Paper Info
Title
Investigation of optimal feature value set in false positive reduction process for automated abdominal lymph node detection method
Abstract
This paper presents an investigation of optimal feature value set in false positive reduction process for the automated method of enlarged abdominal lymph node detection. We have developed the automated abdominal lymph node detection method to aid for surgical planning. Because it is important to understand the location and the structure of an enlarged lymph node in order to make a suitable surgical plan. However, our previous method was not able to obtain the suitable feature value set. This method was able to detect 71.6% of the lymph nodes with 12.5 FPs per case. In this paper, we investigate the optimal feature value set in the false positive reduction process to improve the method for automated abdominal lymph node detection. By applying our improved method by using the optimal feature value set to 28 cases of abdominal 3D CT images, we detected about 74.7% of the abdominal lymph nodes with 11.8 FPs/case.
Year
DOI
Venue
2015
10.1117/12.2082500
Proceedings of SPIE
Keywords
Field
DocType
computer aided surgery,lymph node detection,local intensity structure analysis,support vector machine
Lymph,Computer vision,Surgical planning,Abdominal lymph nodes,Value set,Computer aided surgery,Enlarged lymph node,Abdomen,Artificial intelligence,Radiology,Lymph node,Physics
Conference
Volume
ISSN
Citations 
9414
0277-786X
0
PageRank 
References 
Authors
0.34
3
11
Name
Order
Citations
PageRank
Yoshihiko Nakamura17012.29
Yukitaka Nimura26611.19
Takayuki Kitasaka352067.91
Shinji Mizuno4792153.37
Kazuhiro Furukawa5207.20
Hidemi Goto6208.26
Michitaka Fujiwara716816.60
Kazunari Misawa826123.60
masaaki ito900.34
Shigeru Nawano1026529.51
Kensaku Mori111125160.28