Browsing Department of Computational and Data Sciences (CDS) by Subject "medical imaging"

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Lesion Synthesis using Physics-Based Noise Models for Low-Data Medical Imaging Regime applications

Narayanan, Ramanujam

Lesion segmentation and their progression prediction in medical imaging relies critically on the availability of manually annotated, heterogeneous large pathological datasets. Acquiring such diverse large datasets is also ...
Unsupervised Test-time Adaptation for Patient-Specific Deep Learning Models in Medical Imaging

Ravishankar, Hariharan

Deep learning (DL) models have achieved state-of-the-art results in multiple medical imaging applications, resulting in the widespread adoption of artificial intelligence (AI) models for radiological workflows. Despite ...