ITK Snap Segmentation Projects
ITK snap segmentation projects are an interactive software application that allow user to navigate 3D medical images manually delegate anatomical region of interest and perform automatic image segmentation. ITK snap segmentation projects are the process of identifying and classify data found in digital sample representation. We design ITK snap segmentation software with clinical and basic science researcher in mind & provides user friendly interface to maintain a limited feature set to preserve feature creep. We develop and support ITK snap segmentation projects to work with magnetic resource imaging (MRI) and compared tomography (CT) data sets.
Implementing ITK SNAP Segmentation Projects:
We implemented this following technique from Springer papers.
We use this technique to determine anatomies of interest from image.
We obtain 3D model segmentation &triangle reduction.
Required for graphics & haptic rendering.
We apply this technique to magnetic resonance imaging (MRI) or computed tomography to obtain 3D model from medical data.
Haptic simulation in ITK snap segmentation Projects:
Sensimmer: Sensimmer platform represent ongoing evolution of immersive touch for simultaneous Haptic & 3D model graphic rendering.We extract model from MRI or CT scans. We convert collected segment image to 3D volume & further transformed into polygonal surface.
Software tools: We implement following software tools for student project are:
Visualization toolkit: We support advanced visualization & volume processing algorithm in which visualization toolkit is an open source software package. We construct visualization pipeline with data and process objects.
ITK: It is an open source software package which is the segmentation of 3D anatomical structure from medical images.
Uses of ITK snap segmentation: We developed more than 80+ projects with ITK snap segmentation and uses given as: Validate as highly reliable tool in context of child autism neuroimaging study. Perform segmentation as semi automated procedure.
Use two 3D active contour segmentation methods are: Region competition: Driven by intensity regions. Geodesic active contours: Driven by intensity edges.
3D model of medical Image: We developed 3D model in medical image for B.TECH students. It contain following stages are:
Segmentation: Freely available source code actively developed as growing community of users. Friendly user interface by user guide segmentation process in semi automatic manner. Ensure methods for image preprocessing are intensity region & image edges.
Model optimization: It solved major problem in model optimization. First is degree of decimation applied to iso surface from segmented data. Second is number of smoothing iteration applied.
Additional preprocessing in ITK SNAP SEGEMENTATION PROJECTS: We implement ventriculorstomy simulator, and perform burr hole using Boolean operation in VTK in place of 3Ds max.
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