Related papers: Multi-channel coronal hole detection with convolut…
The retinal vascular condition is a reliable biomarker of several ophthalmologic and cardiovascular diseases, so automatic vessel segmentation may be crucial to diagnose and monitor them. In this paper, we propose a novel method that…
The automatic analysis of ultrasound sequences can substantially improve the efficiency of clinical diagnosis. In this work we present our attempt to automate the challenging task of measuring the vascular diameter of the fetal abdominal…
The present paper discusses results of a statistical study of the characteristics of coronal hole (CH) rotation in order to find connections to the internal rotation of the Sun. The goal is to measure CH rotation rates and study their…
Coronal bright points (CBP) are ubiquitous small brightenings in the solar corona associated with small magnetic bipoles. We derive the solar differential rotation profile by tracing the motions of CBPs detected by the Atmospheric Imaging…
In digital pathology, cell detection and classification are often prerequisites to quantify cell abundance and explore tissue spatial heterogeneity. However, these tasks are particularly challenging for multiplex immunohistochemistry (mIHC)…
With the observations from the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager (HMI) aboard the \emph{Solar Dynamics Observatory}, we investigate the coronal hole boundaries (CHBs) of an equatorial extension of…
The spatial-temporal evolution of coronal plasma parameters of the solar outer atmosphere at global scales, derived from solar full-disk imaging spectroscopic observation in the extreme-ultraviolet band, is critical for understanding and…
This paper shows the application of autonomous Crater Detection using the U-Net, a Fully-Convolutional Neural Network, on Ceres. The U-Net is trained on optical images of the Moon Global Morphology Mosaic based on data collected by the LRO…
Coronal holes are the source regions of the fast solar wind, which fills most of the solar system volume near the cycle minimum. Removing stray light from extreme ultraviolet (EUV) images of the Sun's corona is of high astrophysical…
Solar pores possess irregular and evolving boundaries that are often far from the ideal circular flux tubes assumed in many magnetohydrodynamic (MHD) oscillation models. To tackle this irregularity in a consistent way for wave analysis, we…
Coronal seismology is a diagnostic tool used in solar physics for measuring parameters that are otherwise hard to measure; of these parameters, magnetic field values are arguably the most important. The parameters are inferred by combining…
The shape and dynamics of coronal mass ejections (CMEs) vary significantly based on the instrument and wavelength used. This has led to significant debate about the proper definitions of CME/shock fronts, pile-up/compression regions, and…
Studying coronal mass ejections (CMEs) in coronagraph data can be challenging due to their diffuse structure and transient nature, compounded by the variations in their dynamics, morphology, and frequency of occurrence. The large amounts of…
A convolution model which accounts for neural activity dynamics in the primary visual cortex is derived and used to detect visually salient contours in images. Image inputs to the model are modulated by long-range horizontal connections,…
The fast growing deep learning technologies have become the main solution of many machine learning problems for medical image analysis. Deep convolution neural networks (CNNs), as one of the most important branch of the deep learning…
Coronal lines are a powerful, yet poorly understood, tool to identify and characterize Active Galactic Nuclei (AGNs). There have been few large scale surveys of coronal lines in the general galaxy population in the literature so far. Using…
A plethora of coronal models, from empirical to more complex magnetohydrodynamic (MHD) ones, are being used for reconstructing the coronal magnetic field topology and estimating the open magnetic flux. However, no individual solution fully…
We develop an algorithm which exceeds the performance of board certified cardiologists in detecting a wide range of heart arrhythmias from electrocardiograms recorded with a single-lead wearable monitor. We build a dataset with more than…
Planning of radiotherapy involves accurate segmentation of a large number of organs at risk, i.e. organs for which irradiation doses should be minimized to avoid important side effects of the therapy. We propose a deep learning method for…
Among several heliophysical and geophysical quantities, the accurate evolution of the solar irradiance is fundamental to forecast the evolution of the neutral and ionized components of the Earth's atmosphere.We developed an artificial…