| Type of Material: | Thesis |
| Title: | 3D image segmentation using multiresolution and wavelwts |
| Researcher: | M NIVAS |
| Guide: | M. RAMAKRISHNAN |
| Department: | Department of Engineering and Technology(Computer Science and Engineering) |
| Publisher: | Bharath University, Chennai |
| Place: | Chennai |
| Year: | 2016 |
| Language: | English |
| Subject: | Acquisition Systems | Positron emission tomography | Magnetic resonance imaging | Computed Tomography | Thresholding | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai; 2016 |
| Fulltext: | Shodhganga |
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| 003 | IN-AhILN | |
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| 008 | __ | 240917t2016||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_454602 |
| 040 | __ | |aBHAU_600073|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aM NIVAS|eResearcher |
| 110 | __ | |aDepartment of Engineering and Technology(Computer Science and Engineering)|bBharath University, Chennai|dChennai|ein |
| 245 | __ | |a3D image segmentation using multiresolution and wavelwts |
| 260 | __ | |aChennai|bBharath University, Chennai|c2016 |
| 300 | __ | |dDVD |
| 502 | __ | |bPhD|d2016|cDepartment of Engineering and Technology(Computer Science and Engineering), Bharath University, Chennai, Chennai |
| 518 | __ | |oDate of Registration|d2008-08-13 |
| 520 | __ | |aMedical volume segmentation obtained the attraction of numerous researchers; as a result, several techniques have been implemented in terms of medical imaging including segmentations and other imaging processes. This research work focuses on an implementation of segmentation system which employs the Multiresolution analysis (MRA) techniques together or on their own to segment medical volumes, the system acquires a stack of 2D slices or a complete 3D volumes acquired from medical scanners as a data input. It aims at developing an automatic image segmentation scheme for categorizing region of interest (ROI) in medical images which are attained from diverse medical scanners such as PET, CT or MRI. Two major schemes have been implemented in this research for segmenting medical volume. The first approach employs 2D wavelet, Ridgelet and Curvelet transforms based (MRA) techniques for segmenting medical volume. It is mainly a tough task to classify cancers in the scanners output of the human organs by means of sha |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aAcquisition Systems |
| 653 | __ | |aPositron emission tomography |
| 653 | __ | |aMagnetic resonance imaging |
| 653 | __ | |aComputed Tomography |
| 653 | __ | |aThresholding |
| 700 | __ | |aM. RAMAKRISHNAN|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/170934|yShodhganga |
| 905 | __ | |afromsg |
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