Congenital cataract and congenital glaucoma in Marshall-Smith syndrome

Marshall-Smith syndrome (MSS) is an ultra rare congenital condition (prevalence <1/1.000.000) caused by de novo mutations involving the gene nuclear factor I/X. It is characterized by increased bone age, respiratory disorders, facial abnormalities and failure to thrive. We present a 22-day-old infant referred to our care centre for large bulging eyes and dysmorphism including prominent eyes, bilateral proptosis, depressed nasal bridge, anteverted nares, micrognathism, prominent forehead and hypertrichosis. Fiberoptic bronchoscopy concluded to severe laryngomalacia. On ophthalmic examination, the corneal diameter was 13.5 mm in the right eye (RE) and 14 mm in the left eye (LE). The intra-ocular pressure was 29 mmHg in the RE and 36 mmHg in the LE. Biomicroscopy showed severe corneal edema in both eyes. Corneal scarring secondary to hydrops has been noted in the LE. Bilateral total cataract precluded fundus examination. Ultrasound B-mode was unremarkable in both eyes. The patient passed away from respiratory compromise at the age of 29 days. Genetic testing has not been performed. However, facial features, the course of respiratory difficulty and ocular involvement were highly suggestive of the diagnosis of MSS

La rétinopathie de décompression oculaire: une complication rare de la trabéculectomie

Une patiente âgée de 50 ans, monophtalme de l'oeil droit nous a été adressée pour une crise aigüe de glaucome par fermeture de l'angle de l'oeil droit qui a évolué vers la chronicité malgré le traitement médical précoce. A j1 post trabéculectomie l'examen retrouve une hypotonie à 6 mmHg avec au fond d'oeil présence d'un oedème  papillaire et de multiples hémorragies pré-rétiniennes rondes dont certaines à centre blanc localisées au pôle postérieur et en moyenne périphérie, épargnant la macula. L'évolution spontanée était favorable avec  stabilisation de la pression intra-oculaire (PIO) à 12 mm Hg et nettoyage du fond de l'oeil au bout de 6  semaines. Le bilan hématologique était sans particularités. La rétinopathie de décompression oculaire est une complication rare de la trabéculectomie. Son évolution est habituellement favorable. Dans certains cas une perturbation du bilan hématologique a été incriminée. Enfin cette complication peut être prévenue en évitant les variations brutales de la PIO.Key words: Rétinopathie, décompression oculaire, trabéculectomi

Hybrid Encryption Model Based on Advanced Encryption Standard and Elliptic Curve Pseudo Random

Securing multimedia applications becomes a major challenge with the violation of the information increasing currently. In this paper, a novel method for color image encryption is proposed. The procedure of encryption is performed using cooperation between Elliptic Curve Cryptography (ECC) and the Advanced Encryption Standard (AES) with CTR (Counter) mode. In the cryptographic system, we have proposed to take advantage of the Elliptic Curve Random Generator to generate a sequence of arbitrary numbers based on the curve. The random generation step is founded on the public key sharing and a changing point G. Then, the AES-CTR is performed to these sequences using arbitrary keys for image encryption. The use of the AES alongside greatly distributed random results an interesting encryption method. Security analysis is successfully performed and our experiments prove that the suggested technique provides the basis of cryptography with more simplicity and correctness

Effect of Exogenous Fibrolytic Enzymes Supplementation or Functional Feed Additives on In Vitro Ruminal Fermentation of Chemically Pre-Treated Sunflower Heads

peer reviewedThis study aims to provide possible utilization of sunflower head byproduct (SFH) as a feedstuff by implementing chemical pretreatments (4% sodium hydroxide (SFHNaOH) or 4% urea (SFHurea) and supplementation with either exogenous fibrolytic enzymes (EFE) or functional feed additive (FFA). The experimental EFE was a complex (1:1, v/v) of two enzyme products with high activity of β-1,3-1,4-glucanase and endo-1,4-β-D-xylanase and applied at 0 (SFHout), 1, 2, 5, and 10 µL/ gdry matter, while FFA was a fermentation byproduct rich in cellulase and xylanase activities, applied at 0 (SFHout), 0.5, 1, 2, and 4 mg/g DM. SFHurea had the highest (p < 0.05) crude protein (CP) content compared to other SFH substrates. Linear enhancements (p < 0.05) in kinetics of gas production (GP), metabolizable energy (ME), organic matter digestibility (OMD) and total short-chain fatty acids (SCFAs) concentrations were observed for all SFH substrates supplemented with EFE. The SFHout had the highest (p < 0.05) potential GP, maximum rate (Rmax) of GP, ME, OMD and SCFAs. Supplementation of EFE was more pronounced than FFA in affecting the kinetic parameters of in vitro GP for all SFH substrates. SFHout supplemented with EFE seems to be the most promising substrate to enhance microbial fermentation in vitro

