Literature DB >> 7656554

3-D image analysis of intra-cerebral brain hemorrhage from digitized CT films.

S Loncaric1, A P Dhawan, J Broderick, T Brott.   

Abstract

A new 3-D technique for the segmentation and quantification of human spontaneous intra-cerebral brain hemorrhage (ICH) is presented in this paper. The algorithm for ICH primary region segmentation uses the spatially weighted K-means histogram-based clustering algorithm. The ICH edema region segmentation algorithm employs an iterative morphological processing of the ICH brain data. A volume rendering technique is used for the effective 3-D visualization of ICH segmented regions. A computer program is developed for use in the human spontaneous ICH study involving a large number of patients. Experimental measurements and visualization results are presented which were computed on real ICH patient brain data.

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Year:  1995        PMID: 7656554     DOI: 10.1016/0169-2607(95)01620-9

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  6 in total

1.  Detection and quantification of intracerebral and intraventricular hemorrhage from computed tomography images with adaptive thresholding and case-based reasoning.

Authors:  Yuanxiu Zhang; Mingyang Chen; Qingmao Hu; Wenhua Huang
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-08-23       Impact factor: 2.924

2.  Three-dimensional reconstruction and volumetry of intracranial haemorrhage and its mass effect.

Authors:  H M Strik; H Borchert; C Fels; M Knauth; O Rienhoff; M Bähr; J F Verhey
Journal:  Neuroradiology       Date:  2005-04-26       Impact factor: 2.804

3.  Automatic detection of the existence of subarachnoid hemorrhage from clinical CT images.

Authors:  Yonghong Li; Jianhuang Wu; Hongwei Li; Degang Li; Xiaohua Du; Zhijun Chen; Fucang Jia; Qingmao Hu
Journal:  J Med Syst       Date:  2010-09-09       Impact factor: 4.460

4.  Automated segmentation of haematoma and perihaematomal oedema in MRI of acute spontaneous intracerebral haemorrhage.

Authors:  Stefan Pszczolkowski; Zhe K Law; Rebecca G Gallagher; Dewen Meng; David J Swienton; Paul S Morgan; Philip M Bath; Nikola Sprigg; Rob A Dineen
Journal:  Comput Biol Med       Date:  2019-01-29       Impact factor: 4.589

Review 5.  Computational Approaches for Acute Traumatic Brain Injury Image Recognition.

Authors:  Emily Lin; Esther L Yuh
Journal:  Front Neurol       Date:  2022-03-09       Impact factor: 4.003

6.  3D Deep Neural Network Segmentation of Intracerebral Hemorrhage: Development and Validation for Clinical Trials.

Authors:  Matthew F Sharrock; W Andrew Mould; Hasan Ali; Meghan Hildreth; Issam A Awad; Daniel F Hanley; John Muschelli
Journal:  Neuroinformatics       Date:  2020-09-27
  6 in total

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