30 citations · 39 across the 4 of their papers we have counts for
4 papers
Prompt-driven Universal Model for View-Agnostic Echocardiography Analysis
Sekeun Kim, Hui Ren, Peng Guo +5
Echocardiography segmentation for cardiac analysis is time-consuming and resource-intensive due to the variability in image quality and the necessity to process scans from various…
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
Cheng Chen, Juzheng Miao, Dufan Wu +10
The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation ta…
Radiology-Llama2: Best-in-Class Large Language Model for Radiology
Zhengliang Liu, Yiwei Li, Peng Shu +18
This paper introduces Radiology-Llama2, a large language model specialized for radiology through a process known as instruction tuning. Radiology-Llama2 is based on the Llama2 arch…
Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification
Jaeik Jeon, Yeonggul Jang, Youngtaek Hong +2
Medical imaging, including MRI, CT, and Ultrasound, plays a vital role in clinical decisions. Accurate segmentation is essential to measure the structure of interest from the image…