F
Farshid Babapour Mofrad
Researcher at Islamic Azad University
Publications - 29
Citations - 132
Farshid Babapour Mofrad is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 5, co-authored 17 publications receiving 86 citations.
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Journal ArticleDOI
Magnetic Resonance Imaging-Based Target Volume Delineation in Radiation Therapy Treatment Planning for Brain Tumors Using Localized Region-Based Active Contour
Hossein Aslian,Mahdi Sadeghi,Seied Rabie Mahdavi,Farshid Babapour Mofrad,Mahdi Astarakee,Navid Khaledi,Pedram Fadavi +6 more
TL;DR: This study shows that the localized region-based algorithms can have great ability in determining the clinical target volume (CTV) and can be appropriate alternatives for manual approaches in brain cancer.
Journal ArticleDOI
Classification of Normal and Diseased Liver Shapes based on Spherical Harmonics Coefficients
Farshid Babapour Mofrad,Reza Aghaeizadeh Zoroofi,Ali Abbaspour Tehrani-Fard,Shahram Akhlaghpoor,Yoshinobu Sato +4 more
TL;DR: Results show that the proposed specific features combined with classifiers outperform existing liver-shape classification techniques that employ liver surface information in the spatial domain.
Journal ArticleDOI
Statistical construction of a Japanese male liver phantom for internal radionuclide dosimetry.
Farshid Babapour Mofrad,Reza Aghaeizadeh Zoroofi,Ali Abbaspour Tehrani-Fard,Ali Abbaspour Tehrani-Fard,Shahram Akhlaghpoor,Masatoshi Hori,Yen-Wei Chen,Yoshinobu Sato +7 more
TL;DR: The proposed technique used to create the race-specific statistical phantom maintains anatomic realism and provides the statistical parameters for application to radionuclide dosimetry.
Journal ArticleDOI
Inter-Patient Modelling of 2D Lung Variations from Chest X-Ray Imaging via Fourier Descriptors.
TL;DR: An approach for creating 2D modelling of human lungs from CXR image archives is presented and some interesting statistical parameters to analysis the left and the right lung shape are reported.
Journal ArticleDOI
Contour-based lung shape analysis in order to tuberculosis detection: modeling and feature description
TL;DR: The results show that the proposed contour-based lung shape analysis is able to explain more than 95% of total variations in both of the normal and PTB cases using only 6 and 7 principal component modes for the right and the left lungs, respectively.