Papers by Mohammed Y . Kamil
International Journal of Reconfigurable and Embedded Systems (IJRES)
Breast cancer is the leading cause of death for women worldwide. Cancer can be discovered early, ... more Breast cancer is the leading cause of death for women worldwide. Cancer can be discovered early, lowering the rate of death. Machine learning techniques are a hot field of research, and they have been shown to be helpful in cancer prediction and early detection. The primary purpose of this research is to identify which machine learning algorithms are the most successful in predicting and diagnosing breast cancer, according to five criteria: specificity, sensitivity, precision, accuracy, and F1 score. The project is finished in the Anaconda environment, which uses Python's NumPy and SciPy numerical and scientific libraries as well as matplotlib and Pandas. In this study, the Wisconsin diagnostic breast cancer dataset was used to evaluate eleven machine learning classifiers: decision tree, quadratic discriminant analysis, AdaBoost, Bagging meta estimator, Extra randomized trees, Gaussian process classifier, Ridge, Gaussian nave Bayes, k-Nearest neighbors, multilayer perceptron, an...
Morphological Gradient in Brain Magnetic Resonance Imaging Based on Intuitionistic Fuzzy Approach / presentation
Morphological gradient in brain magnetic resonance imaging based on intuitionistic fuzzy approach
2016 Al-Sadeq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA), 2016
The morphological operations commonly used image gradient for gray level images in medical images... more The morphological operations commonly used image gradient for gray level images in medical images. Medical images are usually poorly illuminated and several edges are not visible accurately. This paper have used the morphological gradient (erosion-dilation computation) of the fuzzy mathematical morphology based on Hamacher t-norm and t-conorm, and comparison with classical morphological gradient. The results of evaluation shown clearly of the effectiveness of the fuzzy morphological approach in brain magnetic resonance imaging compared to classical morphological based on statistical image quality.
Brain tumor is serious and life-threatening because it found in a specific area inside the skull.... more Brain tumor is serious and life-threatening because it found in a specific area inside the skull. Computed Tomography (CT scan) which be directed into intracranial hole products a complete image of the brain. That image is visually examined by the expert radiologist for diagnosis of brain tumor. This study provides a computer aided method for calculating the area of the tumor with high accuracy is better than technique within CT scan device. This method determines the extracted the position and shape tumor based on morphological operations (dilation and erosion), enhancement filters and thresholding. Then, automatically calculate of tumor area for the area of interest.
International Journal of Intelligent Engineering and Systems, 2021
The task of segmenting breast tumours in mammograms is very difficult, as its difficulty lies in ... more The task of segmenting breast tumours in mammograms is very difficult, as its difficulty lies in the lack of contrast between the tumour and the surrounding breast tissue, especially when dealing with small tumours that are not clear boundaries and hidden under the tissues. Segmentation algorithms often lose the path of tumor boundaries in an attempt to determine the position of them. Active contours are used widely for segmentation as a high-level technology for boundary recognition. The main aim to create a clear contrast between the tumour and the normal breast region. In this study, two approaches to active contour are applied: snakes and level sets. The proposed methods were applied to all abnormal mammogram images taken from mini-MIAS database. The first approach showed a weakness in the segmentation of this type of image, while the other approach was able to segment all the mammogram's tumours. The Chan-Vese method was the most superior of all the active contour segmentation methods. The proposed models were tested in two ways, the first is statistical the best result was for the Chan-Vese method and it came as follows (90%,95% 98%, 97%, 97%) for Jaccard, Dice, PF-Score, Precision, and Sensitivity respectively. And the other is based on the segmented region's characteristics, Chan-Vese was able to accurately determine the location and shape of the tumor. The proposed Chan-Vese approach is appropriate in adopting computer assisted detection systems to predict tumor boundaries and locations in mammography for its reliability and superior performance over other algorithms.
Indonesian Journal of Electrical Engineering and Computer Science, 2021
The accurate segmentation of tumours is a crucial stage of diagnosis and treatment, reducing the ... more The accurate segmentation of tumours is a crucial stage of diagnosis and treatment, reducing the damage that breast cancer causes, which is the most common type of cancer among women, especially after the age of forty. The task of segmenting breast tumours in mammograms is very difficult, as its difficulty lies in the lack of contrast between the tumour and the surrounding breast tissue, especially when dealing with small tumours that are not clear boundaries and hidden under the tissues. As algorithms often lose an automatic path toward the boundaries of the tumour at try to determine the site of this type of tumour. The study aims to create a clear contrast between the tumour and the healthy breast area. For this purpose, we used a Gaussian filter as a pre-processing as it works to intensify the low-frequency components while reducing the high-frequency components as the breast structure is enhanced and noise suppression. Then, CLAHE was used to improve the contrast of the image, ...
Melanoma Skin Cancer Detection Based on ABCD Rule
2019 First International Conference of Computer and Applied Sciences (CAS), 2019
Skin cancer is the most common cancers in the last years, especially in the human body; the Melan... more Skin cancer is the most common cancers in the last years, especially in the human body; the Melanoma is the most destructive type of skin lesions. Detect cancer is important at the initial stage, but only an expert dermatologist can detect which one is non-melanoma and melanoma. Computer-aided diagnosis (CADs) application to skin cancer is relatively understudied. The purpose of this paper is the automated detection of Melanoma via digital image processing. In this project, the algorithm consists of automatic ABCD (asymmetry, border irregularity, colour, and dermoscopic structure) rule of dermoscopy lesions images is implemented. Before that, we use hair removal as a pre-processing step which is based on morphological filter and thresholding. Finally, the lesions are classified as either melanoma or benign. The used dataset is containing 200 dermoscopic images, where 120 are benign lesions and 80 malignant melanomas. The proposed method shows an accuracy of 93.2%, 92.59% specificity, and 90.15% sensitivity.
International Journal of Electrical and Computer Engineering (IJECE), 2021
COVID-19 disease has rapidly spread all over the world at the beginning of this year. The hospita... more COVID-19 disease has rapidly spread all over the world at the beginning of this year. The hospitals' reports have told that low sensitivity of RT-PCR tests in the infection early stage. At which point, a rapid and accurate diagnostic technique, is needed to detect the Covid-19. CT has been demonstrated to be a successful tool in the diagnosis of disease. A deep learning framework can be developed to aid in evaluating CT exams to provide diagnosis, thus saving time for disease control. In this work, a deep learning model was modified to Covid-19 detection via features extraction from chest X-ray and CT images. Initially, many transfer-learning models have applied and comparison it, then a VGG-19 model was tuned to get the best results that can be adopted in the disease diagnosis. Diagnostic performance was assessed for all models used via the dataset that included 1000 images. The VGG-19 model achieved the highest accuracy of 99%, sensitivity of 97.4%, and specificity of 99.4%. T...
Mammography Image Segmentation Based on Fuzzy Morphological Operations
2018 1st Annual International Conference on Information and Sciences (AiCIS), 2018
Breast cancer is one of the most dangerous health problems women suffer from all over the world. ... more Breast cancer is one of the most dangerous health problems women suffer from all over the world. The key to improve diagnosis of breast cancer is the early detection of such a disease, so one of the most credible methods is the mammography for early detection of the breast cancer. In this study, segmentation techniques been proposed in order to analyze and segment the breast tumors, these technologies based on; Classic Morphology and Fuzzy Morphology, and a comparison between them. The proposed methods were tested using the database of mini -MIAS, which contained 322 images; after comparison the statistical results, it shown that diagnosis of tumor boundary with Fuzzy Morphology was high accuracy. also, it given the results better than Classic Morphology.
Texture Analysis of Breast Cancer via LBP, HOG, and GLCM techniques
IOP Conference Series: Materials Science and Engineering, 2020
Breast cancer is a prevailing reason for death, and it is a particular kind of tumor that is popu... more Breast cancer is a prevailing reason for death, and it is a particular kind of tumor that is popular among ladies across the world. Till presently, there is no efficient method to stop the appearance of the breast tumor. Accordingly, early detection is the first stage in the diagnosis of breast tumors and reduces mortality. Screening Mammography is the most effective technique for early detection of breast tumors. Great experience and large practices of specialists are wanted when examining breast tissue in a mammogram. In this work, feature extraction techniques are offered as methods to decrease false-positive that occur in breast diagnosis. Mini-MIAS database used to evaluate these approaches. LBP, HOG, and GLCM are feature extraction techniques used for analyzing mass tissue and extract features from the ROI. Contrast, energy, correlation, and homogeneity are used as features properties. These features utilized as the input to the different classifiers which achieved the best re...
