Publications

Vision-language framework for multi-sequence brain magnetic resonance imaging

Structural magnetic resonance imaging (MRI) is a cornerstone for diagnosing neurological disorders, yet automated interpretation of …

Anatomy-guided, modality-agnostic segmentation of neuroimaging abnormalities

Magnetic resonance imaging (MRI) offers multiple sequences that provide complementary views of brain anatomy and pathology. However, …

AI-based differential diagnosis of dementia etiologies on multimodal data.

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for …

Disease-driven domain generalization for neuroimaging-based assessment of Alzheimer’s disease.

Development of deep learning models to evaluate structural brain changes caused by cognitive impairment in MRI scans holds significant …

VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting

Label-efficient and reliable semantic segmentation is essential for many real-life applications, especially for industrial settings …

Ani-GIFs: A benchmark dataset for domain generalization of action recognition from GIFs.

Deep learning models perform remarkably well for the same task under the assumption that data is always coming from the same …