Search Results for author: Saima Rathore

Found 4 papers, 0 papers with code

Deep radiomic signature with immune cell markers predicts the survival of glioma patients

no code implementations9 Jun 2022 Ahmad Chaddad, Paul Daniel Mingli Zhang, Saima Rathore, Paul Sargos, Christian Desrosiers, Tamim Niazi

These results demonstrate the usefulness of proposed DRFs as non-invasive biomarker for predicting treatment response in patients with brain tumors.

Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma

no code implementations15 Nov 2019 Ahmad Chaddad, Saima Rathore, Mingli Zhang, Christian Desrosiers, Tamim Niazi

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 glioblastoma (rGBM).

General Classification

Prediction of overall survival and molecular markers in gliomas via analysis of digital pathology images using deep learning

no code implementations19 Sep 2019 Saima Rathore, Muhammad Aksam Iftikhar, Zissimos Mourelatos

In this paper, we developed a computational approach based on deep learning to predict the overall survival and molecular subtypes of glioma patients from microscopic images of tissue biopsies, reflecting measures of microvascular proliferation, mitotic activity, nuclear atypia, and the presence of necrosis.

Survival Prediction whole slide images

Radiopathomics: Integration of radiographic and histologic characteristics for prognostication in glioblastoma

no code implementations17 Sep 2019 Saima Rathore, Muhammad A. Iftikhar, Metin N. Gurcan, Zissimos Mourelatos

An extensive set of engineered features was extracted from delineated tumor regions in Rad images, comprising T1, T1-Gd, T2, T2-FLAIR, and 100 random patches extracted from Path images.

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