26 citations · 51 across the 5 of their papers we have counts for
3 papers · 1 filter
Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma
Ahmad Chaddad, Saima Rathore, Mingli Zhang +2
This paper proposes to use deep radiomic features (DRFs) from a convolutional neural network (CNN) to model fine-grained texture signatures in the radiomic analysis of recurrent gl…
Prediction of overall survival and molecular markers in gliomas via analysis of digital pathology images using deep learning
Saima Rathore, Muhammad Aksam Iftikhar, Zissimos Mourelatos
Cancer histology reveals disease progression and associated molecular processes, and contains rich phenotypic information that is predictive of outcome. In this paper, we developed…
Radiopathomics: Integration of radiographic and histologic characteristics for prognostication in glioblastoma
Saima Rathore, Muhammad A. Iftikhar, Metin N. Gurcan +1
Both radiographic (Rad) imaging, such as multi-parametric magnetic resonance imaging, and digital pathology (Path) images captured from tissue samples are currently acquired as sta…