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Your search keyword '"Khawwam, Ahmed A."' showing total 19 results
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19 results on '"Khawwam, Ahmed A."'

1. Aluminum-Copper alloys, Corrosion, acidic medium, alkali medium

Author

null Ahmed Abdulmunem Hussein and null Mohammed Khawwam Ahmed

Subjects
General Medicine
Abstract

This paper suggested a de-noising algorithm used in grayscale images. As long as the noisy image does not give the desired view of its features, de-noising is required. The algorithm is based on block matching and wavelet transformation. Euclidean distance for blocks similarity is exploited, which demonstrate more accurate in finding similar blocks depending on soft thresholding. Regarding wavelet transform, a combine of hard thresholding is performed for HH and LH sub-bands while soft thresholding is used in LL and HL sub-bands of the decomposed images. Three types of noise is encountered: Gaussian noise, salt & pepper noise and speckle noise. The measurements are employed to evaluate our work is MSE and PSNR and SSIM. Finally a comparison of the results shows that our method outperforms traditional wavelet using hard or soft thresholding.

Published
2023

3. Liver fibrosis detection and classification for shear wave elastography (SWE) images based on convolutional neural network (CNN).

Author

Jabbar, Zainab Sattar, Alneami, Auns Q., Salih, Sufian Munther, and Khawwam, Ahmed A.

Subjects
CONVOLUTIONAL neural networks, HEPATIC fibrosis, SHEAR waves, MACHINE learning, DEEP learning
Abstract

Chronic liver disease (CLD) is a general term that refers to a number of different hepatic disease processes that consume a significant amount of healthcare and financial resources worldwide. Cirrhosis develops when CLD progresses to permanent end-stage liver fibrosis. For the course and prognosis of liver fibrosis, early detection and intervention are crucial. Ultrasound provides a variety of advantages as one of the most commonly utilized methods for detecting liver fibers, including ease, accuracy, and resilience. However, getting subjective and consistent diagnoses is challenging since ultrasound images are inevitably influenced by device characteristics, ultrasound interactions with body tissues, operation procedures, and other uncontrollable elements. The goal of paper is to develop a new proposed liver fibrosis detection model for ultrasound shear wave elastography (SWE) images using deep learning algorithm to distinguish between normal and fibrosis tissue. This paper provides a convolutional neural network-based deep learning feature extraction algorithm for binary classification and detection of liver fibrosis. The dataset used to develop these models was locally collected from an Iraqi hospital. The results obtained revealed that the final model (CNN) was able to classify normal and abnormal liver tissue from SWE with an accuracy of 97.45%, Sensitivity 98.27%, Specificity 96.66%, Precision 96.61% and F1-score of 97.17%. This is accurate results for assist diagnosis liver fibrosis. [ABSTRACT FROM AUTHOR]

Published
2023
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8. Neural Networks in Business Applications

Author

Mohammed Khawwam Ahmed

Subjects
Artificial neural network, Computer science, business.industry, General Engineering, Artificial intelligence, business
Published
2019

9. Image De-Noising Based On Wavelet Transform and Block Matching

Author

Ahmed Abdulmunem Hussein and Mohammed Khawwam Ahmed

Subjects
Computer science, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Wavelet transform, Pattern recognition, Speckle noise, Grayscale, Thresholding, Euclidean distance, symbols.namesake, Noise, Wavelet, Gaussian noise, Computer Science::Computer Vision and Pattern Recognition, symbols, Artificial intelligence, business
Abstract

This paper suggested a de-noising algorithm used in grayscale images. As long as the noisy image does not give the desired view of its features, de-noising is required. The algorithm is based on block matching and wavelet transformation. Euclidean distance for blocks similarity is exploited, which demonstrate more accurate in finding similar blocks depending on soft thresholding. Regarding wavelet transform, a combine of hard thresholding is performed for HH and LH sub-bands while soft thresholding is used in LL and HL sub-bands of the decomposed images. Three types of noise is encountered: Gaussian noise, salt & pepper noise and speckle noise. The measurements are employed to evaluate our work is MSE and PSNR and SSIM. Finally a comparison of the results shows that our method outperforms traditional wavelet using hard or soft thresholding http://dx.doi.org/10.25130/tjps.23.2018.038

Published
2018

15. Assessment of knowledge and practice of venous thromboembolism (VTE) prophylaxis after cesarean section among gynecologists and obstetricians in Al-Najaf hospitals.

Author

Suker, Safa Emad Jawad, AL-meen, Ayad Ali Hussein, and Khawwam, Ahmed Abduisahib

Subjects
CESAREAN section, THROMBOEMBOLISM, GYNECOLOGISTS, OBSTETRICIANS, PATIENT compliance
Abstract

Venous Thromboembolism (VTE) is associated with high morbidity and mortality rates after cesarean sections. VTE is likely four-time greater following cesarean section than normal vaginal delivery. Despite a large number of published studies and the availability of well-evidenced guideline recommendations for VTE prevention, it is evident that these guidelines are poorly implemented with suboptimal use of a prophylactic thrombotic agent. The objective of our study was to assess the knowledge and practice of gynecologists and obstetricians about guidelines of VTE prophylaxis after cesarean section. An observational study included 57 gynecologists and obstetricians from all hospitals in Al-Najaf province. The study used a validated questionnaire consisting of 40 items where the correct response scored 1, giving an overall total score of 40. The total overall knowledge and practice score was calculated for participants, and the knowledge and practice levels were evaluated. Only 57 participants out of 67 completed the study giving a response rate of 85%. The mean overall score of practice and adherence was 0.51±0.09. This study showed inadequate practice towards VTE and poor adherence to prophylaxis guidelines because of many barriers, mainly the cost, poor patient adherence, and inconvenience to use guidelines in our patients. [ABSTRACT FROM AUTHOR]

Published
2021
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