介绍NCL-SM：一个来自人类骨骼肌活检图像的完全标注数据集
Introducing NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies
AI总结：
本文发布了NCL-SM数据集，包含46个人类骨骼肌组织切片和超过5万条手动分割的肌纤维标注，为开发自动化、精确的骨骼肌纤维分割与分类流水线提供了高质量数据基础。
摘要：
骨骼肌（SM）组织的单细胞分析是理解许多神经肌肉疾病的基本工具。为了使这种分析可靠且可重复，SM组织显微图像中单个纤维的识别（分割）必须精确。目前没有工具或流水线能够实现SM组织横截面图像的自动、精确分割和整理。该领域的生物医学科学家依赖定制工具和通用机器学习（ML）模型，两者之后都需要耗费大量人力且主观的人工干预才能使分割正确。我们相信，通过训练ML模型，可以实现自动化、精确、可重复的分割。然而，目前没有高质量、公开可用的标注成像数据集可供ML模型训练。在本文中，我们发布了NCL-SM：一个高质量生物成像数据集，包含来自健康对照受试者和基因诊断肌肉病理患者的46个人类组织切片。这些图像包括>50k个手动分割的肌纤维（myofibres）。此外，我们还整理了高质量的肌纤维，并标注了在SM组织图像中拒绝低质量肌纤维和区域的原因，使这些数据完全准备好进行下游分析。我们相信，这将为开发一个全自动流水线铺平道路，该流水线能够在组织切片图像中识别单个肌纤维，特别是还能对适合进一步分析的肌纤维进行分类。
英文摘要：
Single cell analysis of skeletal muscle (SM) tissue is a fundamental tool for understanding many neuromuscular disorders. For this analysis to be reliable and reproducible, identification of individual fibres within microscopy images (segmentation) of SM tissue should be precise. There is currently no tool or pipeline that makes automatic and precise segmentation and curation of images of SM tissue cross-sections possible. Biomedical scientists in this field rely on custom tools and general machine learning (ML) models, both followed by labour intensive and subjective manual interventions to get the segmentation right. We believe that automated, precise, reproducible segmentation is possible by training ML models. However, there are currently no good quality, publicly available annotated imaging datasets available for ML model training. In this paper we release NCL-SM: a high quality bioimaging dataset of 46 human tissue sections from healthy control subjects and from patients with genetically diagnosed muscle pathology. These images include $>$ 50k manually segmented muscle fibres (myofibres). In addition we also curated high quality myofibres and annotated reasons for rejecting low quality myofibres and regions in SM tissue images, making this data completely ready for downstream analysis. This, we believe, will pave the way for development of a fully automatic pipeline that identifies individual myofibres within images of tissue sections and, in particular, also classifies individual myofibres that are fit for further analysis.
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。
