Automated segmentation and detection of increased uptake regions in bone scintigraphy using SPECT/CT images

Masakazu Tsujimoto, Atsushi Teramoto, Seiichiro Ota, Hiroshi Toyama, Hiroshi Fujita

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Purpose: To develop a method for automated detection of highly integrated sites in SPECT images using bone information obtained from CT images in bone scintigraphy. Methods: Bone regions on CT images were first extracted, and bones were identified by segmenting multiple regions. Next, regions corresponding to the bone regions on SPECT images were extracted based on the bone regions on CT images. Subsequently, increased uptake regions were extracted from the SPECT image using thresholding and three-dimensional labeling. Last, the ratio of increased uptake regions to all bone regions was calculated and expressed as a quantitative index. To verify the efficacy of this method, a basic assessment was performed using phantom and clinical data. Results: The results of this analytical method using phantoms created by changing the radioactive concentrations indicated that regions of increased uptake were detected regardless of the radioactive concentration. Assessments using clinical data indicated that detection sensitivity for increased uptake regions was 71% and that the correlation between manual measurements and automated measurements was significant (correlation coefficient 0.868). Conclusion: These results suggested that automated detection of increased uptake regions on SPECT images using bone information obtained from CT images would be possible.

Original languageEnglish
Pages (from-to)182-190
Number of pages9
JournalAnnals of Nuclear Medicine
Volume32
Issue number3
DOIs
Publication statusPublished - 01-04-2018

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Automated segmentation and detection of increased uptake regions in bone scintigraphy using SPECT/CT images'. Together they form a unique fingerprint.

  • Cite this