About

Dr. Nathan Doble joined the Ohio State College of Optometry in July 2013 as an Associate Professor. His research focuses on the design, development, and construction of high-resolution optical imaging systems for in-vivo visualization of the human retina at the cellular level. These systems aim to enhance understanding, enable earlier diagnosis, and improve treatment of various retinal pathologies. Prior to his current position, Dr. Doble was a faculty member at the New England College of Optometry in Boston, MA, from 2008 to 2013. He is also a co-founder of Iris AO Inc., a Berkeley-based company specializing in adaptive optics (AO) applied to biomedical imaging and the construction of deformable mirrors using micro-electromechanical systems (MEMS) technology. Dr. Doble holds M.Sci, M.Sc., and Ph.D. degrees in laser physics and adaptive optics, and has contributed extensively to the field through books, book chapters, journal articles, patents, and presentations, advancing the application of adaptive optics in vision science and ophthalmology.

Research topics

• Computer Science
• Optics
• Physics
• Artificial Intelligence
• Medicine
• Ophthalmology
• Computer vision

Selected publications

• In vivo imaging of the outer retina after an autologous neurosensory retinal free flap transplantation for a refractory macular hole closure

  Journal of Medical Case Reports · 2026-01-07

  articleOpen access

  BACKGROUND: There are limited surgical options to successfully close a refractory macular hole. One promising option is an autologous neurosensory retinal free flap transplantation. An autologous neurosensory retinal free flap transplantation places a graft of peripheral autologous retinal tissue into the macular hole and was developed to improve post-surgical outcomes. Here, clinical instrumentation and a high-resolution adaptive optics system imaged the graft and host tissue of a patient whose refractory macular hole was successfully closed with an autologous neurosensory retinal free flap transplantation. CASE PRESENTATION: A 71-year-old Hispanic female with bilateral moderate nonproliferative diabetic retinopathy (visual acuity of 20/100 in each eye) underwent an autologous neurosensory retinal free flap transplantation in the right eye only, which successfully closed a large refractory macular hole measuring 4° in diameter. Although somewhat variable, the best-corrected visual acuity improved from 20/100 to 20/70 with a subjective improvement noted by the patient. The eye was examined using (1) fundus photography and (2) clinical optical coherence tomography both presurgery and post surgery and (3) with adaptive optics-optical coherence tomography-scanning laser ophthalmoscopy post surgery. Postsurgical clinical optical coherence tomography imaging revealed restoration of the external limiting membrane within the graft. Adaptive optics-optical coherence tomography imaging provided enhanced lateral and axial resolution and showed a restored inner segment/outer segment junction within the graft. Adaptive optics-optical coherence tomography also revealed the cone outer segment tip layer in the host tissue, highlighting preservation of the microarchitecture and indicating that the host tissue was not negatively impacted by the surgery or the presence of the graft. Further, adaptive optics-scanning laser ophthalmoscopy imaging revealed photoreceptors within the graft and surrounding host tissue, indicating surgical success, graft acceptance and viable host tissue. CONCLUSION: Although the exact physiological mechanisms that promote macular hole closure and intraretinal cellular changes after an autologous neurosensory retinal free flap transplantation are unknown, imaging supports the procedure as a reasonable surgical option for refractory macular hole closure. The preserved integrity of the host tissue suggests that the graft does not negatively impact the retina following the surgery. Furthermore, the improvement in the inner segment/outer segment junction and external limiting membrane noted over time within the graft are considered favorable as they relate to the structure and function of the retina.

  PublisherDOI

• ISOSNet: a unified framework for cone photoreceptor detection and inner segment and outer segment length measurement from AO-OCT B-scans

  Biomedical Optics Express · 2025-05-22 · 2 citations

  articleOpen access

  Adaptive optics-optical coherence tomography (AO-OCT) enables cellular-level in vivo visualization of cone photoreceptors in the human retina. Cone biomarkers, such as density, inner segment (IS), and outer segment (OS) lengths, are potentially important for the early detection of many outer retinal conditions. However, their dense spatial packing necessitates automated analytical methods, and most existing approaches focus primarily on cone detection without addressing their detailed structural characteristics. To address this limitation, a unified neural network, termed ISOSNet, is introduced for simultaneous cone detection and IS/OS length measurement. Labeled AO-OCT B-scan datasets, encompassing healthy individuals across multiple retinal locations, were collected for model training and evaluation. Experimental results demonstrate an F1 score of 0.886 for cone detection and relative error rates of 6% and 11% for IS and OS length measurement, respectively. Validation on images from diseased retinas-despite the model being trained only on healthy retina data-highlights the generalizability of the proposed framework.

