Characterization of Breast Tumors from MR Images Using Radiomics and Machine Learning Approaches

Prostate cancer radiomics: A study on IMRT response prediction based on MR image features and machine learning approaches

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...

Comparison of state-of-the-art atlas-based bone segmentation approaches from brain MR images for MR-only radiation planning and PET/MR attenuation correction

Introduction: Magnetic Resonance (MR) imaging has emerged as a valuable tool in radiation treatment (RT) planning as well as Positron Emission Tomography (PET) imaging owing to its superior soft-tissue contrast. Due to the fact that there is no direct transformation from voxel intensity in MR images into electron density, itchr('39')s crucial to generate a pseudo-CT (Computed Tomography) image ...

the relationship between using language learning strategies, learners’ optimism, educational status, duration of learning and demotivation

with the growth of more humanistic approaches towards teaching foreign languages, more emphasis has been put on learners’ feelings, emotions and individual differences. one of the issues in teaching and learning english as a foreign language is demotivation. the purpose of this study was to investigate the relationship between the components of language learning strategies, optimism, duration o...

Prostate cancer Radiomics using multiparametric MR imaging

Automatic Brain Tumors Segmentation of MR Images using Fluid Vector Flow and Support Vector Machine

Manual segmentation of brain tumors by medical practitioners is a time consuming task and has inability to assist in accurate diagnosis. Several automatic methods have been developed to overcome these issues. But Automatic MRI (Magnetic Resonance Imaging) brain tumor segmentation is a complicated task due to the variance and intricacy of tumors; to over by this problem we have developed a new m...