.png){kind=icon}
返回
Segmentation metric misinterpretations in bioimage analysis
.png){kind=icon}
OA
AI
DOI：10.1038/s41592-023-01942-8.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This study shows the importance of proper metrics for comparing algorithms for bioimage segmentation and object detection by exploring the impact of metrics on the relative performance of algorithms in three image analysis competitions. Quantitative evaluation of image segmentation algorithms is crucial in the field of bioimage analysis. The most common assessment scores, however, are often misinterpreted and multiple definitions coexist with the same name. Here we present the ambiguities of evaluation metrics for segmentation algorithms and show how these misinterpretations can alter leaderboards of influential competitions. We also propose guidelines for how the currently existing problems could be tackled.
Keyword:
NUCLEUS SEGMENTATION
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
32.1
论文数:
7.2K
被引数:
12.7W
机构
引用论文
nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer.png)
CELL SYSTEMSOAAI
CELL SYSTEMSIF7.7
OAAI分享收藏
A fully automatic segmentation pipeline of pulmonary lobes before and after lobectomy from computed tomography images计算机断层扫描图像肺叶切除术前后肺叶的全自动分割管道
PREAI
分享收藏LIVECell-A large-scale dataset for label-free live cell segmentationLIVECell-用于无标记活细胞分割的大规模数据集NATURE METHODSOAAI
NATURE METHODSIF32.1
OAAI分享收藏EMBEDSEG: Embedding-based Instance Segmentation for Biomedical Microscopy DataMEDICAL IMAGE ANALYSIS
MEDICAL IMAGE ANALYSISIF11.8
PREAI
分享收藏SpheroidPicker for automated 3D cell culture manipulation using deep learningSCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏
查看更多内容