Classification of magnetic resonance images from rabbit renal perfusion
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Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...
BACKGROUND AND PURPOSE: MS lesions exhibit varying degrees of axonal and myelin damage. A comprehensive description of lesion phenotypes could contribute to an improved radiologic evaluation of smoldering inflammation and remyelination processes. This stud ...
The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...
We introduce robust principal component analysis from a data matrix in which the entries of its columns have been corrupted by permutations, termed Unlabeled Principal Component Analysis (UPCA). Using algebraic geometry, we establish that UPCA is a well-de ...
Premature aging causes morphological and functional changes in the kidney, leading to chronic kidney disease (CKD). CKD is a global public health issue with far-reaching consequences, including cardio-vascular complications, increased frailty, shortened li ...
Bicaudal-C1 (Bicc1), an RNA-Binding protein, is a ciliopathy-associated protein. In development, Bicc1 is necessary for left-right axis specification. Loss of Bicc1 in mice also associates with polycystic kidney development. In human, two hereditary polycy ...
This research aimed to evaluate the clinical features and computed tomography (CT) scans associated with poor outcomes in COVID-19 patients with acute kidney injury (AKI). A total of 351 COVID-19 patients (100 AKI, 251 non-AKI) hospitalized at Imam Hossein ...
BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in m ...
We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety.The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...
State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...