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CT Image under Improved Fuzzy C-Means Clustering Algorithm for Evaluation of the Relationship between Cerebrospinal Fluid Change and Communicating Hydrocephalus after Decompressive Craniectomy in Patients with Traumatic Brain Injury

Authors: Yanmin Zhang; Chunyue Zhang; Yan Wang;

CT Image under Improved Fuzzy C-Means Clustering Algorithm for Evaluation of the Relationship between Cerebrospinal Fluid Change and Communicating Hydrocephalus after Decompressive Craniectomy in Patients with Traumatic Brain Injury

Abstract

This study was aimed to realize the automatic segmentation of communicating hydrocephalus lesions in brain CT after decompressive craniotomy (DC) in patients with traumatic brain injury (TBI) and discover correlation between cerebrospinal fluid changes and communicating hydrocephalus. Based on the traditional fuzzy C-means (FCM) algorithm, a new segmentation method filter-based FCM (FBFCM) algorithm was proposed. With 56 TBI patients as the research objects, the hydrocephalus lesions in CT images of patients after DC were segmented. The segmentation success rate (SSR), the segmentation coefficient Epc, the segmentation entropy Epe, and the number of iterations were indicators reflecting segmentation performance of FBFCM. The region of interest (ROI) on the segmented image was used to study the patient’s cerebral aqueduct, foramen magnum, and C2 level of the cerebrospinal fluid velocity and flow, to analyze the characteristics of the occurrence of communicative hydrocephalus. It was indicated that average Epc of FBFCM algorithm was 0.9321 ± 0.0144, Epe was 0.1126 ± 0.0081, the average number of iterations was 14.42 ± 3.79, and the segmentation success rate was 96%. Moreover, the above four indicators had statistically considerable differences compared with those of the FCM algorithm and the hard clustering algorithm (HCM) ( P  < 0.05). Analysis of the cerebrospinal fluid flow rate in patients with communicative hydrocephalus found that the cerebrospinal fluid flow rate at the midbrain aqueduct of the patient increased greatly. The net flow was 0.000 ± 0.004 mL/s in the aqueduct of the midbrain, 0.001 ± 0.006 mL/s in the foramen magnum, and 0.002 ± 0.004 mL/s in the C2 layer. In summary, the FBFCM algorithm is effective in the segmentation and processing of CT images, which can further improve the effect of this diagnosis. After examination, it is concluded that the cranial cerebrospinal fluid flow rate and flow of TBI patients are improved after DC treatment, so that the patient’s condition can be effectively relieved. It has promotion value with clinical application.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold