search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
Huygens Localizer


Figure 2: Huygens Localizer analysis pipeline. The first three steps form the core of the analysis pipeline, where the raw image series is transformed into a table of localizations. The steps to filter the localizations and correct for drift are optional. Finally, a super-resolved image is generated on-the-fly from the table of localizations.


Materials and Methods SMLM in 2D. Te principle of SMLM


is explained in Figure 1. In short, the bio- logical object is densely labeled with a fluorescent marker, for instance by immu- nofluorescence or by expressing fluores- cent proteins. By exploiting the stochastic properties of a physical process, such as photo-activation (PALM [1,2]), fluorophore blinking (STORM, dSTORM, GSDIM [3–5]), or transient fluorophore binding (PAINT [6]), only a sparse random subset of the markers is active and visible at any given time. By imaging the sample at an appropriate rate, a time-series is obtained where each frame contains only the emis- sions of a small number of well-isolated flu- orescent molecules, which show up as spots in the shape of the PSF of the microscope. Given these sparse images, the lateral


position of the molecules can be derived in a straightforward fashion: first the spots are isolated, and then their location is determined at sub-pixel resolution. Te latter can be done by computing the center-of- mass of each spot. Alternatively and more accurately, the loca- tion can be obtained by fitting an analytical model of the PSF, oſten approximated by a 2D Gaussian function. SMLM in 3D. For 3D super-resolution imaging, the axial


position of the molecules must also be derived with sub-dif- fraction precision. Tis is considerably more difficult since more information must be extracted from the noisy data. In standard wide-field detection, the distance of the fluorescent molecule to the focal plane can be derived from the size of the defocused PSF, but whether it is located above or below the focal plane is not easily determined. Tis problem can be overcome by generating an axially asymmetric PSF, such as an astigmatic PSF [10], or a double-helix PSF [11], among others. Here we focus on exploiting astigmatism, which is achieved


by inserting a cylindrical lens into the detection path of the microscope. Tis leads to an elliptically shaped PSF, with a width-to-height ratio that depends on the distance and relative position to the focal plane, thereby uniquely encoding the axial position of the emitting molecule. To derive the 3D positions of the molecules in the data, a 2D elliptical Gaussian shape is


22


Figure 4: Comparison of the relative speed of Huygens Localizer with and without GPU acceleration, compared to the open-source package Thunder- STORM. Shown are the results for fitting with LSQ and for MLE. The results are normalized to the result for ThunderSTORM running a least-squares fit algo- rithm using an Intel i5 8400 CPU.


www.microscopy-today.com • 2020 March


Figure 3: Accuracy and precision of Huygens Localizer, compared to the open-source package Thun- derSTORM. Shown are results for simulated data that contain a low- and a high-static background, respectively. Both least squares (LSQ) fitting and maximum likelihood estimation (MLE) are tested. The results are based on realistic simulations of SMLM data, which are described in detail in the Huygens Localizer white paper that can be found on the Scientific Volume Imaging website: https://svi.nl/WhitePa- pers. (A) Plot of the Jaccard index, which summarizes the accuracy in terms of true positives, false posi- tives, and false negatives. (B) Plot of the median distance between the estimated positions and the true positions of the simulated particles.


fitted to each spot, determining its position, width, and height. Te axial position can then be derived by comparing the width and the height to the values obtained using the PSF Distiller as outlined above.


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76