REFINED APPROACH FOR AUTOMATIC SEGMENTATION OF SPINAL CANALS

摘要

Accurate extraction and analysis of features of spinal canal is very important for early diagnosis of diseases that affect spine.This is usually done using Computed Tomography(CT)images.Main issues with these images are that they can be of poor illumination or different orientations.In our system,we use Contrast Limited Adaptive Histogram Equalisation(CLAHE)method to improve the poor illumination.The automatic segmentation has more accuracy than the manual segmentation and also the time required for the process is less when compared to the manual segmentation.Finally,the spinal canal is extracted and the shape is determined.So with minimum effort and time,accurate diagnosis of spinal curvature disorder can be found.This proposed method can accurately extract and analyse features from CT Sagittal images and will help in the early diagnosis of the disease.Scoliosis is a deformity of spinal column and trunk,which is usually very painful.It can even affect the optimal functioning of the heart and lungs of the patient.Though,it is not a life-threatening disease,scoliosis is a disease for which no cure or cause has been identified.The key question related to scoliosis is that how a small deformity,which does not require treatment,ends up as a large deformity with surgical intervention as time progress.In critical cases,it may require spinal fusion surgery,which may have a post-operation complication as it affects the spinal flexibility.It is highly important to identify which minor deformities will eventually result in major deformities.To analysis,the minor deformities automatic segmentation of the spinal image is required,as the larger scale view of the spinal image cannot effectively help in the diagnosis of minor deformities in the spinal canal.The Automatic Spinal Canal segmentation(ASCS)should necessarily belp in effective diagnosis of the disease.In the proposed system for preprocessing,we employ CLAHE for segmentation we use K-means clustering and for post-processing technique,we use Active Contour model(ACM).