NCD (Nasal Cytology Dataset)

NCD数据集是由巴里大学计算机科学系等机构联合创建，专注于鼻黏膜细胞的自动检测与分类。该数据集包含超过10,000个鼻黏膜细胞实例，分布在500张图像中，这些图像来源于临床患者的鼻黏膜样本，经过专业人员手动标注。数据集的创建旨在通过深度学习模型，如DETR和YOLO，辅助医生和生物学家在临床实践中快速准确地识别和分类鼻黏膜细胞。NCD数据集的应用领域主要集中在加速鼻科学专家的工作，提高鼻部疾病如鼻炎和过敏的诊断效率。

The NCD dataset was jointly created by the Department of Computer Science of the University of Bari and other institutions, focusing on automatic detection and classification of nasal mucosal cells. This dataset contains over 10,000 nasal mucosal cell instances distributed across 500 images, which are derived from nasal mucosal samples of clinical patients and manually annotated by professionals. The dataset was developed to assist doctors and biologists in rapidly and accurately identifying and classifying nasal mucosal cells in clinical practice via deep learning models such as DETR and YOLO. The application scenarios of the NCD dataset mainly focus on accelerating the work of rhinology experts and improving the diagnostic efficiency of nasal diseases such as rhinitis and allergies.

搜集汇总

背景与挑战

背景概述

NCD数据集是一个专注于鼻黏膜细胞自动检测与分类的数据集，由巴里大学等机构创建，包含超过10,000个细胞实例和500张临床图像，旨在通过深度学习模型辅助医生和生物学家提高鼻部疾病诊断效率。