A new approach of skull fracture detection in CT brain images

Wan Mimi Diyana Wan Zaki, Mohammad Faizal Ahmad Fauzi, Rosli Besar

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

3 Citations (Scopus)

Abstract

This work demonstrates a new automated approach to segment skull from 2D-CT brain image to detect any fracture case. The key steps in the proposed approach include image normalization, centroid identification, multi-level global segmentation and skull skeletonization. Feature vectors such as location and fracture size are then extracted to represent fracture cases. Twenty eight encephalic fracture images are queried from a database of 3032 normal and fractured CT brain images to evaluate the usefulness of the skull segmentation as well as the extracted feature vectors in content-based medical image retrieval system (CBMIR). Retrieval performance of Normalized Euclidean and Normalized Manhattan distance metrics show almost perfect average recall-precision plots that portray the suitability of this approach to the CBMIR of fracture cases.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages156-167
Number of pages12
Volume5857 LNCS
DOIs
Publication statusPublished - 2009
Event1st International Visual Informatics Conference, IVIC 2009 - Kuala Lumpur
Duration: 11 Nov 200913 Nov 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5857 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Visual Informatics Conference, IVIC 2009
CityKuala Lumpur
Period11/11/0913/11/09

Fingerprint

Brain
Image retrieval
Image Retrieval
Medical Image
Feature Vector
Segmentation
Skeletonization
Distance Metric
Centroid
Normalization
Euclidean
Retrieval
Evaluate
Demonstrate

Keywords

  • CBMIR
  • CT brain images
  • Multi-level segmentation
  • Skeletonization
  • Skull fracture

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Wan Zaki, W. M. D., Ahmad Fauzi, M. F., & Besar, R. (2009). A new approach of skull fracture detection in CT brain images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5857 LNCS, pp. 156-167). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5857 LNCS). https://doi.org/10.1007/978-3-642-05036-7_16

A new approach of skull fracture detection in CT brain images. / Wan Zaki, Wan Mimi Diyana; Ahmad Fauzi, Mohammad Faizal; Besar, Rosli.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5857 LNCS 2009. p. 156-167 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5857 LNCS).

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

Wan Zaki, WMD, Ahmad Fauzi, MF & Besar, R 2009, A new approach of skull fracture detection in CT brain images. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5857 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5857 LNCS, pp. 156-167, 1st International Visual Informatics Conference, IVIC 2009, Kuala Lumpur, 11/11/09. https://doi.org/10.1007/978-3-642-05036-7_16
Wan Zaki WMD, Ahmad Fauzi MF, Besar R. A new approach of skull fracture detection in CT brain images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5857 LNCS. 2009. p. 156-167. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-05036-7_16
Wan Zaki, Wan Mimi Diyana ; Ahmad Fauzi, Mohammad Faizal ; Besar, Rosli. / A new approach of skull fracture detection in CT brain images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5857 LNCS 2009. pp. 156-167 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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