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Study of Segmentation Techniques for Medical Images
| Content Provider | NIT Rourkela |
|---|---|
| Author | Sethi, Sachin Kumar |
| Abstract | Segmentation techniques are widely used in for the application of Medical Images. These techniques play a crucial role by automating or facilitating the delineation of anatomical structures and other regions of interest . Image Segmentation is particularly dicult due to restrictions imposed by biological variation and image acquisition . Goal of medical image segmentation is to perform operations on medical images to identify patterns in the use of interaction and develop qualitative criteria to evaluate interactive segmentation methods and extract information from it .Techniques available for segmentation are specic to application and the segment of biological detail to be studied . Number of techniques require wide use of Algorithms specically for certain segmentation procedure of medical images . From the Medical Image processing point of view the classication of segmentation techniques is on gray level and texture based techniques. Approaches have been proposed to segment CT and MR Images. In the following chapters we discuss the reviewed methods with respect to all information provided by the user and the parameters for the computational part. Medical image segmentation techniques require some form of expert supervision to provide accurate and consistent identication of anatomic structures. A novel segmentation technique was developed that combines a knowledge-based segmentation system with a contour model. This method exploits the guidance of a higher level process to robustly perform the segmentation of kind of anatomic structures. Knowledge about the anatomic structures to be segmented is dened statistically in terms of probability density functions of parameters of location, size, and image intensity. The active contour based technique outperform the standard segmentation methods due to its capacity to fully enforce the available a priori knowledge concerning the anatomic structure of interest. The active contour algorithm is suitable for integration with high-level image understanding frameworks, and providing a robust low-level segmentation tool. Studies are required to determine whether the proposed algorithm is indeed capable of providing consistently superior segmentation. |
| Related Links | http://ethesis.nitrkl.ac.in/5150/ |
| File Format | |
| Language | English |
| Publisher Date | 2013-01-01 |
| Access Restriction | Open |
| Subject Keyword | Image Processing |
| Content Type | Text |
| Educational Degree | Bachelor of Technology (B.Tech.) |
| Resource Type | Thesis |
