Test method was developed radioimmunotherapy to appoint in two groups of patients infected with a uterine tumor Great conditions in tumor tissue benign and malignant Ddh teacher radioactive iodine isotope
the sera levels of luteninizing hormone were investgaited prior tq surgery in 10 postmenopaisal women with benign and 10 postmenopausal women with maliganant healthy
kinetic studies were carried out the uterine homogenate time course of the association of with LH in benign and malignant uterine
Background: Parotid gland tumors account for 80% of all salivary gland neoplasms, 20% of these are malignant, but in daily clinical practice most parotid masses are operated on before obtaining the final histological diagnosis. This clinical setting further complicates the critical point of parotid surgery, which is the management of the facial nerve. Materials and methods: 45 patients underwent parotidectomy for benign and malignant neoplasms. A complete history is collected from the patients with the duration and the site of the tumor, the facial nerve examined and its associations, a medical consultation done for opinion and management. Clinical examination with facial nerve was mandatory to avoid any mistakes that may occur. The most si
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Background: Mammary duct ectasia is defined as dilated duct larger than 2 mm in diameter seen in fibrocystic changes, ductal epithelial hyperplasia, papiloma, DCIS. US has a significant role in diagnostic breast imaging. It is most commonly used as an adjunctive test in characterizing lesions detected by other imaging modalities or by clinical examination
Objective: This study was designed to investigate differences in ultrasonographic findings between malignant and benign mammary duct ectasia.
Patients and Methods: From November 2010 to July 2011, 100 womem with mammary duct ectasia lesions depicted on sonograms were included in this study. We evaluated the ultrasonograp
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Background: Characterization of the ovarian masses preoperatively is important to inform the surgeon about the possible management strategies. MRI may be of great help in identifying malignant lesion before surgery. Diffusion Weighted Imaging (DWI) is a sensitive method for changes in proton of water mobility caused by pathological alteration of tissue cellularity, cellular membrane integrity, extracellular space perfusion, and fluid viscosity.
Objective: to study the diagnostic accuracy of DWI in differentiation between benign and malignant ovarian masses.
Type of the study:Cross-sectional study.
Methods: this study included 53with complex
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Background: Pleural effusion is a common clinical
problem.
Objective: The aim of the study was to evaluate the
diagnostic utility of Carcino embryonic antigen
(CEA), CA 15- 3, and alpha-feto protein ( AFP ) as
a tumor markers in serum and pleural effusion and
evaluate the value of combining them as a diagnostic
tools that are complementary to cytology in the
diagnosis of malignancies .
Methods: Forty patients (18 malignant and 22 benign
pleural effusion) were included in this study .The
serum and effusion levels of CEA, CA 15 – 3 and
AFP were measured using immunoradiometric assay
Results: from the 40 effusions studied 26 were
exudates and 14 were transudates. The level of
pleural effusions
People may believe that tissue of normal brain and brain with benign tumor
have the same statistical descriptive measurements that are significantly different
from the of brain with malignant tumor. Thirty brain tumor images were collected
from thirty patients with different complains (10 normal brain images, 10 images
with benign brain tumor and 10 images with malignant brain tumor). Pixel
intensities are significantly different for all three types of images and the F-test was
measured and found equal to 25.55 with p-value less than 0.0001. The means of
standard deviations and coefficients of variation showed that pixel intensities from
normal and benign tumors images are almost have the same behavior whereas the
(1)
This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.