IOP Conference Series: Materials Science and Engineering, 2020
The second foremost reason for dying ladies all across the world is breast cancer. The possibilit... more The second foremost reason for dying ladies all across the world is breast cancer. The possibilities of survival can be raises when cancer detects earlier; therefore, the mortality reduction. The radiologist used mammograms to recognize breast tumors at an early level. Since the mammograms have little contrast, hence, it is unclear to the radiologist to distinguish small tumors. A computer-aided detection system contributes to explaining mammograms and helps the radiologist to indicate the appearance of breast mass and discriminate among normal and abnormal tissue. In this research, we introduce a histogram of oriented gradients as a method of feature extraction and identify mass regions in mammograms. The features extraction from this method classified by a support vector machine. To improve the diagnosis ability, contrast limited adaptive histogram equalization pre-processing system is utilized. Mini-MIAS database used to estimate this approach. The top accuracy, sensitivity, and ...
Journal of Physics: Conference Series, 2020
Breast cancer is one of the types of cancer that threatens the lives of women in their 40s. Based... more Breast cancer is one of the types of cancer that threatens the lives of women in their 40s. Based on the statistic reports, death-rate can be reduced by early detection of breast cancer. Breast cancer detection in early stages and lessen false positives in radiologist diagnosis can be achieved by combination Computer-Aided Diagnosis (CAD) with mammography. In this work, we offer a feature extraction technique as a method to lessen false-positive in breast mass recognition. Distinguishing explicit breast masses and ordinary tissue is the objective we strive to achieve. The mini-MIAS database of mammograms was used in this paper. LBP is the method that was used to extract features from the ROI. Comprehensive detection of this method can be developed, by taking the ROI inside the ground truth, which is automatically identified in the mini-MIAS and classifier majority voting. Better sensitivity, specificity, and accuracy are observed with a logistic regression classifier.
Analysis of Tissue Abnormality in Mammography Images Using Gray Level Co-occurrence Matrix Method
Journal of Physics: Conference Series, 2020
One of the dangerous diseases is breast cancer, which threatens women and men to the same extent.... more One of the dangerous diseases is breast cancer, which threatens women and men to the same extent. But women are more affected by this disease. Computer-Aided Diagnosis (CAD) is the optimal method for the early detection of breast cancer. It can reduce the false positives in radiologist diagnosis, which leads to reduce the death-rate. This paper presents a feature extraction technique with mammography images to breast mass recognition. Then, distinguishing normal tissue and abnormal breast masses. The mini-MIAS database of mammograms was used in this paper. Gray Level Co-occurrence Matrix is the method that was used to extract features from the region of interest. The best sensitivity, specificity, and accuracy are observed with a k nearest neighbor classifier.
International Journal of Electrical and Computer Engineering (IJECE), 2020
The most prominent reason for the death of women all over the world is breast cancer. Early detec... more The most prominent reason for the death of women all over the world is breast cancer. Early detection of cancer helps to lower the death rate. Mammography scans determine breast tumors in the first stage. As the mammograms have slight contrast, thus, it is a blur to the radiologist to recognize micro growths. A computer-aided diagnostic system is a powerful tool for understanding mammograms. Also, the specialist helps determine the presence of the breast lesion and distinguish between the normal area and the mass. In this paper, the Gabor filter is presented as a key step in building a diagnostic system. It is considered a sufficient method to extract the features. That helps us to avoid tumor classification difficulties and false-positive reduction. The linear support vector machine technique is used in this system for results classification. To improve the results, adaptive histogram equalization pre-processing procedure is employed. Mini-MIAS database utilized to evaluate this me...
Al-Mustansiriyah Journal of Science, 2018
The segmentation performance is topic to suitable initialization and best configuration of superv... more The segmentation performance is topic to suitable initialization and best configuration of supervisory parameters. In medical image segmentation, the segmentation is very important when the diagnosing becomes very hard in medical images which are not properly illuminated. This paper proposes segmentation of brain tumour image of MRI images based on spatial fuzzy clustering and level set algorithm. After performance evaluation of the proposed algorithm was carried on brain tumour images, the results showed confirm its effectiveness for medical image segmentation, where the brain tumour is detected properly.
