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20232026
most citedEnhancing chest X-ray datasets with privacy-preserving large language models and multi-type annotations: a data-driven approach for improved classification

7 citations · 16 across the 14 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

eess.IV2024★ 4 cited

MRISegmentator-Abdomen: A Fully Automated Multi-Organ and Structure Segmentation Tool for T1-weighted Abdominal MRI

Yan Zhuang, Tejas Sudharshan Mathai, Pritam Mukherjee +6

Background: Segmentation of organs and structures in abdominal MRI is useful for many clinical applications, such as disease diagnosis and radiotherapy. Current approaches have foc…

cs.AI2024

How Well Do Multi-modal LLMs Interpret CT Scans? An Auto-Evaluation Framework for Analyses

Qingqing Zhu, Benjamin Hou, Tejas S. Mathai +7

Automatically interpreting CT scans can ease the workload of radiologists. However, this is challenging mainly due to the scarcity of adequate datasets and reference standards for…

eess.IV2024★ 7 cited

Enhancing chest X-ray datasets with privacy-preserving large language models and multi-type annotations: a data-driven approach for improved classification

Ricardo Bigolin Lanfredi, Pritam Mukherjee, Ronald Summers

In chest X-ray (CXR) image analysis, rule-based systems are usually employed to extract labels from reports for dataset releases. However, there is still room for improvement in la…

cs.CL2024★ 5 cited

Leveraging Professional Radiologists' Expertise to Enhance LLMs' Evaluation for Radiology Reports

Qingqing Zhu, Xiuying Chen, Qiao Jin +6

In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging. Current metrics,…

eess.IV2024

Weakly Supervised Detection of Pheochromocytomas and Paragangliomas in CT

David C. Oluigboa, Bikash Santra, Tejas Sudharshan Mathai +6

Pheochromocytomas and Paragangliomas (PPGLs) are rare adrenal and extra-adrenal tumors which have the potential to metastasize. For the management of patients with PPGLs, CT is the…

eess.IV2024

Automated Classification of Body MRI Sequence Type Using Convolutional Neural Networks

Kimberly Helm, Tejas Sudharshan Mathai, Boah Kim +3

Multi-parametric MRI of the body is routinely acquired for the identification of abnormalities and diagnosis of diseases. However, a standard naming convention for the MRI protocol…