Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Beulah, A.
- Human Spine Structure Localization on MRI – A Survey
Abstract Views :195 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, SSN College of Engineering, Chennai - 603110, Tamil Nadu, IN
1 Department of CSE, SSN College of Engineering, Chennai - 603110, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 42 (2016), Pagination:Abstract
Objective: This study is mainly to locate all the spine structures on MR Images automatically. Localizing the vertebrae and intervertebral disc is an exacting work due to various different size and shape of the spine in different humans and abnormalities if any. Methods/Statistical Analysis: Numerous techniques for localization and labelling on MR images have been proposed during several past years. Identifying spine structures are done using intensity-based models, graphical models like Markov Random Field (MRF), probabilistic models etc. Also, machine learning approaches are used to classify the different structures of the spine. Findings: In this paper, a survey is done on different localization algorithms. This paper also describes their key ideas, features, the advantages, and disadvantages. Application: Also, it is identified that more future research scope is available in the area of human spine structure localization.Keywords
Human Spine Structures, Intervertebral Discs, Localization, MR Images Vertebrae.Full Text
- Lumbar Spine Classification using Pyramidal Histogram of Oriented Gradients
Abstract Views :151 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, SSN College of Engineering, Chennai - 603110, Tamil Nadu, IN
1 Department of CSE, SSN College of Engineering, Chennai - 603110, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 32 (2016), Pagination:Abstract
Objective: To diagnose any injury in the lumbar region of human spine, the classification of each vertebra and Intervertebral Disc (IVD) is the vital task. Methods: The classification of the lumbar structure is done using Pyramidal Histogram of Gradients (PHOG). The PHOG technique is applied on the MR Image to select the basic intensity level features. These features are trained with Support Vector Machine (SVM). After building a model with SVM classification algorithm, classify the MR Images for discs and vertebrae separately. Findings: The accuracy is calculated to verify the performance of this work. This classification procedure is performed on a lumbar MR image dataset which contains 960 IVDs and 800 vertebrae with T1 and T2 weighted for 80 subjects.Keywords
Classification, Intervertebral Discs, Lumbar spine, Pyramidal Histogram of Oriented Gradients (PHOG), Support Vector Machine (SVM), Vertebrae.Full Text