Výsledky vyhledávání - "Papineni, Vijay Ram"

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TiBiX: Leveraging Temporal Information for Bidirectional X-ray and Report Generation

Autor: Sanjeev, Santosh, Maani, Fadillah Adamsyah, Abzhanov, Arsen, Papineni, Vijay Ram, Almakky, Ibrahim, Papież, Bartłomiej W., Yaqub, Mohammad

With the emergence of vision language models in the medical imaging domain, numerous studies have focused on two dominant research activities: (1) report generation from Chest X-rays (CXR), and (2) synthetic scan generation from text or reports. Desp

Externí odkaz: http://arxiv.org/abs/2403.13343

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XReal: Realistic Anatomy and Pathology-Aware X-ray Generation via Controllable Diffusion Model

Autor: Hashmi, Anees Ur Rehman, Almakky, Ibrahim, Qazi, Mohammad Areeb, Sanjeev, Santosh, Papineni, Vijay Ram, Jagdish, Jagalpathy, Yaqub, Mohammad

Large-scale generative models have demonstrated impressive capabilities in producing visually compelling images, with increasing applications in medical imaging. However, they continue to grapple with hallucination challenges and the generation of an

Externí odkaz: http://arxiv.org/abs/2403.09240

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PECon: Contrastive Pretraining to Enhance Feature Alignment between CT and EHR Data for Improved Pulmonary Embolism Diagnosis

Autor: Sanjeev, Santosh, Khatib, Salwa K. Al, Shaaban, Mai A., Almakky, Ibrahim, Papineni, Vijay Ram, Yaqub, Mohammad

Previous deep learning efforts have focused on improving the performance of Pulmonary Embolism(PE) diagnosis from Computed Tomography (CT) scans using Convolutional Neural Networks (CNN). However, the features from CT scans alone are not always suffi

Externí odkaz: http://arxiv.org/abs/2308.14050

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