| Automatic subarachnoid space segmentation and hemorrhage detection in clinical head CT scans. | |
| | |
MedLine Citation:
|
PMID: 22081264 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
|
PURPOSE: The subarachnoid space (SAS) lies between the arachnoid membrane and the pia mater of the human brain, normally filled with cerebrospinal fluid (CSF). Subarachnoid hemorrhage (SAH) is a serious complication of neurological disease that can have high mortality and high risk of disability. Computed tomography (CT) head scans are often used for diagnosing SAH which may be difficult when the hemorrhage is small or subtle. A computer-aided diagnosis system from CT images is thus developed to augment image interpretation. METHODS: Supervised learning using the probability of distance features of several landmarks was employed to recognize SAS. For each CT image, the SAS was approximated in four steps: (1) Landmarks including brain boundary, midsagittal plane (MSP), anterior and posterior intersection points of brain boundary with the MSP, and superior point of the brain were extracted. (2) Distances to all the landmarks were calculated for every pixel in the CT image, and combined to construct a high-dimensional feature vector. (3) Using head CT images with manually delineated SAS as training dataset, the prior probabilities of distances for pixels within SAS and non-SAS were computed. (4) Any pixel of a head CT scan in the testing dataset was classified as an SAS or non-SAS pixel in a Bayesian decision framework based on its distance features. RESULTS: The proposed method was validated on clinical head CT images by comparison with manual segmentation. The results showed that the automated method is consistent with the gold standard. Compared with elastic registration based on grayscale information, the proposed method was less affected by grayscale variation between normal controls and patients. Compared with manual delineation, the average spatial overlap, relative overlap, and similarity index were, respectively, 89, 63, and 76% for the automatic SAS approximation of the 69 head CT scans tested. The proposed method was tested for SAH detection and yielded a sensitivity of 100% and a specificity of 92%. CONCLUSION: Automated SAH detection with high sensitivity was shown feasible in a prototype computer-aided diagnosis system. The proposed method may be extended for computer-aided diagnosis of several CSF-related diseases relevant to SAS abnormalities. |
| | |
Authors:
|
Yong-Hong Li; Liang Zhang; Qing-Mao Hu; Hong-Wei Li; Fu-Cang Jia; Jian-Huang Wu |
Related Documents
:
|
18165614 - Immuno-pet: a navigator in monoclonal antibody development and applications. 14516554 - Detection of recurrent brain tumor. comparison of mr registered camera-based and dedica... 15243404 - Pet/ct in diagnostic oncology. 22106234 - The benefit of early pet/ct surveillance in hpv-associated head and neck squamous cell ... 7530124 - Transrectal ultrasound versus magnetic resonance imaging in the estimation of prostatic... 6278454 - Nuclear overhauser effect study and assignment of d stem and reverse-hoogsteen base pai... |
Publication Detail:
|
Type: JOURNAL ARTICLE Date: 2011-11-12 |
Journal Detail:
|
Title: International journal of computer assisted radiology and surgery Volume: - ISSN: 1861-6429 ISO Abbreviation: - Publication Date: 2011 Nov |
Date Detail:
|
Created Date: 2011-11-14 Completed Date: - Revised Date: - |
Medline Journal Info:
|
Nlm Unique ID: 101499225 Medline TA: Int J Comput Assist Radiol Surg Country: - |
Other Details:
|
Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
|
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Boulevard, Shenzhen, 518055, China. |
Export Citation:
|
APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
|
|
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
Previous Document: Transfusion risk in cancer patients with chemotherapy-induced anemia when initiating darbepoetin alf...
Next Document: Large soft tissue osteochondroma of the heel: a case report and literature review.