标题： 超声-QBench：大型语言模型能否助力超声影像的质量评估？ 显示英文标题

标题： Ultrasound-QBench: Can LLMs Aid in Quality Assessment of Ultrasound Imaging?

摘要： 随着超声检查数量的急剧增加，由于操作者熟练程度和成像条件的变化，低质量的超声成像逐渐增多，这给诊断准确性带来了严重负担，甚至在危急情况下可能导致诊断需要重新开始。 为了帮助临床医生选择高质量的超声图像并确保准确的诊断，我们引入了Ultrasound-QBench，这是一个全面的基准，系统地评估多模态大型语言模型（MLLMs）在超声图像质量评估任务中的表现。 Ultrasound-QBench建立了两个来自不同来源的数据集： IVUSQA，包含7,709张图像，以及CardiacUltraQA，包含3,863张图像。 这些包含常见超声成像伪影的图像是由专业超声专家标注并分为三个质量级别：高、中、低。 为了更好地评估MLLMs，我们将质量评估任务分解为三个维度：定性分类、定量评分和比较评估。 对7个开源MLLMs以及1个专有MLLMs的评估表明，MLLMs在超声图像质量分类的低级视觉任务中具有初步能力。 我们希望这个基准能够激发研究社区深入探索和提升MLLMs在医学影像任务中尚未开发的潜力。 显示英文摘要

摘要： With the dramatic upsurge in the volume of ultrasound examinations, low-quality ultrasound imaging has gradually increased due to variations in operator proficiency and imaging circumstances, imposing a severe burden on diagnosis accuracy and even entailing the risk of restarting the diagnosis in critical cases. To assist clinicians in selecting high-quality ultrasound images and ensuring accurate diagnoses, we introduce Ultrasound-QBench, a comprehensive benchmark that systematically evaluates multimodal large language models (MLLMs) on quality assessment tasks of ultrasound images. Ultrasound-QBench establishes two datasets collected from diverse sources: IVUSQA, consisting of 7,709 images, and CardiacUltraQA, containing 3,863 images. These images encompassing common ultrasound imaging artifacts are annotated by professional ultrasound experts and classified into three quality levels: high, medium, and low. To better evaluate MLLMs, we decompose the quality assessment task into three dimensionalities: qualitative classification, quantitative scoring, and comparative assessment. The evaluation of 7 open-source MLLMs as well as 1 proprietary MLLMs demonstrates that MLLMs possess preliminary capabilities for low-level visual tasks in ultrasound image quality classification. We hope this benchmark will inspire the research community to delve deeper into uncovering and enhancing the untapped potential of MLLMs for medical imaging tasks.