Constrained Labeling of 2D Slice Data for Reading Images in Radiology

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dc.contributor.authorMogalle, Katjaen_US
dc.contributor.authorTietjen, Christianen_US
dc.contributor.authorSoza, Grzegorzen_US
dc.contributor.authorPreim, Bernharden_US
dc.contributor.editorTimo Ropinski and Anders Ynnerman and Charl Botha and Jos Roerdinken_US
dc.date.accessioned2013-11-08T10:34:22Z
dc.date.available2013-11-08T10:34:22Z
dc.date.issued2012en_US
dc.description.abstractAn important and underestimated task to support reading of images in radiology is a proper annotation of findings. In radiology reading, 2D slice images from a given modality (e.g. CT or MRI) need to be analyzed carefully by a radiologist, whereas all clinical relevant findings have to be annotated in the images. This includes information in particular for documentation, follow-up investigations and medical team meetings. The main problem of the automatic placement of labels in a clinical context is to find an arrangement of multiple variable-sized labels which guarantees readability, clearness and unambiguity and avoids occlusion of the image itself. Based on a case study of abdominal CT-Images in an oncologic context we analyze the main constraints for label placement in order to extract candidate label positions, evaluate these and determine valid and good label positions. Based on this preprocessing step, different approaches can be applied for placing multiple labels in a scene. We present a new method called Shifting and compare it to other labeling strategies.en_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicineen_US
dc.identifier.isbn978-3-905674-38-5en_US
dc.identifier.issn2070-5778en_US
dc.identifier.urihttps://doi.org/10.2312/VCBM/VCBM12/131-138en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.6 [Computer Graphics]en_US
dc.subjectMethodology and Techniquesen_US
dc.subjectInteraction techniquesen_US
dc.titleConstrained Labeling of 2D Slice Data for Reading Images in Radiologyen_US
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VCBM 12: Eurographics Workshop on Visual Computing for Biology and Medicine