Conditions for global convergency of spirit reconstruction in PMRI (Record no. 6577)

MARC details
000 -LEADER
fixed length control field 02215nam a22001937a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220107122853.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190711b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency IIITMK
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Dhanya P Raj (17MBE0015)
9 (RLIN) 16207
245 ## - TITLE STATEMENT
Title Conditions for global convergency of spirit reconstruction in PMRI
300 ## - PHYSICAL DESCRIPTION
Extent Master of Technology in Biomedical Engineering 2017-2019
500 ## - GENERAL NOTE
General note Magnetic Resonance Imaging (MRI) is a non-invasive imaging modality in contrast to<br/>X-radiation (CT), MRI doesn't use radiation. additionally, MRI provides an oversized<br/>range of versatile distinction parameters. These give glorious soft tissue distinction.<br/>Over the years, MRI has improved dramatically in each imaging quality and imaging<br/>speed. This revolutionized the sphere of diagnostic medication. However, imaging<br/>speed that is crucial to several of the MRI applications remains a significant challenge.<br/>SPIR-iT is an Iterative Self Consistent Parallel Imaging Reconstruction technique.It is<br/><br/>auto-calibrating and doesn't need express estimates of the coil sensitivity maps. SPIR-<br/>iT formulates the parallel imaging reconstruction through information consistency<br/><br/>constraints. it's a general, optimum answer for coil-by-coil parallel imaging from<br/>capricious k-space trajectories.<br/>In SPIRiT reconstruction method,among the regularization strategies, the<br/>Tikhonov regularization is important due to rough Gaussianity of the information<br/>noise, the easiness to include previous data, additionally because the existence of a<br/>closed-form answer. A central issue in implementing the Tikhonov theme is that the<br/><br/>alternative of the regularization parameter and also the regularization image, that is self-<br/>addressed consistently during this paper. A new algorithmic rule is additionally planned<br/><br/>for generating the regularization image and choosing the regularization parameter.<br/>Experimental results are shown to demonstrate the performance of the algorithmic rule.<br/><br/>
502 ## - DISSERTATION NOTE
Degree type Master of Technology in Biomedical Engineering
Name of granting institution 2017-2019
Year degree granted EXT
-- Dr Joseph S Paul
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element SPIRiT
9 (RLIN) 16208
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element TIKHONOV REGULARIZATION
9 (RLIN) 16209
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element PARALLEL MAGNETIC RESONANCE IMAGING
9 (RLIN) 16210
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non Fiction IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre   11/07/2019   R-1581 11/07/2019 11/07/2019 Project Reports