Cancer constitutes a serious disease and a major health problem in worldwide, a lot of people were infected with this dangerous disease, Therefore, there must be attention to this disease through diagnosis and prevention there. In this study, we determined the relationship between the Cancer and the concentration of trace elements by comparing the concentration trace elements for infected and non-infected people. The trace elements concentrations to nails are one of the diagnostic criteria that easily to detect and dated this disease without any harm to the patient. Eight nails samples were collected from cancer-infected and eight samples from non-infected of the relatives of first-degree. All samples were measured by the concentrations

Background: Nasopharyngeal carcinoma (NPC) is one of the most challenging tumors because of their relative inaccessibility and that their spread can occur without significant symptoms with few signs, but Radiotherapy (RT) has a role in treatment of it.
Objectives: To show that RT is still the modality of choice in the treatment of NPC, to study modes of presentations, commonest histopathological types and their percentages, to show differences in the sensitivities of these types to RT and to find out a 5 year survival rate(5YSR) and its relation with lymph node involvement.
Methods: This is a retrospective study of 44 patients with NPC who were treated with routine RT from 1988-2007 at the institute of radiology and nuclear medicin

Image registration plays a significant role in the medical image processing field. This paper proposes a development on the accuracy and performance of the Speeded-Up Robust Surf (SURF) algorithm to create Extended Field of View (EFoV) Ultrasound (US) images through applying different matching measures. These measures include Euclidean distance, cityblock distance, variation, and correlation in the matching stage that was built in the SURF algorithm. The US image registration (fusion) was implemented depending on the control points obtained from the used matching measures. The matched points with higher frequency algorithm were proposed in this work to perform and enhance the EFoV for the US images, since the maximum accurate matching po

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

The typical test for diagnosis of severe acute respiratory syndrome coronavirus 2 is a reverse transcription-polymerase chain reaction (RT-PCR) technique, but the chest CT scan might play a complementary role at the first detection of Coronavirus Disease 2019 (COVID-19) pneumonia. Objectives: To determine the sensitivity of CT scan on patients with COVID-19 in Al-Najaf, Iraq, and to compare the accuracy of CT scan with that of RT-PCR technique. Material and Method: This is a prospective study. The patients suspicious of having COVID-19 infection and respiratory symptoms were registered. All patients were diagnosed by RT-PCR and chest CT. Diagnostic performance of CT was intended using RT-PCR as the reference sta

In this study used three methods such as Williamson-hall, size-strain Plot, and Halder-Wagner to analysis x-ray diffraction lines to determine the crystallite size and the lattice strain of the nickel oxide nanoparticles and then compare the results of these methods with two other methods. The results were calculated for each of these methods to the crystallite size are (0.42554) nm, (1.04462) nm, and (3.60880) nm, and lattice strain are (0.56603), (1.11978), and (0.64606) respectively were compared with the result of Scherrer method (0.29598) nm,(0.34245),and the Modified Scherrer (0.97497). The difference in calculated results Observed for each of these methods in this study.

Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol