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Updated: Feb 26, 2026

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis
Published on: February 1, 2022
Super-resolution imaging in a multiple layer EPID
Haijian Chen1, Joerg Rottmann1, Stephen Sf Yip1
1Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.
None:
A new portal imager consisting of four vertically stacked conventional electronic portal imaging device (EPID) layers has been constructed in pursuit of improved detective quantum efficiency (DQE). We hypothesize that super-resolution (SR) imaging can also be achieved in such a system by shifting each layer laterally by half a pixel relative to the layer above. Super-resolution imaging will improve resolution and contrast-to-noise ratio (CNR) in megavoltage (MV) planar and cone beam computed tomography (MV-CBCT) applications. Simulations are carried out to test this hypothesis with digital phantoms. To assess planar resolution, 2 mm long iron rods with 0.3 × 0.3 mm2 square cross-section are arranged in a grid pattern at the center of a 1 cm thick solid water. For measuring CNR in MV-CBCT, a 20 cm diameter digital phantom with 8 inserts of different electron densities is used. For measuring resolution in MV-CBCT, a digital phantom featuring a bar pattern similar to the Gammex™ phantom is used. A 6 MV beam is attenuated through each phantom and detected by each of the four detector layers. Fill factor of the detector is explicitly considered. Projections are blurred with an estimated point spread function (PSF) before super-resolution reconstruction. When projections from multiple shifted layers are used in SR reconstruction, even a simple shift-add fusion can significantly improve the resolution in reconstructed images. In the reconstructed planar image, the grid pattern becomes visually clearer. In MV-CBCT, combining projections from multiple layers results in increased CNR and resolution. The inclusion of two, three and four layers increases CNR by 40%, 70% and 99%, respectively. Shifting adjacent layers by half a pixel almost doubles resolution. In comparison, using four perfectly aligned layers does not improve resolution relative to a single layer.