Deep Residual Network in Network

Deep network in network (DNIN) model is an efficient instance and an important extension of the convolutional neural network (CNN) consisting of alternating convolutional layers and pooling layers. In this model, a multilayer perceptron (MLP), a nonlinear function, is exploited to replace the linear filter for convolution. Increasing the depth of DNIN can also help improve classification accuracy while its formation becomes more difficult, learning time gets slower, and accuracy becomes saturated and then degrades. This paper presents a new deep residual network in network (DrNIN) model that represents a deeper model of DNIN. This model represents an interesting architecture for on-chip implementations on FPGAs. In fact, it can be applied to a variety of image recognition applications. This model has a homogeneous and multilength architecture with the hyperparameter “L” (“L” defines the model length). In this paper, we will apply the residual learning framework to DNIN and we will explicitly reformulate convolutional layers as residual learning functions to solve the vanishing gradient problem and facilitate and speed up the learning process. We will provide a comprehensive study showing that DrNIN models can gain accuracy from a significantly increased depth. On the CIFAR-10 dataset, we evaluate the proposed models with a depth of up to L = 5 DrMLPconv layers, 1.66x deeper than DNIN. The experimental results demonstrate the efficiency of the proposed method and its role in providing the model with a greater capacity to represent features and thus leading to better recognition performance

Hardware Implementation of an Improved Hybrid Cryptosystem for Numerical Image Encryption and Authenticity

Cryptography is the science that concerns protecting information by transforming its comprehensible form into an incomprehensible one. The conception of a robust cryptosystem is a challenge. In this paper, an improved hybrid cryptosystem for numerical image protection is presented. First, the initial secret key is generated by a secure hash function (keccak). Secondly, the plain image is encrypted through the advanced encryption standard (AES) with CTR mode. Finally, a Rivest-Shamir-Adleman (RSA) algorithm is used to secure the symmetric key transmitted over the insecure channel and owner signature. Our cryptosystem is implemented in hardware and evaluated by different tools mainly identified from the image cryptography community using numerous kinds of standard images. The experimental and analytical findings prove that our framework security gives a trade-off between robustness and performance, which can be used in several domains like medicine, military, and community privacy

FPGA Implementation of Improved Security Approach for Medical Image Encryption and Decryption

Securing medical images is a great challenge to protect medical privacy. An image encryption model founded on a complex chaos-based Pseudorandom Number Generator (PRNG) and Modified Advanced Encryption Standard (MAES) is put forward in this paper. Our work consists of the following three main points. First, we propose the use of a complex PRNG based on two different chaotic systems which are the 2D Logistic map in a complex set and Henon’s system in the key generation procedure. Second, in the MAES 128 bits, the subbytes’ operation is performed using four different S-boxes for more complexity. Third, both shift-rows’ and mix-columns’ transformations are eliminated and replaced with a random permutation method which increases the complexity. More importantly, only four rounds of encryption are performed in a loop that reduces significantly the execution time. The overall system is implemented on the Altera Cyclone III board, which is completed with an SD card interface for medical image storage and a VGA interface for image display. The HPS software runs on μClinux and is used to control the FPGA encryption-decryption algorithm and image transmission. Experimental findings prove that the propounded map used has a keyspace sufficiently large and the proposed image encryption algorithm augments the entropy of the ciphered image compared to the AES standard and reduces the complexity time by 97%. The power consumption of the system is 136.87 mw and the throughput is 1.34 Gbit/s. The proposed technique is compared to recent image cryptosystems including hardware performances and different security analysis properties, such as randomness, sensitivity, and correlation of the encrypted images and results prove that our cryptographic algorithm is faster, more efficient, and can resist any kind of attacks

Fast Oriented Anisotropic Diffusion filter

International audienceIn image and video processing the denoising process is an important step before several processing tasks. This paper presents a Faster Oriented Speckle Reducing Anisotropic Diffusion filter (FOSRAD) method to speed up the processing time and keep a higher quality of image, which can be considered as a modified version of the Oriented Speckle Reducing Anisotropic Diffusion (OSRAD) filter. The OSRAD works very well for denoising images with speckle noise. However, this filter has a powerful computational complexity and is not suitable for real time implementation. In this paper we propose a new scheme for optimizing the processing time based on look ahead decomposition technique. This method leads to dividing the processing time by two. Compared to the conventional OSRAD filter, the proposed filter has the advantage of speeding up the numerical scheme. The simulation result show that the FOSRAD filter improved the execution time by 14x compared to the original OSRAD filter. A comparison measure is given by the metrics like the mean structural similarity index and the peak signal-to-noise ratio

Automated Breast Cancer Diagnosis Based on GVF-Snake Segmentation, Wavelet Features Extraction and Fuzzy Classification

International audienceThe automatic diagnosis of breast cancer (BC) is an important, real-world medical problem. This paper proposes a design of automated detection, segmentation, and classification of breast cancer nuclei using a fuzzy logic. The first step is based on segmentation using an active contour for cell tracking and isolating of the nucleus in the cytological image. Then from this nucleus, have been extracted some textural features using the wavelet transforms to characterize image using its texture, so that malign texture can be differentiated from benign one with the assumption that tumoral texture is different from the texture of other kinds of tissues. Finally, the obtained features will be introduced as the input vector of a fuzzy C-means (FCM) clustering algorithm to classify the images into malign and benign ones. The implementation of such algorithm has been done using a methodology based on very high speed integrated circuit, hardware description language (VHDL). The design of the circuit is performed by using a CMOS 0.35 μm technology

An approach for an efficient sharing of IP as a Service in cloud FPGA

International audienc