Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentation method of gray level CT images. The segmentation process is performed by using the Fuzzy C-Means (FCM) clustering method to detect and segment kidney CT images for the kidney region. The propose method is started with pre-processing of the kidney CT image to separate the kidney from the abdomen CT and to enhance its contrast and removing the undesired noise in order to make the image suitable for further processing. The resulted segmented CT images, then used to extract the tumor region from kidney image defining the tumor volume (size) is not an easy task, because the 2D tumor shape in the CT slices are not regular. To overcome the problem of calculating the area of the convex shape of the hull of the tumor in each slice, we have used the Frustum model for the fragmented data.
Background: The use of antiepileptic drugs (AEDs) during pregnancy warrants several side effects and also deleterious effects on fetal development, the antiepileptic drugs have potential to affect the fetal development throughout the pregnancy although, the majority of infants born to epileptic pregnant women are normal but more expose to the malformations. Aim: The present study aimed to investigate the effect of carbamazepine drug on the kidney development at day 7 postnatally in the Albino Rat (Rattus rattus) as a mammalian model. Material & Methods: 20 healthy pregnant female rats were divided into two groups, 10 pregnant rats in each group; group one served as control group administrated distal water while group two used as experimenta
... Show MoreThe aim of this research was to analyze the financial reporting requirements of segmental information that stipulated by the Iraqi accounting rules, investigating the extent of it compliance with the requirements of the International Financial Reporting Standard No.8 (IFRS 8) and the Statement of Financial Standards No.131 (SFAS 131). Also the research aimed to identify the segmental disclosure practices in listed corporations on Iraq Stock Exchange (ISX), basing on a hypotheses said that “the insufficient of Iraqi financial reporting requirements of segmental information affect<
... Show MoreThe statistical distributions study aimed to obtain on best descriptions of variable sets phenomena, which each of them got one behavior of that distributions . The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods like greatest ability, minimum squares method and Mixing method (suggested method).
The research
... Show MoreThe research tagged (the image of the soldier in contemporary Iraqi painting) dealt with the concept of the image as one of the basic concepts in the creative achievement, whether it is in the field of art, literature or beauty. Therefore, the concept of the image expanded to express the various aspects of human creativity, including the field of painting. To know the image of the soldier in contemporary Iraqi painting, the research included four chapters. The first chapter focused on the methodological framework of the research, while the second chapter included three sections. The first topic dealt with the philosophical and artistic concept of the image. The second topic was concerned with the representations of the soldier's image in
... Show MoreImage fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
... Show MoreImage compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreThe objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.
The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed sign