Medviso

[Enrichetta]

Segmentis freely available for research purposes provided that you cite relevant publications and the usage of the software in your publications according to here. Segment includes a broad range of analysis tools for MRI, CT and Myocardial perfusion SPECT images. The software package can also be used for a wide range of Radiology and Cardiology applications.

Segment is released in two formats; the Stand-alone format and the Source code format. Both formats are freely available for research purposes. The stand-alone format is the general default format for users who wants to use the software. The Source code format is for you who wants to do your own plug-ins to Segment in Matlab.

We offer Academic support contract for 900 Euro/year. With a valid support contract you can at all times contract us by email or request video conferences for assistance. We also assist you with developing additions to Segment and writing own plug-ins. Depending on the scope of request we also implement custom functionality included in the support contract. Please contact sa...@medviso.com to get more information and request a quote

We define academic research purposes as projects where the funding to the major part comes from governmental funds or donations. If answer for the examined patient is written back to the referring doctor this is considered to be clinical use and is not covered by academic research purposes. For usage not covered by academic research purposes, such as industry sponsored clinical trials, clinical or pre-clinical usage, Medviso provides commercial Software licenses.

Solution: Please contact sup...@medviso.com and provide a screenshot of the error message you get when the installation agent fails to launch. The support team will assist you with the installation process.

Solution: Ensure that the services Segment Sorter Server, Segment Storage Server and Segment Sync are not running before upgrading. For more instructions on how to do this, please refer to Software Installation Manual.

Solution: This issue was reported to us by users using the anti-virus software from McAfee. McAfee has an add-on called Access Protection. This feature is known to flag certain installer files. Try to temporarily disable or uninstall Access Protection and run the installation file again. Access Protection can then be enabled or reinstalled after the installation completes. For more information about disabling this feature, please refer to the McAfee support site.

This means that the software is unable to connect to Medviso license server. The computer needs to have a working Internet connection. If you are connected to the Internet, then the most likely cause is that there is some kind of security setting on your machine that blocks this communication.

Solution: Segment does not run natively on Mac. However, we had positive feedback from users who have set up dual booting on their Mac, or used a virtual machine such as Parallels, in order to be able to run Segment on Windows. Mac computers have a native utility tool to set up dual booting called Boot Camp Assistant. On the other hand, Parallels is, among others, a software that you can use to emulate a Windows environment. It is up to you to choose which solution suits you best.

Please note that you will not be able to use our latest fully automatic AI-based tools for LV and RV segmentation since they require a specific type of graphic card that is not available for Mac. However, you will be able to use our semi-automatic AI-based tools for segmentation.

Proper referencing of Segment when publishing scientific results is a prerequisite for using Segment. This is vital. We are dependent on proper citations in order to continue to release the software freely available for researchers.

Please send full bibliographic information (such as the Pubmed link) of your final work, when published or accepted for publication, to sup...@medviso.com. Please see the list of researchers who has already remembered to give us credit by a proper citation in our publications list.

A reference should encompass both the name Segment, and a suitable publication. When in doubt, please send an email to sup...@medviso.com or put reference [1] which is the generic reference for image analysis in Segment. This open-access paper describes Segment and its potential uses.

Note that referencing the software is mandatory also for abstracts to scientific conferences. If shortage of space, at least reference the software as something like:

Images were analysed using Segment (Medviso).

In extreme shortage of space, such as conferences where the word limit is less than 350 words, then reference may be omitted in the abstract text, but should be included in the oral presentation and / or poster.

[2] K. Berggren, E. Hedstrom, K. Steding Ehrenborg, M. Carlsson, H. Engblom, E. Ostenfeld, J. Jogi, D. Atar, U. Ekelund, H. Arheden, E.Heiberg, Multiple Convolutional Neural Networks for Robust Myocar-dial Segmentation. In proceedings of SSBA 2020

[3] J. Tufvesson, E. Hedstrom, K. Steding-Ehrenborg, M. Carlsson, H. Arheden, and E. Heiberg, Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging, Biomed Res Int, 2015:970357.

The current algorithm for infarct quantification is EWA and should be referenced as [6]. The old weighted version should be referenced as [7]. Measurement of endocardial extent should be referenced to as [8]. Gray zone analysis should be referenced as gray zone analysis using weighted method using either [6] or [7] as reference. If the ROI based gray zone algorithm is used then the algorithm should be referred to as [9].

[6] H. Engblom, J. Tufvesson, R. Jablonowski, M. Carlsson, A. H. Aletras, P. Hoffmann, A. Jacquier, F. Kober, B. Metzler, D. Erlinge, D. Atar, H. Arheden, and E. Heiberg, A new automatic algorithm for quantification of myocardial infarction imaged by late gadolinium enhancement cardiovascular magnetic resonance: experimental validation and comparison to expert delineations in multi-center, multi-vendor patient data, J Cardiovasc Magn Reson 18(1) p 27, 2016.

