@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 = {<p>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.</p>},
	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 {1225,
	title = {The Orthanc Ecosystem for Medical Imaging.},
	journal = {J Digit Imaging},
	volume = {31},
	year = {2018},
	month = {2018 06},
	pages = {341-352},
	abstract = {<p>This paper reviews the components of Orthanc, a free and open-source, highly versatile ecosystem for medical imaging. At the core of the Orthanc ecosystem, the Orthanc server is a lightweight vendor neutral archive that provides PACS managers with a powerful environment to automate and optimize the imaging flows that are very specific to each hospital. The Orthanc server can be extended with plugins that provide solutions for teleradiology, digital pathology, or enterprise-ready databases. It is shown how software developers and research engineers can easily develop external software or Web portals dealing with medical images, with minimal knowledge of the DICOM standard, thanks to the advanced programming interface of the Orthanc server. The paper concludes by introducing the Stone of Orthanc, an innovative toolkit for the cross-platform rendering of medical images.</p>},
	keywords = {Diagnostic Imaging, Humans, Radiology Information Systems},
	issn = {1618-727X},
	doi = {10.1007/s10278-018-0082-y},
	author = {Jodogne, S{\'e}bastien}
}
