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Automated and accurate segmentation of cystoid structures in Optical Coherence Tomography (OCT) is of interest in the early detection of retinal diseases. It is, however, a challenging task. We propose a novel method for localizing cysts in…

Computer Vision and Pattern Recognition · Computer Science 2017-08-29 Karthik Gopinath , Jayanthi Sivaswamy

Two-dimensional (2D) spectroscopy combines high temporal and spectral resolution, allowing the observation of ultrafast energy transfer and the separation of homogeneous and inhomogeneous broadening. Typically, 2D spectroscopy is dominated…

The measurement of three-dimensional (3D) images and the analysis of subcellular organelles are crucial for the study of the pathophysiology of cells and tissues. Optical diffraction tomography (ODT) facilitates label-free and quantitative…

Image and Video Processing · Electrical Eng. & Systems 2019-10-08 Taean Chang , Seungwoo Shin , Moosung Lee , YongKeun Park

Optical coherence tomography (OCT) has become the most important imaging modality in ophthalmology. A substantial amount of research has recently been devoted to the development of machine learning (ML) models for the identification and…

The intensity levels allowed by safety standards (ANSI or ICNIRP) limit the amount of light that can be used in a clinical setting to image highly scattering or absorptive tissues with Optical Coherence Tomography (OCT). To achieve…

Spectral domain optical coherence tomography (OCT) offers high resolution multidimensional imaging, but generally suffers from defocussing, intensity falloff and shot noise, causing artifacts and image degradation along the imaging depth.…

Image and Video Processing · Electrical Eng. & Systems 2021-08-04 Jonathan H. Mason , Yvonne Reinwald , Ying Yang , Sarah Waters , Alicia El Haj , Pierre O. Bagnaninchi

Optical diffraction tomography (ODT) is an emerging 3D imaging technique that is used for the 3D reconstruction of the refractive index (RI) for semi-transparent samples. Various inverse models have been proposed to reconstruct the 3D RI…

Optics · Physics 2022-06-13 Ahmed B. Ayoub , Amirhossein Saba , Carlo Gigli , Demetri Psaltis

Optical Coherence Tomography (OCT) is an imaging modality that has been widely adopted for visualizing corneal, retinal and limbal tissue structure with micron resolution. It can be used to diagnose pathological conditions of the eye, and…

Image and Video Processing · Electrical Eng. & Systems 2019-05-08 Jiahong Ouyang , Tejas Sudharshan Mathai , Kira Lathrop , John Galeotti

Optical Coherence Tomography (OCT) is a widely used non-invasive biomedical imaging modality that can rapidly provide volumetric images of samples. Here, we present a deep learning-based image reconstruction framework that can generate…

Image and Video Processing · Electrical Eng. & Systems 2021-07-30 Yijie Zhang , Tairan Liu , Manmohan Singh , Yilin Luo , Yair Rivenson , Kirill V. Larin , Aydogan Ozcan

To add the detailed information to the existed knowledge of nonlinear optics field, the nonlinear optical processes of the second and third order have been discussed in their respective susceptibility tensors in the presence of degenerate…

Optics · Physics 2018-01-29 A Srinivasa Rao

The Henle's fiber layer (HFL) in the retina carries valuable information on the macular condition of an eye. However, in the common practice, this layer is not separately segmented but rather included in the outer nuclear layer since it is…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Selahattin Cansiz , Cem Kesim , Sevval Nur Bektas , Zeynep Kulali , Murat Hasanreisoglu , Cigdem Gunduz-Demir

We apply three optical coherence tomography (OCT) image analysis techniques to extract morphometric information from OCT images obtained on peripheral nerves of rat. The accuracy of each technique is evaluated against histological…

Tissues and Organs · Quantitative Biology 2019-01-09 J. Hope , B. Brauer , S. Amirapu , A. McDaid , F. Vanholsbeeck

Second-order optical nonlinearities can be greatly enhanced by orders of magnitude in resonantly excited nanostructures, theoretically predicted and experimentally investigated in a variety of semiconductor systems. These resonant…

Alternative machine learning approaches that are computationally light with low latency and can work with only a small training dataset are needed for applications where the insatiable demand of deep learning methods for computing power and…

Optics · Physics 2021-07-29 Tingyi Zhou , Fabien Scalzo , Bahram Jalali

Optical Coherence Tomography (OCT) is a key 3D imaging technology that provides micron scale depth resolution for bio-imaging. This resolution substantially surpasses what it typically achieved in Light Detection and Ranging (LiDAR) which…

Optics · Physics 2022-07-27 Robbie Murray , Ashley Lyons

We develop a data-driven optimal shrinkage algorithm for matrix denoising in the presence of high-dimensional noise with a separable covariance structure; that is, the noise is colored and dependent across samples. The algorithm, coined…

Applications · Statistics 2024-05-14 Pei-Chun Su , Hau-Tieng Wu

Optical coherence tomography (OCT) has proven to be a powerful technique for studying tissue morphology in ophthalmology, cardiology, and endomicroscopy. Its performance is limited by the fundamental trade-off between the imaging…

Optics · Physics 2008-02-27 Keisuke Goda , Daniel R. Solli , Bahram Jalali

We have observed nonlinear transduction of the thermomechanical motion of a nanomechanical resonator when detected as laser transmission through a sideband unresolved optomechanical cavity. Nonlinear detection mechanisms are of considerable…

Mesoscale and Nanoscale Physics · Physics 2014-12-25 C. Doolin , B. D. Hauer , P. H. Kim , A. J. R. MacDonald , H. Ramp , J. P. Davis

We introduce a novel algorithm for nonlinear processing of data gathered by an active array of sensors which probes a medium with pulses and measures the resulting waves. The algorithm is motivated by the application of array imaging. We…

Numerical Analysis · Mathematics 2019-02-20 Liliana Borcea , Vladimir Druskin , Alexander V. Mamonov , Mikhail Zaslavsky

In the real world, out-of-distribution samples, noise and distortions exist in test data. Existing deep networks developed for point cloud data analysis are prone to overfitting and a partial change in test data leads to unpredictable…

Computer Vision and Pattern Recognition · Computer Science 2020-12-04 Morteza Ghahremani , Bernard Tiddeman , Yonghuai Liu , Ardhendu Behera