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Ruida Cheng

4 papers

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papers

Publications (4)

cs.CV2026

A Unified 2D Framework for DeepLesion Detection, Segmentation and Short Report Generation

Ruida Cheng, Tejas S. Mathai, Benjamin Hou +4

In previous work, we integrated large language models (LLMs) into the lesion segmentation model based on the ULS23 DeepLesion dataset, using short-form findings from the reports. I…

cs.CV2016

Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation

Naji Khosravan, Haydar Celik, Baris Turkbey +9

This study introduced a novel system, called Gaze2Segment, integrating biological and computer vision techniques to support radiologists' reading experience with an automatic image…

cs.CV2025

Text Embedded Swin-UMamba for DeepLesion Segmentation

Ruida Cheng, Tejas Sudharshan Mathai, Pritam Mukherjee +5

Segmentation of lesions on CT enables automatic measurement for clinical assessment of chronic diseases (e.g., lymphoma). Integrating large language models (LLMs) into the lesion s…

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…

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