Method of generating multiple sets of experimental phantom data.

نویسندگان

  • Arkadiusz Sitek
  • Bryan W Reutter
  • Ronald H Huesman
  • Grant T Gullberg
چکیده

UNLABELLED Currently, 2 types of phantoms (physical and computer generated) are used for testing and comparing tomographic reconstruction methods. Data from physical phantoms include all physical effects associated with the detection of radiation. However, with physical phantoms it is difficult to control the number of detected counts, simulate the dynamics of uptake and washout, or create multiple noise realizations of an acquisition. Computer-generated phantoms can overcome some of the disadvantages of physical phantoms, but simulation of all factors affecting the detection of radiation is extremely complex and in some cases impossible. To overcome the problems with both types of phantoms, we developed a physical and computer-generated hybrid phantom that allows the creation of multiple noise realizations of tomographic datasets of the dynamic uptake governed by kinetic models. METHODS The method is phantom and camera specific. We applied it to an anthropomorphic torso phantom with a cardiac insert, using a SPECT system with attenuation correction. First, real data were acquired. For each compartment (heart, blood pool, liver, and background) of the physical phantom, large numbers of short tomographic projections were acquired separately for each angle. Sinograms were built from a database of projections by summing the projections of each compartment of the phantom. The amount of activity in each phantom compartment was regulated by the number of added projections. Sinograms corresponding to various projection times, configurations and numbers of detector heads, numbers of noise realizations, numbers of phantom compartments, and compartment-specific time-activity curves in MBq/cm3 were assembled from the database. RESULTS The acquisition produced a database of 120 projection angles ranging over 360 degrees . For each angle, 300 projections of 0.5 s each were stored in 128 x 128 matrices for easy access. The acquired database was successful in the generation of static and dynamic sinograms for which the myocardial uptake and washout was governed by a compartment kinetic model. CONCLUSION A method has been developed that allows creation of sinograms of physical phantoms with the capacity to control the number of noise realizations, the level of noise, the dynamics of uptake in the phantom compartments, and the acquisition parameters and acquisition modes.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Effects of Student-Generated MCQs on their Academic Achievement

Introduction: Involvement of students in exam questions generating is a technique that has been recently used in order to increase learning and improve academic achievement. This study aimed to investigate the effects of multiple choice questions (MCQ) generating by students on their academic achievement in Ahvaz Jundishapur University of Medical Sciences in 2014-15 academic years. Methods: Thi...

متن کامل

Gamma Knife Simulation Using the MCNP4C Code and the Zubal Phantom and Comparison with Experimental Data

Introduction: Gamma Knife is an instrument specially designed for treating brain disorders. In Gamma Knife, there are 201 narrow beams of cobalt-60 sources that intersect at an isocenter point to treat brain tumors. The tumor is placed at the isocenter and is treated by the emitted gamma rays. Therefore, there is a high dose at this point and a low dose is delivered to the normal tissue surroun...

متن کامل

Solubility Prediction of Drugs in Supercritical Carbon Dioxide Using Artificial Neural Network

The descriptors computed by HyperChem® software were employed to represent the solubility of 40 drug molecules in supercritical carbon dioxide using an artificial neural network with the architecture of 15-4-1. The accuracy of the proposed method was evaluated by computing average of absolute error (AE) of calculated and experimental logarithm of solubilities. The AE (±SD) of data sets was 0.4 ...

متن کامل

Solubility Prediction of Drugs in Supercritical Carbon Dioxide Using Artificial Neural Network

The descriptors computed by HyperChem® software were employed to represent the solubility of 40 drug molecules in supercritical carbon dioxide using an artificial neural network with the architecture of 15-4-1. The accuracy of the proposed method was evaluated by computing average of absolute error (AE) of calculated and experimental logarithm of solubilities. The AE (±SD) of data sets was 0.4 ...

متن کامل

RANDOM FUZZY SETS: A MATHEMATICAL TOOL TO DEVELOP STATISTICAL FUZZY DATA ANALYSIS

Data obtained in association with many real-life random experiments from different fields cannot be perfectly/exactly quantified.hspace{.1cm}Often the underlying imprecision can be suitably described in terms of fuzzy numbers/\values. For these random experiments, the scale of fuzzy numbers/values enables to capture more variability and subjectivity than that of categorical data, and more accur...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Journal of nuclear medicine : official publication, Society of Nuclear Medicine

دوره 47 7  شماره 

صفحات  -

تاریخ انتشار 2006