1998
DOI: 10.3109/14639239809001400
|View full text |Cite
|
Sign up to set email alerts
|

A JAVA environment for medical image data analysis: Initial application for brain PET quantitation

Abstract: Analysis software for medical image data tends to be expensive and usable only in a restricted environment. Therefore the aim of the current project was to implement a flexible framework for medical image processing and visualization which is portable among platforms and open to different data formats including DICOM 3.0. The software was designed as a set of tools which encapsulate specialized functionality. The tools are full stand alone applications, but they are also able to present a co-operating environm… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
102
0

Year Published

2002
2002
2009
2009

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 141 publications
(104 citation statements)
references
References 4 publications
0
102
0
Order By: Relevance
“…MRTM2 parametric imaging was performed by voxelwise weighted linear least-squares fitting with weights equal to the inverse of the data variance. The data variance was obtained by the method based on the noise equivalent counts (Pajevic et al, 1998) implemented in pixelwise modeling software, PMOD [version 2.5, PMOD group, Zurich, Switzerland (Mikolajczyk et al, 1998)]. …”
Section: Methodsmentioning
confidence: 99%
“…MRTM2 parametric imaging was performed by voxelwise weighted linear least-squares fitting with weights equal to the inverse of the data variance. The data variance was obtained by the method based on the noise equivalent counts (Pajevic et al, 1998) implemented in pixelwise modeling software, PMOD [version 2.5, PMOD group, Zurich, Switzerland (Mikolajczyk et al, 1998)]. …”
Section: Methodsmentioning
confidence: 99%
“…The raw data were reconstructed using the iterative one pass listmode-expectation maximisation (OPL-EM) algorithm (0.5 mm bin size, 200×200×440 matrix size) incorporating resolution recovery. Volumes of interest (VOIs) were subsequently placed on various tissue areas using the software PMOD [11]. The uptake values were expressed in kBq/ml using the syringe calibration.…”
Section: Methodsmentioning
confidence: 99%
“…Promising results for staging patients with prostate carcinoma have been reported with labelled choline compounds. Some studies have used carbon-11 labelled choline [4,5,6], whose clinical usefulness is limited by the short half-life of 11 C. This problem is overcome by 18 F-labelled choline (FCH), which has recently been introduced and has also shown promising results in the evaluation of patients with prostate cancer [7,8,9,10]. For every tumour imaging compound it is important to know the accumulation characteristics in non-tumorous lesions, of which inflammatory/infectious foci are among the most important.…”
Section: Introductionmentioning
confidence: 99%
“…Quantification of PET and MR data was done using PMOD [12] on digitized images as described in detail in our recent publication [13]. For calculation of the MR tumor volume we used the FLAIR sequence which provides the best delineation between tumor and adjacent brain [3,14].…”
Section: Patientsmentioning
confidence: 99%