7 citations · 15 across the 34 of their papers we have counts for
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Robust Multicenter CT Radiogenomics for Dual EGFR and KRAS Prediction in Lung Cancer with Stability-Aware Modeling and SHAP Interpretation
Somayeh Sadat Mehrnia, Fatemeh Razavi, Helia Abedini +3
Accurate identification of EGFR and KRAS mutations is essential for precision therapy in non-small cell lung cancer (NSCLC), but tissue genotyping is invasive and may not capture t…
Renal Blood Flow Quantification During Standard Myocardial Perfusion Imaging with Rubidium-82 Positron Emission Tomography
Hamid Abdollahi, Robert Doot, Raul Porto +6
Background: Renal blood flow (RBF) is an important marker of kidney health, but noninvasive assessment is not routinely used in clinical imaging. We evaluated the feasibility and p…
A Clinically Anchored Radiomics Dictionary for Explainable TI-RADS-Based Thyroid Nodule Classification in Ultrasound; Dictionary Version TU1.0
Mohammad Salmanpour, Shahram Taeb, Ali Fathi Jouzdani +5
Artificial intelligence based radiomics models for thyroid ultrasound (US) often achieve strong diagnostic performance but remain difficult to interpret, limiting clinical trust an…
Towards Routine AI-Based PET/CT and SPECT/CT Lesion Segmentation and Tracking in PSMA Theranostics
Fereshteh Yousefirizi, Jean-Mathieu Beauregard, Arman Rahmim
Quantitative molecular imaging is central to treatment response assessment in oncology, yet clinical practice remains largely dominated by patient-level or limited target-lesion cr…
Beyond the Tumor: Recurrence-Prone Radiomics for Prognostication in Negative PSMA PET/CT scans of Prostate Cancer
Fereshteh Yousefirizi, Sara Harsini, Mobin Mohebi +14
In patients with biochemical recurrence of prostate cancer and negative PSMA PET/CT, radiomics features extracted from recurrence-prone organs can predict clinical progression and…
Multi-Kernel Gated Decoder Adapters for Robust Multi-Task Thyroid Ultrasound under Cross-Center Shift
Maziar Sabouri, Nourhan Bayasi, Arman Rahmim
Thyroid ultrasound (US) automation couples two competing requirements: global, geometry-driven reasoning for nodule delineation and local, texture-driven reasoning for malignancy r…