Mulrecon is a web-based platform independent imaging viewer that enables generation of multiplanar reconstruction (MPR) from a stack of DICOM or JPEG images that can be manipulated as in a Picture Archiving and Communication System (PACS). The viewer supports DICOM as well as JPEG files as image stacks.
Link to stand-alone viewer here.
The source code of Mulrecon is available under the LGPLv3 licence.
Mulrecon applied to various stacks from cross-sectional imaging cases can be found in the list below.
Information with regards to how to use the program with image stacks in local folders as well as image stacks placed in folders on a webserver can be found here.
Furthermore, for demonstrational purposes, a version of Mulrecon connected to a webserver has been build.
This version has a file chooser that allows users to upload a stack of JPEG images in a zip file with this stack subsequently being opened in Mulrecon. A sample image stack compressed in zip format intended for use with the above can be downloaded from the list below.
List of cases
Data referencesKirk, S., Lee, Y., Lucchesi, F. R., Aredes, N. D., Gruszauskas, N., Catto, J., … Lemmerman, J. (2016). Radiology Data from The Cancer Genome Atlas Urothelial Bladder Carcinoma [TCGA-BLCA] collection. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2016.8LNG8XDR
Open Access Series of Imaging Studies (OASIS): Longitudinal MRI Data in Nondemented and Demented Older Adults Marcus, DS, Fotenos, AF, Csernansky, JG, Morris, JC, Buckner, RL, 2010. Journal of Cognitive Neuroscience, 22, 2677-2684.
Linehan, M., Gautam, R., Kirk, S., Lee, Y., Roche, C., Bonaccio, E., … Jarosz, R. (2016). Radiology Data from The Cancer Genome Atlas Cervical Kidney renal papillary cell carcinoma [KIRP] collection. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2016.ACWOGBEF
National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC). (2018). Radiology Data from the Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme [CPTAC-GBM] collection [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/k9/tcia.2018.3rje41q1