Al-Mustansiriyah Journal of Science, 2019
Breast cancer is the most widespread cancer that influences ladies about the world. Early recogni... more Breast cancer is the most widespread cancer that influences ladies about the world. Early recognition of breast tumor is a standout amongst the hugest variables influencing the probability of recuperation from the illness. Hence, mammography remains the most precise and best device for distinguishing breast malignancy. This paper presents a method for segment the boundary of breast masses regions in mammograms via a proposed algorithm based on fuzzy set techniques. Firstly, it was used data set (mini-MIAS) for evaluate algorithm. it was preprocessing the data set to remove noise and propose a fuzzy set by using fuzzy inference system by generated two input parameters (employs image gradient), then used thresholding filter. Then it was evaluated this proposed method, qualitative and quantitative results were obtained to demonstrate the efficiency of this method and confirm the possibility of its use in improving the diagnosis.
International Journal of Advanced Pervasive and Ubiquitous Computing, 2019
Breast cancer is one of most dangerous diseases and more common in women. The early detection of ... more Breast cancer is one of most dangerous diseases and more common in women. The early detection of cancer is one of the most key factors for possible cure. There are numerous methods of diagnosis amongst which: clinical examination, sonar and mammography, which is the best and more effective in detecting breast cancer. Detection of breast tumors is difficult because of the weak illumination in the image and the overlap between regions. Segmentation is one the crucial steps in locating the tumors, which is an important method of diagnosis of the computer. In this study, segmentation techniques are proposed based on; classic morphology and fuzzy morphology, and a comparison between them. The proposed methods were tested using the database of mini -MIAS, which contains 322 images. After the comparison the statistical results, it shows, the detection of tumor boundary with fuzzy morphology give the higher accuracy than the results in classic morphology. The accuracy is 60.69%, 58.61% resp...
International Journal of Intelligent Engineering and Systems, 2019
Breast Cancer is one of the common and dangerous among women at the age of forty, so it is better... more Breast Cancer is one of the common and dangerous among women at the age of forty, so it is better for woman to have mammography testing as a significant step for the early detection of breast cancer and is diagnosis for treatment; There is an important need to an algorithm is used to determine the boundaries of the tumor in a finite accuracy. In this work, two algorithms were built depending on clustering approach as segmentation method. In the first algorithm has employed (K-mean) method, whilst in the second algorithm has employed fuzzy c-mean method (FCM). In both, the lazy snapping algorithm was used as an additional step to improve the segmentation performance of the detection of abnormal area. The proposed methods have been tested using mini-MIAS database, after assessment the results obtained. it indicates the accuracy of segmentation first algorithm, are 91.18% and accuracy of second algorithm is 94.12%. from results, it concludes that the proposed second algorithm is capable of estimate breast abnormal region boundary at high accuracy because it used fuzzy logic technique.
3D Image Reconstruction for Wooden Object based on Laser Triangulation Technique
This paper presents a way of constructing a system capable of determine the dimensions and recons... more This paper presents a way of constructing a system capable of determine the dimensions and reconstructs a 3D shape for symmetric wooden object based on laser triangulation technique to find the depth of object. The results show that the proposed algorithm for reconstruct 3D surface of object is accurate and get rid of the difficulties in reconstruction symmetric wooden object using captured images by photo detect. Also, the images efficiency is less when the angle between the photo detector and the illumination source is very small.
Exact solution for simple pendulum motion by using Maclaurin series
Simple pendulum is nonlinear physics systems that represent his equation at a differential equati... more Simple pendulum is nonlinear physics systems that represent his equation at a differential equation of the second degree. We studied the motion of the pendulum analytical and derive the equation of motion when large amplitude using Mcleoran series then build a computational program to determine the value of period time for different amplitudes and tested for several values. The results show that the effect powers for series vanished almost at powers more than (4), make us an approximation of the series to fourth term, and also test the effect of large amplitude angles on the period time which showed a deviation clearly in the value (Tlr0) to the first power values. In addition, we got the mathematical exact equation of the simple pendulum motion at large amplitudes.
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Papers by Mohammed Y . Kamil