%0 Journal Article %J Radiol Med %D 2015 %T Open source software in a practical approach for post processing of radiologic images. %A Valeri, Gianluca %A Mazza, Francesco Antonino %A Maggi, Stefania %A Aramini, Daniele %A La Riccia, Luigi %A Mazzoni, Giovanni %A Giovagnoni, Andrea %K Diagnostic Imaging %K Humans %K Image Interpretation, Computer-Assisted %K Image Processing, Computer-Assisted %K Radiology Information Systems %K Reproducibility of Results %K Sensitivity and Specificity %K Software %K Software Validation %K User-Computer Interface %X

PURPOSE: The purpose of this paper is to evaluate the use of open source software (OSS) to process DICOM images.

MATERIALS AND METHODS: We selected 23 programs for Windows and 20 programs for Mac from 150 possible OSS programs including DICOM viewers and various tools (converters, DICOM header editors, etc.). The programs selected all meet the basic requirements such as free availability, stand-alone application, presence of graphical user interface, ease of installation and advanced features beyond simple display monitor. Capabilities of data import, data export, metadata, 2D viewer, 3D viewer, support platform and usability of each selected program were evaluated on a scale ranging from 1 to 10 points.

RESULTS: Twelve programs received a score higher than or equal to eight. Among them, five obtained a score of 9: 3D Slicer, MedINRIA, MITK 3M3, VolView, VR Render; while OsiriX received 10.

CONCLUSIONS: OsiriX appears to be the only program able to perform all the operations taken into consideration, similar to a workstation equipped with proprietary software, allowing the analysis and interpretation of images in a simple and intuitive way. OsiriX is a DICOM PACS workstation for medical imaging and software for image processing for medical research, functional imaging, 3D imaging, confocal microscopy and molecular imaging. This application is also a good tool for teaching activities because it facilitates the attainment of learning objectives among students and other specialists.

%B Radiol Med %V 120 %P 309-23 %8 2015 Mar %G eng %N 3 %R 10.1007/s11547-014-0437-5 %0 Journal Article %J Cad Saude Publica %D 2015 %T Why open source? %A Carvalho, Marilia Sá %K Access to Information %K Periodicals as Topic %K Reproducibility of Results %K Software %K Software Design %B Cad Saude Publica %V 31 %P 221-2 %8 2015 Feb %G eng %N 2 %0 Journal Article %J Acta Cytol %D 2014 %T Making cytological diagnoses on digital images using the iPath network. %A Dalquen, Peter %A Savic Prince, Spasenija %A Spieler, Peter %A Kunze, Dietmar %A Neumann, Heinrich %A Eppenberger-Castori, Serenella %A Adams, Heiner %A Glatz, Katharina %A Bubendorf, Lukas %K Adolescent %K Adult %K Aged %K Aged, 80 and over %K Child %K Child, Preschool %K Computers, Handheld %K Cytodiagnosis %K Diagnosis, Differential %K Female %K Humans %K Hyperplasia %K Infant %K Male %K Metaplasia %K Middle Aged %K Neoplasms %K Observer Variation %K Reproducibility of Results %K Sensitivity and Specificity %K Telemedicine %X

BACKGROUND: The iPath telemedicine platform Basel is mainly used for histological and cytological consultations, but also serves as a valuable learning tool.

AIM: To study the level of accuracy in making diagnoses based on still images achieved by experienced cytopathologists, to identify limiting factors, and to provide a cytological image series as a learning set.

METHOD: Images from 167 consecutive cytological specimens of different origin were uploaded on the iPath platform and evaluated by four cytopathologists. Only wet-fixed and well-stained specimens were used. The consultants made specific diagnoses and categorized each as benign, suspicious or malignant.

RESULTS: For all consultants, specificity and sensitivity regarding categorized diagnoses were 83-92 and 85-93%, respectively; the overall accuracy was 88-90%. The interobserver agreement was substantial (κ = 0.791). The lowest rate of concordance was achieved in urine and bladder washings and in the identification of benign lesions.

CONCLUSION: Using a digital image set for diagnostic purposes implies that even under optimal conditions the accuracy rate will not exceed to 80-90%, mainly because of lacking supportive immunocytochemical or molecular tests. This limitation does not disqualify digital images for teleconsulting or as a learning aid. The series of images used for the study are open to the public at http://pathorama.wordpress.com/extragenital-cytology-2013/.

%B Acta Cytol %V 58 %P 453-60 %8 2014 %G eng %N 5 %R 10.1159/000369241 %0 Journal Article %J PLoS One %D 2010 %T JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections. %A Ribes, Delphine %A Parafita, Julia %A Charrier, Rémi %A Magara, Fulvio %A Magistretti, Pierre J %A Thiran, Jean-Philippe %K Animals %K Autoradiography %K Brain %K Carbon Radioisotopes %K Deoxyglucose %K Image Processing, Computer-Assisted %K Imaging, Three-Dimensional %K Male %K Maze Learning %K Mice %K Mice, Inbred C57BL %K Reproducibility of Results %K Software %X

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

%B PLoS One %V 5 %P e14094 %8 2010 %G eng %N 11 %R 10.1371/journal.pone.0014094 %0 Journal Article %J BMC Med Imaging %D 2010 %T An open-source software tool for the generation of relaxation time maps in magnetic resonance imaging. %A Messroghli, Daniel R %A Rudolph, Andre %A Abdel-Aty, Hassan %A Wassmuth, Ralf %A Kuhne, Titus %A Dietz, Rainer %A Schulz-Menger, Jeanette %K Algorithms %K Humans %K Image Enhancement %K Image Interpretation, Computer-Assisted %K Magnetic Resonance Imaging %K Programming Languages %K Reproducibility of Results %K Sensitivity and Specificity %K Software %X

BACKGROUND: In magnetic resonance (MR) imaging, T1, T2 and T2* relaxation times represent characteristic tissue properties that can be quantified with the help of specific imaging strategies. While there are basic software tools for specific pulse sequences, until now there is no universal software program available to automate pixel-wise mapping of relaxation times from various types of images or MR systems. Such a software program would allow researchers to test and compare new imaging strategies and thus would significantly facilitate research in the area of quantitative tissue characterization.

RESULTS: After defining requirements for a universal MR mapping tool, a software program named MRmap was created using a high-level graphics language. Additional features include a manual registration tool for source images with motion artifacts and a tabular DICOM viewer to examine pulse sequence parameters. MRmap was successfully tested on three different computer platforms with image data from three different MR system manufacturers and five different sorts of pulse sequences: multi-image inversion recovery T1; Look-Locker/TOMROP T1; modified Look-Locker (MOLLI) T1; single-echo T2/T2*; and multi-echo T2/T2*. Computing times varied between 2 and 113 seconds. Estimates of relaxation times compared favorably to those obtained from non-automated curve fitting. Completed maps were exported in DICOM format and could be read in standard software packages used for analysis of clinical and research MR data.

CONCLUSIONS: MRmap is a flexible cross-platform research tool that enables accurate mapping of relaxation times from various pulse sequences. The software allows researchers to optimize quantitative MR strategies in a manufacturer-independent fashion. The program and its source code were made available as open-source software on the internet.

%B BMC Med Imaging %V 10 %P 16 %8 2010 %G eng %R 10.1186/1471-2342-10-16