Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor the removal of brain sections can be addressed in the subsequent steps, resulting in an unfixed mistake during further analysis. Therefore, accurate skull stripping is necessary for neuroimaging diagnostic systems. This paper proposes a system based on deep learning and Image processing, an innovative method for converting a pre-trained model into another type of pre-trainer using pre-processing operations and the CLAHE filter as a critical phase. The global IBSR data set was used as a test and training set. For the system's efficacy, work was performed based on the principle of three dimensions and three sections of MR images and two-dimensional images, and the results were 99.9% accurate.
Background: Ultrasound provides a powerful tool for assessing early pregnancy and detecting pregnancy failure at first trimester and promoting rapid effective management. Several criteria have been established to predict the pregnancy outcome particularly in symptomatic women .
Aim: To evaluate asymptomatic women at the first trimester of pregnancy , to assess the efficacy of certain ratios as mid sac diameter (MSD) / yolk sac ratio & crown rump length (CRL)/mid sac diameter (as indicator of early first trimester oligohydramnios) in predicting poor 1st trimester outcome
Type of the study: A cross-s
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Research Summary
The research revolves around the collection of pending hadiths on Abdullah bin Amr bin Al-Aas, may God be pleased with them, and it is required in these hadiths that they be among those in which there is no room for diligence, such as telling about unseen matters, signs of the Hour, or a statement of virtue and reward for obedience, or punishment for disobedience.
The research consists of an introduction, two topics, and a conclusion of the first topic in the translation of Abdullah bin Amr bin Al-Aas, and the second topic, the pending hadiths of Abdullah bin Amr bin Al-Aas, may God be pleased with them, in which there is no room for diligence in collecting and studying
At the end of this rese
DAIRMD Professor Hayder R. Al-Hamamy, **Professor Adil A. Noaimi, **Dr. Ihsan A. Al-Turfy, IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2015
The educational service industry is one of the most negatively affected industries by the spread of the COVID-19 pandemic. Government agencies have taken many measures to slow its spread, and then restrict movement and gatherings and stop recreational activities. Furthermore, the repercussions of the curfew had a significant impact due to the interruption in actual attendance for students and employees, and the severity of the Covid-19 crisis and its (economic, social, security, humanitarian and behavioral) effects on all societies and work sectors is no secret to anyone. Iraq, like other countries, was also affected by the negative impact of Covid-19 pandemic in all fields of institutional work, especially public fields, and specifically t
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This study was conducted to detect the relationship between organic content in the sediment of Rivers Tigris and Diyala, at two locations south of Baghdad, with some environmental factors and the benthic invertebrates and values of diversity indices. Monthly samples collected from the area for the period November 2007 to October 2008. Results showed differences in the physical and chemical characteristics of the two sites, Where the annual average in Tigris and Diyala were respectively for: water temperature (19, 20) C°, pH (8, 8), dissolved oxygen (4, 8) mg / l , Biochemical oxygen Demand BOD5 (3,44 ) mg/l, TDS (632,1585) mg / l, TSS (42, 44) mg / l, turbidity (28,74) NTU, and total hardness as CaCO3 (485,823) mg / l ,Sulfat
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