@article {1304, title = {iBEX: Modular Open-Source Software for Digital Radiography.}, journal = {J Digit Imaging}, volume = {33}, year = {2020}, month = {2020 06}, pages = {708-721}, abstract = {

A device-independent software package, named iBEX, is developed to accelerate the research and development efforts for X-ray imaging setups such as chest radiography, linear and multidirectional tomography, and dental and skeletal radiography. Its extension mechanism makes the software adaptable for a wide range of digital X-ray imaging hardware combinations and provides capabilities for researchers to develop image processing plug-ins. Independent of the X-ray sensor technology, iBEX could integrate with heterogeneous communication channels of digital detectors. iBEX is a freeware option for preclinical and early clinical testing of radiography devices. It provides tools to calibrate the device, integrate to health information infrastructure, acquire image, store studies on local storage, and send them to Picture Archiving and Communication System (PACS). iBEX is a unique open-source project bringing X-ray imaging devices{\textquoteright} software into the scope of the open-source community to reduce the X-ray scanners{\textquoteright} research effort, potentially increase the image quality, and cut down the production and testing costs of radiography devices.

}, keywords = {Humans, Image Processing, Computer-Assisted, Radiographic Image Enhancement, Radiology Information Systems, Software, Tomography, X-Ray Computed}, issn = {1618-727X}, doi = {10.1007/s10278-019-00304-1}, author = {Brusan, Altay and Durmaz, F Ayta{\c c} and Yaman, Alper and {\"O}zt{\"u}rk, Cengizhan} } @article {1287, title = {Landmark detection in 2D bioimages for geometric morphometrics: a multi-resolution tree-based approach.}, journal = {Sci Rep}, volume = {8}, year = {2018}, month = {2018 01 11}, pages = {538}, abstract = {

The detection of anatomical landmarks in bioimages is a necessary but tedious step for geometric morphometrics studies in many research domains. We propose variants of a multi-resolution tree-based approach to speed-up the detection of landmarks in bioimages. We extensively evaluate our method variants on three different datasets (cephalometric, zebrafish, and drosophila images). We identify the key method parameters (notably the multi-resolution) and report results with respect to human ground truths and existing methods. Our method achieves recognition performances competitive with current existing approaches while being generic and fast. The algorithms are integrated in the open-source Cytomine software and we provide parameter configuration guidelines so that they can be easily exploited by end-users. Finally, datasets are readily available through a Cytomine server to foster future research.

}, keywords = {Algorithms, Animals, Body Weights and Measures, Drosophila, Humans, Image Processing, Computer-Assisted, Software, Zebrafish}, issn = {2045-2322}, doi = {10.1038/s41598-017-18993-5}, author = {Vandaele, R{\'e}my and Aceto, Jessica and Muller, Marc and P{\'e}ronnet, Fr{\'e}d{\'e}rique and Debat, Vincent and Wang, Ching-Wei and Huang, Cheng-Ta and Jodogne, S{\'e}bastien and Martinive, Philippe and Geurts, Pierre and Mar{\'e}e, Rapha{\"e}l} } @article {987, title = {Open source software in a practical approach for post processing of radiologic images.}, journal = {Radiol Med}, volume = {120}, year = {2015}, month = {2015 Mar}, pages = {309-23}, abstract = {

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.

}, keywords = {Diagnostic Imaging, Humans, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Radiology Information Systems, Reproducibility of Results, Sensitivity and Specificity, Software, Software Validation, User-Computer Interface}, issn = {1826-6983}, doi = {10.1007/s11547-014-0437-5}, author = {Valeri, Gianluca and Mazza, Francesco Antonino and Maggi, Stefania and Aramini, Daniele and La Riccia, Luigi and Mazzoni, Giovanni and Giovagnoni, Andrea} } @article {1026, title = {Simplifying electronic data capture in clinical trials: workflow embedded image and biosignal file integration and analysis via web services.}, journal = {J Digit Imaging}, volume = {27}, year = {2014}, month = {2014 Oct}, pages = {571-80}, abstract = {

To improve data quality and save cost, clinical trials are nowadays performed using electronic data capture systems (EDCS) providing electronic case report forms (eCRF) instead of paper-based CRFs. However, such EDCS are insufficiently integrated into the medical workflow and lack in interfacing with other study-related systems. In addition, most EDCS are unable to handle image and biosignal data, although electrocardiography (EGC, as example for one-dimensional (1D) data), ultrasound (2D data), or magnetic resonance imaging (3D data) have been established as surrogate endpoints in clinical trials. In this paper, an integrated workflow based on OpenClinica, one of the world{\textquoteright}s largest EDCS, is presented. Our approach consists of three components for (i) sharing of study metadata, (ii) integration of large volume data into eCRFs, and (iii) automatic image and biosignal analysis. In all components, metadata is transferred between systems using web services and JavaScript, and binary large objects (BLOBs) are sent via the secure file transfer protocol and hypertext transfer protocol. We applied the close-looped workflow in a multicenter study, where long term (7~days/24~h) Holter ECG monitoring is acquired on subjects with diabetes. Study metadata is automatically transferred into OpenClinica, the 4~GB BLOBs are seamlessly integrated into the eCRF, automatically processed, and the results of signal analysis are written back into the eCRF immediately.

