background and purpose : there has been no report in which preoperative evaluation of adc for prediction of post therapeutic outcome was presented. the aim of our study was to retrospectively evaluation the use of the apparent diffusion coefficient (adc) for the prediction of malignancy and the outcome of malignant astrocytic tumors. methods: we reviewed mri of 26 male and 14 female patients wi...

Background: Despite the existence of various imaging methods, the accurate diagnosis of many neurodegenerative diseases is still controversial. The use of advanced imaging techniques, such as the diffusion weighted imaging can be help the early detection of MS and evaluation of the treatment efficacy in these patients. Materials and method: 24 MS patients with acute attack and thirty healthy s...

objectives the aim of this study was to evaluate the value of diffusion weighted imaging in diffusion weighted imaging in distinguishing between in benign and malignant breast lesion methods there were 37 female patients with 47 lesions. sixty seven female subjectd (40 mean age ) ,age ranges 17-69 , with histopathologically proven breast lesions underwent dwi of breasts with a single shot echo ...

This paper presents an adaptive digital resolution improvement method for extrapolating and recursive analog-to-digital converters (ADCs). The presented adaptively enhanced ADC (AE-ADC) digitally estimates the digital equivalent of the input signal by utilizing an adaptive digital filter (ADF). The least mean squares (LMS) algorithm also determines the coefficients of the ADF block. In this sch...

this paper presents a new method to reduce consumption power in flash adc in 65nm cmos technology. this method indicates a considerable reduction in consumption power, by removing comparators memories. the simulations used a frequency of 1 ghz, resulting in decreased consumption power by approximately 90% for different processing corners. in addition, in this paper the proposed method was desig...

Introduction: To develop different radiomic models based on radiomic features and machine learning methods to predict early intensity modulated radiation therapy (IMRT) response.   Materials and Methods: Thirty prostate patients were included. All patients underwent pre ad post-IMRT T2 weighted and apparent diffusing coefficient (ADC) magnetic resonance imagi...