subjects with ACHM. Finally, a significantly faster CNN based approach is developed for the classification and detection of cones and rods, and is validated on images from both healthy and pathological subjects. Additionally, several image processing and analysis works on optical coherence tomography images that were carried out during the completion of this dissertation are presented.

The completion of this dissertation led to fast and accurate image analysis tools for the quantification of biomarkers in AOSLO images pertinent to an array of retinal diseases, lessening the reliance on subjective and time-consuming manual analysis. For the first time, automatic methods have comparable accuracy to humans for quantifying photoreceptors in diseased eyes. This is an important step in the long-term goal to facilitate early diagnosis, accurate prognosis, and personalized treatment of ocular and neurodegenerative diseases through optimal visualization and quantification of microscopic structures in the eye.

Optical coherence tomography (OCT) is a non-invasive optical imaging modality which can provide high-resolution, cross-sectional images of retina and cornea. It has become a standard of care in ophthalmology for the diagnosis and monitoring of ocular diseases. However, current OCT systems face several major challenges, among which include: (1) difficult alignment and fixation in pediatric retinal imaging (2) limited cellular-level contrast for ophthalmic disease diagnosis and (3) expensive hardware and intensive computation requirements for real-time high-speed 3D imaging.

This dissertation describes the development of several novel optical design and signal processing approaches in OCT and optical coherence imaging technologies to address these limitations. We first describe a long working distance swept-source OCT system to facilitate retinal imaging in young children (chapter 2). The system incorporates two custom lenses and a novel compact 2f retinal scanning configuration to achieve a working distance of 350mm with a 16o OCT field of view. The system achieves high quality retinal imaging of children as young as 21 months old without sedation in the clinic. We then present a spectroscopic OCT technology that utilizes time-frequency analysis to obtain quantitative diagnostic information of cellular responses in the anterior chamber of the eye, which can indicate many ocular diseases such as hyphema and anterior uveitis. We demonstrate that this technology can differentiate and quantify the composition of anterior chamber blood cells such as red blood cells and subtypes of WBCs, including granulocytes, lymphocytes and monocytes (chapter 3 and 4). Finally, we describe a coherence-based 3D imaging technique that uses a grating for fast beam steering, a swept-source laser with long coherence length, and time-frequency analysis for depth retrieval (chapter 5). We demonstrate that the system can achieve high-speed 3D imaging with sub-millimeter axial resolution and tens of centimeters axial imaging ranging.

Ophthalmic microsurgery is one of the most commonly performed surgical procedures in the world and it necessitates precise three-dimensional manipulation of tissue at sub-millimeter spatial scales. As a result, ophthalmic surgeons require an operating microscope to perform surgery and to asses alterations to the tissue. Unfortunately, modern operating microscopes provide a limited en face perspective of the three-dimensional surgical field, and surgeons must infer depth information using stereoscopy and cannot directly visualize sub-surface anatomy. These limitations may compromise the surgeon’s ability to maneuver instruments axially and to comprehensively evaluate the three-dimensional tissue structure.

Optical coherence tomography (OCT) is a non-contact volumetric imaging modality that is well suited to image the anterior and posterior human eye in vivo. The success of OCT in clinical ophthalmology motivated the development of intraoperative OCT to overcome the limitations of the operating microscope for ophthalmic surgery. However, current intraoperative OCT systems either require pauses in surgery for imaging or are restricted to cross-sectional imaging during surgery, thereby preventing OCT imaging of live surgery that extends over three-dimensional space.

This dissertation describes the design, development, and assessment of novel technologies for ophthalmic OCT imaging and intrasurgical guidance. These technologies seek to address challenges associated with translating a biomedical imaging device to the human operating suite and to improve upon current surgical visualization methods. We first describe eye tracking technologies designed to compensate for undesired subject motion during retinal and anterior eye OCT imaging. Next, we present a novel optical design for OCT retinal imaging, demonstrate its use for pediatric imaging, and discuss its advantages compared to conventional OCT retinal scanners. We then present the first 4D (volumetric imaging over time) intraoperative OCT system capable of imaging human ophthalmic surgery at up to 3 volumes/second. We report the results of a clinical study in which 4D intraoperative OCT was successfully used in >150 human eye surgeries. Next, we describe the optimization of an ultrahigh-speed OCT system using optical amplification and present a novel OCT scanning method designed for 4D imaging. Finally, we present the preliminary design of a second-generation 4D intraoperative OCT system capable of imaging surgical maneuvers at 15 volumes/second.