SPLICE——简化数字病理图像处理
SPLICE -- Streamlining Digital Pathology Image Processing
AI总结：
提出无监督算法SPLICE，将全幻灯片图像浓缩为紧凑代表性图像块，减少50%存储需求并提升计算效率。
摘要：
数字病理学与人工智能（AI）模型的整合彻底改变了组织病理学，开启了新的机遇。随着全幻灯片图像（WSIs）的日益普及，从海量生物医学档案中高效检索、处理和分析相关图像的需求不断增长。然而，由于WSIs的巨大尺寸和内容复杂性，处理WSIs面临挑战。对WSIs进行完整的计算机消化是不切实际的，并且单独处理所有图像块的成本过高。在本文中，我们提出了一种无监督图像块处理算法——用于图像分类与查询的顺序处理格（SPLICE）。这种新颖的方法将组织病理学WSI浓缩为一组紧凑的代表性图像块，形成WSI的“拼贴”，同时最大限度地减少冗余。SPLICE通过顺序分析WSI并选择非冗余的代表性特征，优先考虑图像块的质量和唯一性。我们评估了SPLICE在搜索和匹配应用中的表现，与现有最先进方法相比，显示出更高的准确性、更少的计算时间和存储需求。作为一种无监督方法，SPLICE有效地将表示组织图像的存储需求减少了50%。这种减少使计算病理学中的众多算法能够更高效地运行，为加速数字病理学的采用铺平了道路。
英文摘要：
Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whole Slide Images (WSIs), there's a growing demand for efficient retrieval, processing, and analysis of relevant images from vast biomedical archives. However, processing WSIs presents challenges due to their large size and content complexity. Full computer digestion of WSIs is impractical, and processing all patches individually is prohibitively expensive. In this paper, we propose an unsupervised patching algorithm, Sequential Patching Lattice for Image Classification and Enquiry (SPLICE). This novel approach condenses a histopathology WSI into a compact set of representative patches, forming a "collage" of WSI while minimizing redundancy. SPLICE prioritizes patch quality and uniqueness by sequentially analyzing a WSI and selecting non-redundant representative features. We evaluated SPLICE for search and match applications, demonstrating improved accuracy, reduced computation time, and storage requirements compared to existing state-of-the-art methods. As an unsupervised method, SPLICE effectively reduces storage requirements for representing tissue images by 50%. This reduction enables numerous algorithms in computational pathology to operate much more efficiently, paving the way for accelerated adoption of digital pathology.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