  PublisherDOI

• On-axis full-field swept-source optical coherence tomography for murine retinal imaging

  Optics Letters · 2024-07-25 · 19 citations

  articleOpen accessCorresponding

  A full-field swept-source optical coherence tomography (FF-SS-OCT) for in vivo murine retinal imaging is demonstrated. The on-axis FF-SS-OCT system was built in a Mach-Zehnder interferometer configuration employing a tunable laser source with an adjustable sweep rate and sweep range in conjunction with a fast 2D-CMOS camera. A large field retinal (coherent) illumination was accomplished using an imaging interface comprised of a short-focal length imaging lens and a contact lens. The magnification between the camera and retina (spatial sampling) was appropriately chosen to record the microscopic structural features of the retina in the image. A pupil stop was employed in the detection path to reject unwanted backscattering from the mouse eye and other sources and limit aberrations distorting the retinal images. In vivo mouse retinal imaging was performed at a sweep rate of 150 Hz to acquire volumes unaffected by the system vibrations, which predominated at lower frequencies. Operating the FF-SS-OCT at this speed yielded an effective axial scan rate of 20 million A-scans/s and a field of view of 820 × 410 µm (24.12° × 12.06°). High-quality retinal B-scans and enface images of the retina were obtained with the SS-FF-OCT, revealing all major retinal layers and vascular plexuses.

  PublisherOA PDFDOI

• Quantitative Analysis of the Vasculature and Cone Photoreceptors in Subjects With Diabetes Without Diabetic Retinopathy

  Current Eye Research · 2024-02-26

  article

  PURPOSE: To characterize any differences in the vasculature and cone photoreceptor packing geometry (CPG) between subjects with diabetes without/no diabetic retinopathy (NDR) and healthy controls. METHODS: Eight NDR and five controls were enrolled. Optical coherence tomography angiography (OCTA) taken at the macula was used to measure vessel density, vessel length density, and vessel density index (VDI) in three vascular plexuses, namely, the superficial vascular plexus, intermediate capillary plexus, and deep capillary plexus (DCP). The choriocapillaris (CC) flow deficit (FD) was also measured. OCTA images were binarized and processed to extrapolate the parafovea and parafoveal quadrants and the OCTA indices mentioned above. The CC was processed with six different radii to quantify FD. Adaptive optics - scanning laser ophthalmoscopy images were acquired and processed to extract CPG indices, i.e., cone density (CD), cone-to-cone spacing (CS), linear dispersion index, heterogeneity packing index and percent of cells with six neighbors at 3.6° in the temporal retina. RESULTS: = 0.048). No other significant correlations were found. For OCTA or CPG indices, no significant differences were found between the cohorts in the parafovea or parafoveal quadrants. CONCLUSIONS: CS is the most sensitive CPG index for detecting alterations in the cone mosaic. The DCP and the cone photoreceptors are significantly correlated, indicating that alterations in the DCP can affect the cones. Future work elucidating the vascular alterations and neurodegeneration present in diabetic eyes should focus on the DCP and multiple CPG indices, not solely CD. Moreover, such alterations are highly localized, hence using larger regions e.g. parafovea versus smaller areas, such as the PTQ, will potentially mask significant correlations.

  PublisherDOI

• High-speed, phase contrast retinal and blood flow imaging using an adaptive optics partially confocal multi-line ophthalmoscope

  Biomedical Optics Express · 2024-01-22 · 8 citations

  articleOpen accessSenior author

  High-speed, phase contrast retinal and blood flow imaging using an adaptive optics partially confocal multi-line ophthalmosocope (AO-pcMLO) is described. It allows for simultaneous confocal and phase contrast imaging with various directional multi-line illumination by using a single 2D camera and a digital micromirror device (DMD). Both vertical and horizontal line illumination directions were tested, for photoreceptor and vascular imaging. The phase contrast imaging provided improved visualization of retinal structures such as cone inner segments, vessel walls and red blood cells with images being acquired at frame rates up to 500 Hz. Blood flow velocities of small vessels (<40 µ m in diameter) were measured using kymographs for capillaries and cross-correlation between subsequent images for arterioles or venules. Cardiac-related pulsatile patterns were observed with normal resting heart-beat rate, and instantaneous blood flow velocities from 0.7 to 20 mm/s were measured.

