Estimation of non-uniform motion blur using a patch-based regression convolutional neural network.

The non-uniform blur of atmospheric turbulence can be modeled as a superposition of linear motion blur kernels at a patch level. We propose a regression convolutional neural network (CNN) to predict angle and length of a linear motion blur kernel for varying sized patches. We analyze the robustness of the network for different patch sizes and the performance of the network in regions where the characteristics of the blur are transitioning.

Estimation of modified Zernike coefficients from turbulence-degraded multispectral imagery using deep learning.

We investigate how wavelength diversity affects the performance of a deep-learning model that predicts the modified Zernike coefficients of turbulence-induced wavefront error from multispectral images. The ability to perform accurate predictions of the coefficients from images collected in turbulent conditions has potential applications in image restoration. The source images for this work were a point object and extended objects taken from a character-based dataset, and a wavelength-dependent simulation was developed that applies the effects of isoplanatic atmospheric turbulence to the images.

Quantifying the Consistency and Characterizing the Confidence of Coronal Holes Detected by Active Contours Without Edges (ACWE).

Coronal Holes (CHs) are regions of open magnetic-field lines, resulting in high-speed solar wind. Accurate detection of CHs is vital for space-weather prediction. This paper presents an intramethod ensemble for coronal-hole detection based on the Active Contours Without Edges (ACWE) segmentation algorithm.

Solar active region magnetogram image dataset for studies of space weather.

In this dataset we provide a comprehensive collection of line-of-sight (LOS) solar photospheric magnetograms (images quantifying the strength of the photospheric magnetic field) from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO). The dataset incorporates data from three sources and provides SDO Helioseismic and Magnetic Imager (HMI) magnetograms of solar active regions (regions of large magnetic flux, generally the source of eruptive events) as well as labels of corresponding flaring activity. This dataset will be useful for image analysis or solar physics research related to magnetic structure, its evolution over time, and its relation to solar flares.

Morphological restriction of human coronary artery endothelial cells substantially impacts global gene expression patterns.

Alterations in cell shape have been shown to modulate chromatin condensation and cell lineage specification; however, the mechanisms controlling these processes are largely unknown. Because endothelial cells experience cyclic mechanical changes from blood flow during normal physiological processes and disrupted mechanical changes as a result of abnormal blood flow, cell shape deformation and loss of polarization during coronary artery disease, we aimed to determine how morphological restriction affects global gene expression patterns. Human coronary artery endothelial cells (HCAECs) were cultured on spatially defined adhesive micropatterns, forcing them to conform to unique cellular morphologies differing in cellular polarization and angularity.

Targeting of beta adrenergic receptors results in therapeutic efficacy against models of hemangioendothelioma and angiosarcoma.

Therapeutic targeting of the beta-adrenergic receptors has recently shown remarkable efficacy in the treatment of benign vascular tumors such as infantile hemangiomas. As infantile hemangiomas are reported to express high levels of beta adrenergic receptors, we examined the expression of these receptors on more aggressive vascular tumors such as hemangioendotheliomas and angiosarcomas, revealing beta 1, 2, and 3 receptors were indeed present and therefore aggressive vascular tumors may similarly show increased susceptibility to the inhibitory effects of beta blockade. Using a panel of hemangioendothelioma and angiosarcoma cell lines, we demonstrate that beta adrenergic inhibition blocks cell proliferation and induces apoptosis in a dose dependent manner.

Propranolol treatment of infantile hemangioma endothelial cells: A molecular analysis.

Infantile hemangiomas (IHs) are non-malignant, largely cutaneous vascular tumors affecting approximately 5-10% of children to varying degrees. During the first year of life, these tumors are strongly proliferative, reaching an average size ranging from 2 to 20 cm. These lesions subsequently stabilize, undergo a spontaneous slow involution and are fully regressed by 5 to 10 years of age.

Histopathological image analysis: a review.

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques.

Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery.

Background: We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420-700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery.