collaborators

6 papers

cs.CV2026

EchoSonar-R: A Multi-View Reasoning-Enabled Model for Disease Classification and Report Generation in Echocardiography

Darya Taratynova, Ahmed Aly, Numan Saeed +1

Echocardiography is the most widely used non-invasive cardiac imaging modality, providing essential information for cardiovascular diagnosis. Interpreting an echocardiogram require…

cs.CV2026

CardioBench: Do Echocardiography Foundation Models Generalize Beyond the Lab?

Darya Taratynova, Ahmed Aly, Numan Saeed +1

Foundation models are reshaping medical imaging, yet their application in echocardiography remains limited, hindered by a heavy reliance on private datasets that prevent reproducib…

eess.IV2025

BRIQA: Balanced Reweighting in Image Quality Assessment of Pediatric Brain MRI

Alya Almsouti, Ainur Khamitova, Darya Taratynova +1

Assessing the severity of artifacts in pediatric brain Magnetic Resonance Imaging (MRI) is critical for diagnostic accuracy, especially in low-field systems where the signal-to-noi…

cs.CV2025

A Multimodal and Multi-centric Head and Neck Cancer Dataset for Segmentation, Diagnosis and Outcome Prediction

Numan Saeed, Salma Hassan, Shahad Hardan +40

We present a publicly available multimodal dataset for head and neck cancer research, comprising 1123 annotated Positron Emission Tomography/Computed Tomography (PET/CT) studies fr…

cs.CV2025

TPA: Temporal Prompt Alignment for Fetal Congenital Heart Defect Classification

Darya Taratynova, Alya Almsouti, Beknur Kalmakhanbet +2

Congenital heart defect (CHD) detection in ultrasound videos is hindered by image noise and probe positioning variability. While automated methods can reduce operator dependence, c…

cs.LG2025

Forget-MI: Machine Unlearning for Forgetting Multimodal Information in Healthcare Settings

Shahad Hardan, Darya Taratynova, Abdelmajid Essofi +2

Privacy preservation in AI is crucial, especially in healthcare, where models rely on sensitive patient data. In the emerging field of machine unlearning, existing methodologies st…