Abstract
Pathologists rely on gigapixel whole-slide images (WSIs) to diagnose diseases like cancer, yet current digital pathology tools hinder diagnosis. The immense scale of WSIs, often exceeding 100,000 X 100,000 pixels, clashes with the limited views traditional monitors offer. This mismatch forces constant panning and zooming, increasing pathologist cognitive load, causing diagnostic fatigue, and slowing pathologists' adoption of digital methods. PathVis, our mixed-reality visualization platform for Apple Vision Pro, addresses these challenges. It transforms the pathologist's interaction with data, replacing cumbersome mouse-and-monitor navigation with intuitive exploration using natural hand gestures, eye gaze, and voice commands in an immersive workspace. PathVis integrates AI to enhance diagnosis. An AI-driven search function instantly retrieves and displays the top five similar patient cases side-by-side, improving diagnostic precision and efficiency through rapid comparison. Additionally, a multimodal conversational AI assistant offers real-time image interpretation support and aids collaboration among pathologists across multiple Apple devices. By merging the directness of traditional pathology with advanced mixed-reality visualization and AI, PathVis improves diagnostic workflows, reduces cognitive strain, and makes pathology practice more effective and engaging. The PathVis source code and a demo video are publicly available at: this https URL
Abstract (translated)
病理学家依赖于巨像素全切片图像（WSIs）来诊断癌症等疾病，然而现有的数字病理工具却妨碍了这一过程。由于WSI的规模庞大，通常超过10万乘以10万像素，与传统显示器提供的有限视角形成了冲突。这种不匹配迫使病理学家不断地进行平移和缩放操作，增加了认知负担，导致诊断疲劳，并减缓了他们采用数字方法的速度。 PathVis是我们为苹果Vision Pro设计的混合现实可视化平台，旨在解决这些问题。它通过在沉浸式工作空间中使用自然的手势、视线以及语音命令来替代笨拙的老鼠与显示器导航方式，从而改变了病理学家对数据的交互方式。PathVis将人工智能集成到诊断过程中：一个基于AI的搜索功能能够立即检索并展示前五名类似患者的病例，实现快速比较以提高诊断精度和效率。 此外，一个多模态对话式AI助手为实时图像解读提供支持，并帮助多台苹果设备上的病理学家进行协作。通过结合传统病理学的直接性和先进的混合现实可视化以及人工智能技术，PathVis改进了诊断工作流程，减少了认知负担，并使病理实践更加有效和吸引人。 PathVis源代码及演示视频公开链接：[此 URL](this%20https%20URL)（请将“this https URL”替换为实际提供的链接）。
URL
https://arxiv.org/abs/2505.02780