  PublisherDOI

• Reducing manual labeling requirements and improved retinal ganglion cell identification in 3D AO-OCT volumes using semi-supervised learning

  Biomedical Optics Express · 2024-06-26 · 7 citations

  articleOpen access

  Adaptive optics-optical coherence tomography (AO-OCT) allows for the three-dimensional visualization of retinal ganglion cells (RGCs) in the living human eye. Quantitative analyses of RGCs have significant potential for improving the diagnosis and monitoring of diseases such as glaucoma. Recent advances in machine learning (ML) have made possible the automatic identification and analysis of RGCs within the complex three-dimensional retinal volumes obtained with such imaging. However, the current state-of-the-art ML approach relies on fully supervised training, which demands large amounts of training labels. Each volume requires many hours of expert manual annotation. Here, two semi-supervised training schemes are introduced, (i) cross-consistency training and (ii) cross pseudo supervision that utilize unlabeled AO-OCT volumes together with a minimal set of labels, vastly reducing the labeling demands. Moreover, these methods outperformed their fully supervised counterpart and achieved accuracy comparable to that of human experts.

  PublisherDOI

• Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain

  2024-08-24 · 2 citations

  preprintOpen access

  Standard modern machine-learning-based imaging methods have faced challenges in medical applications due to the high cost of dataset construction and, thereby, the limited labeled training data available. Additionally, upon deployment, these methods are usually used to process a large volume of data on a daily basis, imposing a high maintenance cost on medical facilities. In this paper, we introduce a new neural network architecture, termed LoGoNet, with a tailored self-supervised learning (SSL) method to mitigate such challenges. LoGoNet integrates a novel feature extractor within a U-shaped architecture, leveraging Large Kernel Attention (LKA) and a dual encoding strategy to capture both long-range and short-range feature dependencies adeptly. This is in contrast to existing methods that rely on increasing network capacity to enhance feature extraction. This combination of novel techniques in our model is especially beneficial in medical image segmentation, given the difficulty of learning intricate and often irregular body organ shapes, such as the spleen. Complementary, we propose a novel SSL method tailored for 3D images to compensate for the lack of large labeled datasets. The method combines masking and contrastive learning techniques within a multi-task learning framework and is compatible with both Vision Transformer (ViT) and CNN-based models. We demonstrate the efficacy of our methods in numerous tasks across two standard datasets (i.e., BTCV and MSD). Benchmark comparisons with eight state-of-the-art models highlight LoGoNet's superior performance in both inference time and accuracy.

  PublisherOA PDFDOI

• Assessing the efficacy of 2D and 3D CNN algorithms in OCT-based glaucoma detection

  Scientific Reports · 2024-05-23 · 19 citations

  articleOpen access

  Glaucoma is a progressive neurodegenerative disease characterized by the gradual degeneration of retinal ganglion cells, leading to irreversible blindness worldwide. Therefore, timely and accurate diagnosis of glaucoma is crucial, enabling early intervention and facilitating effective disease management to mitigate further vision deterioration. The advent of optical coherence tomography (OCT) has marked a transformative era in ophthalmology, offering detailed visualization of the macula and optic nerve head (ONH) regions. In recent years, both 2D and 3D convolutional neural network (CNN) algorithms have been applied to OCT image analysis. While 2D CNNs rely on post-prediction aggregation of all B-scans within OCT volumes, 3D CNNs allow for direct glaucoma prediction from the OCT data. However, in the absence of extensively pre-trained 3D models, the comparative efficacy of 2D and 3D-CNN algorithms in detecting glaucoma from volumetric OCT images remains unclear. Therefore, this study explores the efficacy of glaucoma detection through volumetric OCT images using select state-of-the-art (SOTA) 2D-CNN models, 3D adaptations of these 2D-CNN models with specific weight transfer techniques, and a custom 5-layer 3D-CNN-Encoder algorithm. The performance across two distinct datasets is evaluated, each focusing on the macula and the ONH, to provide a comprehensive understanding of the models' capabilities in identifying glaucoma. Our findings demonstrate that the 2D-CNN algorithm consistently provided robust results compared to their 3D counterparts tested in this study for glaucoma detection, achieving AUC values of 0.960 and 0.943 for the macular and ONH OCT test images, respectively. Given the scarcity of pre-trained 3D models trained on extensive datasets, this comparative analysis underscores the overall utility of 2D and 3D-CNN algorithms in advancing glaucoma diagnostic systems in ophthalmology and highlights the potential of 2D algorithms for volumetric OCT image-based glaucoma detection.

