Paper Info
Title
Evaluation of nucleus segmentation in digital pathology images through large scale image synthesis.
Abstract
Digital histopathology images with more than 1 Gigapixel are drawing more and more attention in clinical, biomedical research, and computer vision fields. Among the multiple observable features spanning multiple scales in the pathology images, the nuclear morphology is one of the central criteria for diagnosis and grading. As a result it is also the mostly studied target in image computing. Large amount of research papers have devoted to the problem of extracting nuclei from digital pathology images, which is the foundation of any further correlation study. However, the validation and evaluation of nucleus extraction have yet been formulated rigorously and systematically. Some researches report a human verified segmentation with thousands of nuclei, whereas a single whole slide image may contain up to million. The main obstacle lies in the difficulty of obtaining such a large number of validated nuclei, which is essentially an impossible task for pathologist. We propose a systematic validation and evaluation approach based on large scale image synthesis. This could facilitate a more quantitatively validated study for current and future histopathology image analysis field.
Year
DOI
Venue
2017
10.1117/12.2254220
Proceedings of SPIE
Keywords
Field
DocType
histopathology,nucleus extraction,segmentation evaluation,image synthesis
Computer vision,Scale-space segmentation,Segmentation,Computer science,Digital pathology,Image synthesis,Image segmentation,Artificial intelligence,Medical diagnostics
Conference
Volume
ISSN
Citations 
10140
0277-786X
3
PageRank 
References 
Authors
0.40
5
10
Name
Order
Citations
PageRank
Naiyun Zhou151.78
Xiaxia Yu230.40
Tianhao Zhao3121.60
Si Wen41196.03
Fusheng Wang5173.14
Wei Zhu6304.00
Tahsin M. Kurç71423149.77
Allen Tannenbaum83629409.15
Joel H. Saltz94046569.91
Yi Gao1011518.29