Systematic Parameterization, Storage, and Representation of Volumetric DICOM Data

Tomographic medical imaging systems produce hundreds to thousands of slices, enabling three-dimensional (3D) analysis. Radiologists process these images through various tools and techniques in order to generate 3D renderings for various applications, such as surgical planning, medical education, and volumetric measurements. To save and store these visualizations, current systems use snapshots or video exporting, which prevents further optimizations and requires the storage of significant additional data. The Grayscale Softcopy Presentation State extension of the Digital Imaging and Communications in Medicine (DICOM) standard resolves this issue for two-dimensional (2D) data by introducing an extensive set of parameters, namely 2D Presentation States (2DPR), that describe how an image should be displayed. 2DPR allows storing these parameters instead of storing parameter applied images, which cause unnecessary duplication of the image data. Since there is currently no corresponding extension for 3D data, in this study, a DICOM-compliant object called 3D presentation states (3DPR) is proposed for the parameterization and storage of 3D medical volumes. To accomplish this, the 3D medical visualization process is divided into four tasks, namely pre-processing, segmentation, post-processing, and rendering. The important parameters of each task are determined. Special focus is given to the compression of segmented data, parameterization of the rendering process, and DICOM-compliant implementation of the 3DPR object. The use of 3DPR was tested in a radiology department on three clinical cases, which require multiple segmentations and visualizations during the workflow of radiologists. The results show that 3DPR can effectively simplify the workload of physicians by directly regenerating 3D renderings without repeating intermediate tasks, increase efficiency by preserving all user interactions, and provide efficient storage as well as transfer of visualized data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40846-015-0097-5) contains supplementary material, which is available to authorized users

Long noncoding RNA ERICD interacts with ARID3A via E2F1 and regulates migration and proliferation of osteosarcoma cells

PMID = 3274976

Kinetic modeling of liquid-phase adsorption of Congo red dyeusing guava leaf-based activated carbon

Guava leaf, a waste material, was treated andactivated to prepare adsorbent. The adsorbent was char-acterized using Scanning Electron Microscopy (SEM),Fourier Transform Infra Red (FTIR) and Energy-Disper-sive X-ray (EDX) techniques. The carbonaceous adsorbentprepared from guava leaf had appreciable carbon content(86.84 %). The adsorption of Congo red dye onto guavaleaf-based activated carbon (GLAC) was studied in thisresearch. Experimental data were analyzed by four differ-ent model equations: Langmuir, Freundlich, Temkin andDubinin–Radushkevich isotherms and it was found to fitFreundlich equation most. Adsorption rate constants weredetermined using pseudo-first-order, pseudo-second-order,Elovich and intraparticle diffusion model equations. Theresults clearly showed that the adsorption of CR dye ontoGLAC followed pseudo-second-order kinetic model.Intraparticle diffusion was involved in the adsorption pro-cess. The mean energy of adsorption calculated from D-Risotherm confirmed the involvement of physical adsorp-tion. Thermodynamic parameters were obtained and it wasfound that the adsorption of CR dye onto GLAC was anexothermic and spontaneous process at the temperaturesunder investigation. The maximum adsorption of CR dyeby GLAC was found to be 47.62 mg/g. The study showsthat GLAC is an effective adsorbent for the adsorption ofCR dye from aqueous solution