Literature DB >> 26208594

Spleen Segmentation and Assessment in CT Images for Traumatic Abdominal Injuries.

S M Reza Soroushmehr1, Pavani Davuluri, Somayeh Molaei, Rosalyn Hobson Hargraves, Yang Tang, Charles H Cockrell, Kevin Ward, Kayvan Najarian.   

Abstract

Spleen segmentation is especially challenging as the majority of solid organs in the abdomen region have similar gray level range. Physician analysis of computed tomography (CT) images to assess abdominal trauma could be very time consuming and hence, automating this process can reduce time to treatment. The proposed method presented in this paper is a fully automated and knowledge based technique that employs anatomical information to accurately segment the spleen in CT images. The spleen detection procedure is proposed to locate the spleen in both healthy and injured cases. In the presence of hemorrhage and laceration, the edge merging technique is used. The accuracy of the method is measured by some criteria such as mis-segmented area, accuracy, specificity and sensitivity. The results show that the proposed spleen segmentation method performs well and outperforms other methods.

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Year:  2015        PMID: 26208594     DOI: 10.1007/s10916-015-0271-x

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  15 in total

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2.  The epidemiology and clinical evaluation of abdominal trauma. An analysis of a multidisciplinary trauma registry.

Authors:  Gianluca Costa; Simone Maria Tierno; Federico Tomassini; Luigi Venturini; Barbara Frezza; Giulio Cancrini; Francesco Stella
Journal:  Ann Ital Chir       Date:  2010 Mar-Apr       Impact factor: 0.766

3.  Multiple abdominal organ segmentation: an atlas-based fuzzy connectedness approach.

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Journal:  IEEE Trans Inf Technol Biomed       Date:  2007-05

Review 4.  Imaging issues in CT of blunt trauma to the chest and abdomen.

Authors:  Lane F Donnelly
Journal:  Pediatr Radiol       Date:  2009-06

Review 5.  A review of algorithms for medical image segmentation and their applications to the female pelvic cavity.

Authors:  Zhen Ma; João Manuel R S Tavares; Renato Natal Jorge; T Mascarenhas
Journal:  Comput Methods Biomech Biomed Engin       Date:  2010       Impact factor: 1.763

6.  Segmentation and quantification of intra-ventricular/cerebral hemorrhage in CT scans by modified distance regularized level set evolution technique.

Authors:  K N Bhanu Prakash; Shi Zhou; Tim C Morgan; Daniel F Hanley; Wieslaw L Nowinski
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-09       Impact factor: 2.924

7.  Management of penetrating abdominal trauma in the conflict environment: the role of computed tomography scanning.

Authors:  Jonathan J Morrison; Jon C Clasper; Iain Gibb; Mark Midwinter
Journal:  World J Surg       Date:  2011-01       Impact factor: 3.352

8.  Automated medical image segmentation techniques.

Authors:  Neeraj Sharma; Lalit M Aggarwal
Journal:  J Med Phys       Date:  2010-01

9.  Incidence, patterns, and factors predicting mortality of abdominal injuries in trauma patients.

Authors:  Mohammad A Gad; Aly Saber; Shereif Farrag; Mohamed E Shams; Goda M Ellabban
Journal:  N Am J Med Sci       Date:  2012-03

10.  Unified wavelet and Gaussian filtering for segmentation of CT images; application in segmentation of bone in pelvic CT images.

Authors:  Simina Vasilache; Kevin Ward; Charles Cockrell; Jonathan Ha; Kayvan Najarian
Journal:  BMC Med Inform Decis Mak       Date:  2009-11-03       Impact factor: 2.796

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  1 in total

Review 1.  Current Applications and Future Impact of Machine Learning in Radiology.

Authors:  Garry Choy; Omid Khalilzadeh; Mark Michalski; Synho Do; Anthony E Samir; Oleg S Pianykh; J Raymond Geis; Pari V Pandharipande; James A Brink; Keith J Dreyer
Journal:  Radiology       Date:  2018-06-26       Impact factor: 11.105

  1 in total

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