Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network

Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images from one single area in the low resolution (LR) input, which limits the flexibility of models to infer various scales of details for high resolution (HR) output. Moreover, most of them train a specific model for each up-scale factor. In this paper, we propose a multi-scale super resolution (MSSR) network. Our network consists of multi-scale paths to make the HR inference, which can learn to synthesize features from different scales. This property helps reconstruct various kinds of regions in HR images. In addition, only one single model is needed for multiple up-scale factors, which is more efficient without loss of restoration quality. Experiments on four public datasets demonstrate that the proposed method achieved state-of-the-art performance with fast speed

Supercontinuum Generation in a Silica Spiral Waveguide

A low-loss silica spiral waveguide is used for demonstrating on-chip supercontinuum generation. The broadest measured spectrum spans an octave (936 – 1888 nm) at −50 dB from peak when 2.17 nJ pulses are launched

Coherent ultra-violet to near-infrared generation in silica ridge waveguides

Short duration, intense pulses of light can experience dramatic spectral broadening when propagating through lengths of optical fibre. This continuum generation process is caused by a combination of nonlinear optical effects including the formation of dispersive waves. Optical analogues of Cherenkov radiation, these waves allow a pulse to radiate power into a distant spectral region. In this work, efficient and coherent dispersive wave generation of visible to ultraviolet light is demonstrated in silica waveguides on a silicon chip. Unlike fibre broadeners, the arrays provide a wide range of emission wavelength choices on a single, compact chip. This new capability is used to simplify offset frequency measurements of a mode-locked frequency comb. The arrays can also enable mode-locked lasers to attain unprecedented tunable spectral reach for spectroscopy, bioimaging, tomography and metrology

Morphological changes of the lateral meniscus in end-stage lateral compartment osteoarthritis of the knee.

OBJECTIVE: The aim of this study was to evaluate the morphological changes of the lateral meniscus in end-stage lateral compartment osteoarthritis (OA) of the knee. METHODS: One hundred fifty-eight knee joints from 133 patients that subsequently underwent total knee joint arthroplasty from January 2008 to December 2009 were enrolled. There were 26 men and 107 women. Their ages ranged from 56 to 81 (mean 67.4 + 6.5 years). All study participants had complete obliteration of the lateral joint space identified by weight-bearing radiography. Meniscal position was assessed by measuring meniscal subluxation and meniscal height. The meniscal morphology was assessed using a modification of the whole-organ magnetic resonance imaging score (WORMS). The frequency of different meniscal morphology and their respective positions was calculated. RESULTS: The predominant type (42.4%, 53.8% and 52.5% in the anterior horn, mid-body and posterior horn, respectively) of abnormal meniscal morphology was a complete maceration/destruction or complete resection. The anterior horn of non-macerated lateral meniscus was more subluxed than that of the non-macerated medial meniscus in patients with lateral OA. CONCLUSION: This study suggests that the lateral meniscus in persons with end-stage lateral OA are mostly macerated or destroyed. Also, unlike isolated end-staged medial compartment OA, the anterior horn of the lateral meniscus in isolated end-stage lateral OA is commonly affected. Copyright 2011 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved

Hypothalamic AMPK as a Regulator of Energy Homeostasis

Activated in energy depletion conditions, AMP-activated protein kinase (AMPK) acts as a cellular energy sensor and regulator in both central nervous system and peripheral organs. Hypothalamic AMPK restores energy balance by promoting feeding behavior to increase energy intake, increasing glucose production, and reducing thermogenesis to decrease energy output. Besides energy state, many hormones have been shown to act in concert with AMPK to mediate their anorexigenic and orexigenic central effects as well as thermogenic influences. Here we explore the factors that affect hypothalamic AMPK activity and give the underlying mechanisms for the role of central AMPK in energy homeostasis together with the physiological effects of hypothalamic AMPK on energy balance restoration

Single Image Super-Resolution Using Lightweight CNN with Maxout Units

Rectified linear units (ReLU) are well-known to be helpful in obtaining faster convergence and thus higher performance for many deep-learning-based applications. However, networks with ReLU tend to perform poorly when the number of filter parameters is constrained to a small number. To overcome it, in this paper, we propose a novel network utilizing maxout units (MU), and show its effectiveness on super-resolution (SR) applications. In general, the MU has been known to make the filter sizes doubled in generating the feature maps of the same sizes in classification problems. In this paper, we first reveal that the MU can even make the filter sizes halved in restoration problems thus leading to compaction of the network sizes. To show this, our SR network is designed without increasing the filter sizes with MU, which outperforms the state of the art SR methods with a smaller number of filter parameters. To the best of our knowledge, we are the first to incorporate MU into SR applications and show promising performance results. In MU, feature maps from a previous convolutional layer are divided into two parts along channels, which are then compared element-wise and only their max values are passed to a next layer. Along with some interesting properties of MU to be analyzed, we further investigate other variants of MU and their effects. In addition, while ReLU have a trouble for learning in networks with a very small number of convolutional filter parameters, MU do not. For SR applications, our MU-based network reconstructs high-resolution images with comparable quality compared to previous deep-learning-based SR methods, with lower filter parameters.Comment: ACCV201

Journey towards tiny perceptual super-resolution

Recent works in single-image perceptual super-resolution (SR) have demonstrated unprecedented performance in generating realistic textures by means of deep convolutional networks. However, these convolutional models are excessively large and expensive, hindering their effective deployment to end devices. In this work, we propose a neural architecture search (NAS) approach that integrates NAS and generative adversarial networks (GANs) with recent advances in perceptual SR and pushes the efficiency of small perceptual SR models to facilitate on-device execution. Specifically, we search over the architectures of both the generator and the discriminator sequentially, highlighting the unique challenges and key observations of searching for an SR-optimized discriminator and comparing them with existing discriminator architectures in the literature. Our tiny perceptual SR (TPSR) models outperform SRGAN and EnhanceNet on both full-reference perceptual metric (LPIPS) and distortion metric (PSNR) while being up to 26.4 × more memory efficient and 33.6 × more compute efficient respectively

Multiple Sequential Complications After Sirolimus-Eluting Stent Implantation: Very Late Stent Thrombosis, Stent Fracture, In-Stent Restenosis, and Peri-Stent Aneurysm

A 55-year-old male patient presented with an acute myocardial infarction. A sirolimus-eluting stent (SES) was implanted in the proximal left anterior descending artery (LAD). Eight months later, there was a newly developed distal LAD lesion. An additional SES was implanted. Twenty-eight months after the index procedure of primary coronary intervention, the electrocardiogram showed ST elevation in the precordial leads and an emergency coronary angiogram showed diffuse stent thrombosis (ST) in the proximal LAD. Thirty-four months after the index procedure, coronary angiography showed a large peri-stent coronary aneurysm in the proximal LAD and focal in-stent restenosis (ISR) at the proximal edge of the distal LAD stent. On fluoroscopy, a fracture was noted in the middle part of the distal SES. A zotarolimus- eluting stent (ZES) was deployed and overlapped the restenosis and fracture sites. Forty months after the index procedure, there were no changes in the size of the aneurysm or in the other stent complications including the fracture and restenosis. At present, the patient has remained asymptomatic for eight months