Deep Learning Techniques For Skull Stripping of Brain MR Images
The conjugate coefficient optimal is the very establishment of a variety of conjugate gradient methods. This paper proposes a new class coefficient of conjugate gradient (CG) methods for impulse noise removal, which is based on the quadratic model. Our proposed method ensures descent independent of the accuracy of the line search and it is globally convergent under some conditions, Numerical experiments are also presented for the impulse noise removal in images.
Background: Brain abscess is collection of pus in the brain parrynchima surrounded by a true capsule. Usually diagnosed by CT & MRI, & treated surgically by drainage by burr hole, or excision.
Objective: evaluate our work with brain abscess.
Patient& method: 74 Patients collected in the specialized surgical hospital neuro-surgical department, from Jan. 1995 till Jan. 2005 treated surgically, all cases fully evaluated clinically & radiologically & then evaluation of the surgical procedure.
Results: there is a slight male predominance & prevalence more in the 1st 2decades of life mostly in children with cong. heart disease, headache was the most common presenting feature, with other signs of infection diagn
Background: Frovatriptan succinate (FVT) is an effective medication used to treat migraines; however, available oral formulations suffer from low permeability; accordingly, several formulations of FVT were prepared. Objective: Prepare, optimize, and evaluate FVT-BE formulation to develop enhanced intranasal binary nano-ethosome gel. Methods: Binary ethosomes were prepared using different concentrations of phospholipid PLH90, ethanol, propylene glycol, and cholesterol by thin film hydration and characterized by particle size, zeta potential, and entrapment efficiency. Furthermore, in-vitro, in-vivo, ex-vivo, pharmacokinetics, and histopathological studies were done. Results: Regarding FVT-loaded BE, formula (F9) demonstrated the best paramet
... Show MoreContours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.
Texture synthesis using genetic algorithms is one way; proposed in the previous research, to synthesis texture in a fast and easy way. In genetic texture synthesis algorithms ,the chromosome consist of random blocks selected manually by the user .However ,this method of selection is highly dependent on the experience of user .Hence, wrong selection of blocks will greatly affect the synthesized texture result. In this paper a new method is suggested for selecting the blocks automatically without the participation of user .The results show that this method of selection eliminates some blending caused from the previous manual method of selection.
Ultrasound imaging is often preferred over other medical imaging modalities because it is non-invasive, non-ionizing, and low-cost. However, the main weakness of medical ultrasound image is the poor quality of images, due to presence of speckle noise and blurring. Speckle is characteristic phenomenon in ultrasound images, which can be described as random multiplicative noise that occurrence is often undesirable, since it affects the tasks of human interpretation and diagnosis. Blurring is a form of bandwidth reduction of an ideal image owing to the imperfect image formation process. Image denoising involves processing of the image data to produce a visually high quality image. The denoising algorithms may be classified into two categorie
... Show MorePrinted Arabic document image retrieval is a very important and needed system for many companies, governments and various users. In this paper, a printed Arabic document images retrieval system based on spotting the header words of official Arabic documents is proposed. The proposed system uses an efficient segmentation, preprocessing methods and an accurate proposed feature extraction method in order to prepare the document for classification process. Besides that, Support Vector Machine (SVM) is used for classification. The experiments show the system achieved best results of accuracy that is 96.8% by using polynomial kernel of SVM classifier.
Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,
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