NDLI: A Monte Carlo approach to handling data scaling in nuclear medicine

Content Provider	IEEE Xplore Digital Library
Author	Chuanyong Bai Conwell, R. Kindem, J.
Copyright Year	2009
Description	Author affiliation: Digirad Corporation, 13950 Stowe Drive, Poway, CA 92064, USA (Chuanyong Bai; Conwell, R.; Kindem, J.)
Abstract	In medicine imaging, data scaling is sometimes desired to handle the system complexity, such as uniformity calibration. Since the data are usually saved in short integer, conventional data scaling will first scale the data in floating point format and then truncate or round the floating point data to short integer data. For example, when using truncation, scaling of 9 by 1.1 results in 9 and scaling of 10 by 1.1 results in 11. When the count level is low, such scaling may change the local data distribution and affect the intended application of the data. In this work, we use a gated cardiac SPECT study to illustrate the effect of conventional scaling by factors of 1.1 and 1.2. We then scale the data with the same scaling factors using a Monte Carlo approach in which a random number evenly distributed between 0 and 1 is generated to determine how the floating point data will be saved as short integer data. If the random number is between 0 and 0.9, then 9.9 will be saved as 10, otherwise 9. In other words, the floating point value 9.9 will be saved in short integer value as 10 with 90% probability or 9 with 10% probability. The image reconstructed from the original data showed a perfusion defect at the apex of the myocardium. The defect size was noticeably increased by scaling with 1.1 and significantly decreased by scaling with 1.2 using the conventional approach. Using the Monte Carlo approach, in contrast, the images from the scaled data appeared identical to the original image. In conclusion, conventional approaches for data scaling can lead to unexpected local count variation and significantly affect the clinical usage of the data. The proposed Monte Carlo approach minimizes the scaling-introduced local data variation and is preferred for nuclear medicine data scaling.
Starting Page	2567
Ending Page	2572
File Size	364062
Page Count	6
File Format	PDF
ISBN	9781424439614
ISSN	10957863
DOI	10.1109/NSSMIC.2009.5402021
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monte Carlo methods Nuclear medicine Calibration Biomedical imaging Pixel Nuclear and plasma sciences Random number generation Image reconstruction Myocardium Head Nuclear Medicine Data scaling Monte Carlo
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Monte Carlo calculation of Fisher information and Cramer-Rao Bounds

Reconstruction of 2D PET data with Monte Carlo generated natural pixels

Patient motion correction of SPECT images: dual scan approach

Monte Carlo volume rendering

Monte Carlo simulation of gated SPECT cardiac blood pool studies

Edge-adaptive super-resolution image reconstruction using a Markov chain Monte Carlo approach

A new approach to medical image reconstruction

Effect of the data constraint on few-view, fan-beam CT image reconstruction by TV minimization

Image reconstruction from few views by non-convex optimization

A Monte Carlo approach to handling data scaling in nuclear medicine

Similar Documents

Monte Carlo calculation of Fisher information and Cramer-Rao Bounds

Reconstruction of 2D PET data with Monte Carlo generated natural pixels

Patient motion correction of SPECT images: dual scan approach

Monte Carlo volume rendering

Monte Carlo simulation of gated SPECT cardiac blood pool studies

Edge-adaptive super-resolution image reconstruction using a Markov chain Monte Carlo approach

A new approach to medical image reconstruction

Effect of the data constraint on few-view, fan-beam CT image reconstruction by TV minimization

Image reconstruction from few views by non-convex optimization

A Monte Carlo approach to handling data scaling in nuclear medicine