College of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing, China.
Chinese PLA Medical School, Beijing, China.
Sci Data. 2024 Jun 8;11(1):608. doi: 10.1038/s41597-024-03370-5.
Microbiological Rapid On-Site Evaluation (M-ROSE) is based on smear staining and microscopic observation, providing critical references for the diagnosis and treatment of pulmonary infectious disease. Automatic identification of pathogens is the key to improving the quality and speed of M-ROSE. Recent advancements in deep learning have yielded numerous identification algorithms and datasets. However, most studies focus on artificially cultured bacteria and lack clinical data and algorithms. Therefore, we collected Gram-stained bacteria images from lower respiratory tract specimens of patients with lung infections in Chinese PLA General Hospital obtained by M-ROSE from 2018 to 2022 and desensitized images to produce 1705 images (4,912 × 3,684 pixels). A total of 4,833 cocci and 6,991 bacilli were manually labelled and differentiated into negative and positive. In addition, we applied the detection and segmentation networks for benchmark testing. Data and benchmark algorithms we provided that may benefit the study of automated bacterial identification in clinical specimens.
微生物快速现场评估（M-ROSE）基于涂片染色和显微镜观察，为肺部传染病的诊断和治疗提供了重要参考。病原体的自动识别是提高 M-ROSE 质量和速度的关键。深度学习的最新进展产生了许多识别算法和数据集。然而，大多数研究都集中在人工培养的细菌上，缺乏临床数据和算法。因此，我们收集了中国人民解放军总医院 M-ROSE 从 2018 年到 2022 年从下呼吸道标本中获取的肺部感染患者的革兰氏染色细菌图像，并对图像进行脱敏处理，生成了 1705 张图像（4912x3684 像素）。总共手动标记了 4833 个球菌和 6991 个杆菌，并将其分为阴性和阳性。此外，我们还应用了检测和分割网络进行基准测试。我们提供的数据和基准算法可能有助于研究临床标本中自动细菌识别。
