Computer aided diagnosis for pulmonary nodules by shape feature extraction

Kazunori Takei, Noriyasu Homma, Tadashi Ishibashi, Masao Sakai, Makoto Yoshizawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, we propose a new diagnosis method of pulmonary nodules in CT images to reduce false positive (FP) rate for high true positive (TP) rate conditions. An essential core of the method is to extract two novel and effective features from the raw CT images: One is orientation features of nodules in a region of interest (ROI) extracted by a gabor filter, while the other is variation of CT values of the ROI in the direction along body axis. By using the extracted features, a principal component analysis technic and neural network approaches are then used to discriminate between nodule and non-nodule images. Simulation results show that discrimination performance using the proposed features is extremely improved compared to that of the conventional method.

Original languageEnglish
Title of host publicationSICE Annual Conference, SICE 2007
Pages1964-1967
Number of pages4
DOIs
Publication statusPublished - 2007 Dec 1
EventSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
Duration: 2007 Sep 172007 Sep 20

Publication series

NameProceedings of the SICE Annual Conference

Other

OtherSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
CountryJapan
CityTakamatsu
Period07/9/1707/9/20

Keywords

  • Computer aided diagnosis
  • Feature extraction
  • Pulmonary nodules
  • X-ray CT images

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Computer aided diagnosis for pulmonary nodules by shape feature extraction'. Together they form a unique fingerprint.

Cite this