[7] E. Heiberg, M. Ugander, H. Engblom, M. Gtberg, G. K. Olivecrona, D. Erlinge, and H. Arheden, Automated quantification of myocardial infarction from MR images by accounting for partial volume effects: animal, phantom, and human study, Radiology 246(2) pp. 581-8, 2008.

[8] H. Engblom, M. B. Carlsson, E. Hedstrom, E. Heiberg, M. Ugander, G. S. Wagner, and H. Arheden, The endocardial extent of reperfused first-time myocardial infarction is more predictive of pathologic Q waves than is infarct transmurality: a magnetic resonance imaging study, Clin Physiol Funct Imaging 27(2) pp. 101-8, 2007.

[9] Wu KC, Gerstenblith G, Guallar E, Marine JE, Dalal D, Cheng A, Marbn E, Lima JAC, Tomaselli GF, Weiss RG. Combined cardiac MRI and C-reactive protein levels identify a cohort at low risk for defibrillator firings and death. Circ Cardiovasc Imaging 2012; 5:178-86. PMCID:PMC3330427

The underlying algorithm for the new Strain MITT module is given in, and should be referenced as, [11]. The underlying algorithm for the first generation Strain module is given in, and should be referenced as, [12] or [13]. The clinical reproducibility of feature tracking in cine MRI is reported in [14].

[15] J. Sjogren, J. F. Ubachs, H. Engblom, M. Carlsson, H. Arheden, and E. Heiberg, Semi-automatic segmentation of myocardium at risk in T2-weighted cardiovascular magnetic resonance, J Cardiovasc Magn Reson 14(1) p 10, 2012.

[16] J. Tufvesson, M. Carlsson, A. H. Aletras, H. Engblom, J. F. Deux, S. Koul, P. Sorensson, J. Pernow, D. Atar, D. Erlinge, H. Arheden, and E. Heiberg, Automatic segmentation of myocardium at risk from contrast enhanced SSFP CMR: validation against expert readers and SPECT, BMC Med Imaging 16 p 19, 2016.

[17]P. A. Cain, M. Ugander, J. Palmer, M. Carlsson, E. Heiberg, and H. Arheden, Quantitative polar representation of left ventricular myocardial perfusion, function and viability using SPECT and cardiac magnetic resonance: initial results, Clin Physiol Funct Imaging 25(4) pp. 215-22, 2005

[18] S. Bidhult, C. G. Xanthis, L. L. Liljekvist, G. Greil, E. Nagel, A. H. Aletras, E. Heiberg, E. Hedstrm, Validation of a New T2* Algorithm and Its Uncertainty Value for Cardiac and Liver Iron Load Determination from MRI Magnitude Images. Magn Reson Med, May 22, 2015.

[19] S. Bidhult, G. Kantasis, A. H. Aletras, H. Arheden, E. Heiberg, and E. Hedstrom, Validation of T1 and T2 algorithms for quantitative MRI: performance by a vendor-independent software, BMC Med Imaging 16(1) p 46, 2016.

Quantification of LV mass in SPECT images should be referenced to with reference [22]. Quantification myocardium at risk in SPECT images should be referenced to with reference [23]. Quantification of LV volumes in SPECT images should be referenced to with reference [24]. Quantification of ischemia in SPECT images should be referenced to with reference [25].

[22] H. Soneson, J. F. Ubachs, M. Ugander, H. Arheden, and E. Heiberg, An Improved Method for Automatic Segmentation of the Left Ventricle in Myocardial Perfusion SPECT, J Nucl Med 50(2) pp. 205-13, 2009.

[23] H. Soneson, H. Engblom, E. Hedstrom, F. Bouvier, P. Sorensson, J. Pernow, H. Arheden, and E. Heiberg, An automatic method for quantification of myocardium at risk from myocardial perfusion SPECT in patients with acute coronary occlusion, J Nucl Cardiol 17(5) pp. 831-40, 2010.

[24] H. Soneson, F. Hedeer, C. Arevalo, M. Carlsson, H. Engblom, J. F. Ubachs, H. Arheden, and E. Heiberg, Development and validation of a new automatic algorithm for quantification of left ventricular volumes and function in gated myocardial perfusion SPECT using cardiac magnetic resonance as reference standard, J Nucl Cardiol, 2011.

[25] H. Fransson, M. Ljungberg, M. Carlsson, H. Engblom, H. Arheden, and E. Heiberg, Validation of an automated method to quantify stress-induced ischemia and infarction in rest-stress myocardial perfusion SPECT, J Nucl Cardiol, 21(3) pp 503-18 2014.

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