  PublisherOA PDFDOI

• HIGH-RESOLUTION IMAGING OF THE OUTER RETINA IN TYPE 2 ACUTE MACULAR NEURORETINOPATHY

  Retinal Cases & Brief Reports · 2023-03-30 · 1 citations

  article1st authorCorresponding

  PURPOSE: The purpose of this study was to investigate the outer retinal changes in a patient with type 2 acute macular neuroretinopathy (AMN). METHODS: A 35-year-old White woman complaining of a unilateral blind spot was imaged using various retinal imaging modalities including clinical optical coherence tomography (OCT), OCT-angiography, fundus fluorescein angiography, and adaptive optics (AO). RESULTS: Fundus examination revealed multiple paracentral reddish brown petaloid lesions in the symptomatic left eye, while the other eye was unremarkable. Clinical OCT showed areas of hyperreflectance at the outer plexiform layer/outer nuclear layer complex with a disrupted inner/outer segment junction, which are characteristic features of type 2 AMN. AO imaging further revealed either shortening or absence of cone outer segments within the AMN lesions attributing to the darker features observed in the en face images from fundus photography and scanning laser ophthalmoscopy. CONCLUSION: The AO findings indicate that the petaloid lesions in type 2 AMN are caused by a combination of the shortening and absence of the outer segment in individual cone photoreceptors.

  PublisherDOI

• High-speed adaptive optics partially confocal ophthalmoscope based on Digital Micromirror Device (DMD)

  2023-03-15 · 1 citations

  articleSenior author

  A high-speed adaptive optics (AO) partially-confocal ophthalmoscope using a digital micromirror device (DMD) and high-speed 2D CMOS camera is presented. The system allows for easy control of the trade-off between image acquisition rate and contrast by applying different illumination patterns on the DMD. The camera is synchronized with the DMD projecting multi-spot patterns on the human retina, which is pre-corrected by AO, for parallel scanning. Frame acquisition rates up to 250 fps was achieved this applying multi-spot scheme, with the contrast improving 2-3 fold compared to standard flood illumination. Partially confocal images of the human retina showed cone and rod photoreceptors over a range of retinal eccentricities.

  PublisherDOI

Recent grants

• NIH Grant R01EY020901

  NIH · $1.2M · 2015

• Core C. Image Analysis and Data Science (IADS)

  NIH · $4.7M · 2022–2027

Frequent coauthors

• Soichiro Tsuda

  252 shared

• Murat Okandan

  132 shared

• Rita E. Serda

  University of New Mexico

  131 shared

• Zeynep Çelik‐Butler

  The University of Texas at Arlington

  131 shared

• Ryan M. Pocratsky

  Carnegie Mellon University

  131 shared

• Mitsumasa Iwamoto

  Tokyo Institute of Technology

  131 shared

• Farghalli A. Mohamed

  University of California, Irvine

  131 shared

• Craig Snoeyink

  University at Buffalo, State University of New York

  131 shared

Labs

• Karla Zadnik LabPI

Education

• Ph.D., Optometry

  The Ohio State University

  2008

• M.S., Optometry

  The Ohio State University

  2003

• B.S., Optometry

  The Ohio State University

  2001

Awards & honors

• 1st Place Purdue Life Sciences Business Plan Competition ($6…
• 1st Place MBA Jungle Second Annual Business Plan Competition…
• 1st Place Fourth Annual UC Berkeley Business Plan Competitio…