}, keywords = {Algorithms, Automatic Data Processing, Clinical Trials as Topic, Database Management Systems, Humans, Image Processing, Computer-Assisted, Information Storage and Retrieval, Internet, Medical Records Systems, Computerized, Systems Integration, Workflow}, issn = {1618-727X}, doi = {10.1007/s10278-014-9694-z}, author = {Haak, Daniel and Samsel, Christian and Gehlen, Johan and Jonas, Stephan and Deserno, Thomas M} } @article {779, title = {STIR: software for tomographic image reconstruction release 2.}, journal = {Phys Med Biol}, volume = {57}, year = {2012}, month = {2012 Feb 21}, pages = {867-83}, abstract = {We present a new version of STIR (Software for Tomographic Image Reconstruction), an open source object-oriented library implemented in C++~for 3D positron emission tomography reconstruction. This library has been designed such that it can be used for many algorithms and scanner geometries, while being portable to various computing platforms. This second release enhances its flexibility and modular design and includes additional features such as Compton scatter simulation, an additional iterative reconstruction algorithm and parametric image reconstruction (both indirect and direct). We discuss the new features in this release and present example results. STIR can be downloaded from http://stir.sourceforge.net.}, keywords = {Algorithms, Animals, Computers, Image Processing, Computer-Assisted, Mice, Software, Tomography}, issn = {1361-6560}, doi = {10.1088/0031-9155/57/4/867}, author = {Thielemans, Kris and Tsoumpas, Charalampos and Mustafovic, Sanida and Beisel, Tobias and Aguiar, Pablo and Dikaios, Nikolaos and Jacobson, Matthew W} } @article {1047, title = {[Central online quality assurance in radiology: an IT solution exemplified by the German Breast Cancer Screening Program].}, journal = {Rofo}, volume = {183}, year = {2011}, month = {2011 Sep}, pages = {849-54}, abstract = {

PURPOSE: Physical-technical quality assurance is one of the essential tasks of the National Reference Centers in the German Breast Cancer Screening Program. For this purpose the mammography units are required to transfer the measured values of the constancy tests on a daily basis and all phantom images created for this purpose on a weekly basis to the reference centers. This is a serious logistical challenge. To meet these requirements, we developed an innovative software tool.

MATERIALS AND METHODS: By the end of 2005, we had already developed web-based software (MammoControl) allowing the transmission of constancy test results via entry forms. For automatic analysis and transmission of the phantom images, we then introduced an extension (MammoControl DIANA). This was based on Java, Java Web Start, the NetBeans Rich Client Platform, the Pixelmed Java DICOM Toolkit and the ImageJ library.

RESULTS: MammoControl DIANA was designed to run locally in the mammography units. This allows automated on-site image analysis. Both results and compressed images can then be transmitted to the reference center. We developed analysis modules for the daily and monthly consistency tests and additionally for a homogeneity test.

CONCLUSION: The software we developed facilitates the immediate availability of measurement results, phantom images, and DICOM header data in all reference centers. This allows both targeted guidance and short response time in the case of errors. We achieved a consistent IT-based evaluation with standardized tools for the entire screening program in Germany.

}, keywords = {Data Compression, Female, Germany, Guideline Adherence, Humans, Image Processing, Computer-Assisted, Mammography, Mass Screening, Online Systems, Phantoms, Imaging, Quality Assurance, Health Care, Radiology Information Systems, Reference Standards, Software}, issn = {1438-9010}, doi = {10.1055/s-0031-1281599}, author = {Czwoydzinski, J and Girnus, R and Sommer, A and Heindel, W and Lenzen, H} } @article {611, title = {Evaluation of adaptive radiotherapy of bladder cancer by image-based tumour control probability modelling.}, journal = {Acta oncologica (Stockholm, Sweden)}, volume = {49}, year = {2010}, month = {2010 Oct}, pages = {1045-51}, abstract = {Clinical implementation of adaptive radiotherapy strategies could benefit from extended tools for plan evaluation and selection. For this purpose we investigated the feasibility of image-based tumour control probability (TCP) modelling using the bladder as example of a tumour site with potential benefit from adaptive strategies.}, keywords = {Carcinoma, Computer Simulation, Humans, Image Processing, Computer-Assisted, Models, Statistical, Probability, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted, Radiotherapy, Conformal, Tumor Burden, Urinary Bladder, Urinary Bladder Neoplasms}, issn = {1651-226X}, author = {Wright, Pauliina and Muren, Ludvig P and H{\o}yer, Morten and Malinen, Eirik} } @article {1042, title = {JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.}, journal = {PLoS One}, volume = {5}, year = {2010}, month = {2010}, pages = {e14094}, abstract = {

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.

}, keywords = {Animals, Autoradiography, Brain, Carbon Radioisotopes, Deoxyglucose, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Male, Maze Learning, Mice, Mice, Inbred C57BL, Reproducibility of Results, Software}, issn = {1932-6203}, doi = {10.1371/journal.pone.0014094}, author = {Ribes, Delphine and Parafita, Julia and Charrier, R{\'e}mi and Magara, Fulvio and Magistretti, Pierre J and Thiran, Jean-Philippe} } @article {500, title = {Advances in functional and structural MR image analysis and implementation as FSL.}, journal = {NeuroImage}, volume = {23 Suppl 1}, year = {2004}, month = {2004}, pages = {S208-19}, abstract = {The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right. In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB{\textquoteright}s Software Library (FSL).}, keywords = {Bayes Theorem, Brain, Databases, Factual, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Models, Neurological, Models, Statistical, Software}, issn = {1053-8119}, author = {Smith, Stephen M and Jenkinson, Mark and Woolrich, Mark W and Beckmann, Christian F and Behrens, Timothy E J and Johansen-Berg, Heidi and Bannister, Peter R and De Luca, Marilena and Drobnjak, Ivana and Flitney, David E and Niazy, Rami K and Saunders, James and Vickers, John and Zhang, Yongyue and De Stefano, Nicola and Brady, J Michael and Matthews, Paul M} }