X-ray luminescence optical tomography (XLOT) is a promising in vivo noninvasive imaging technique. By using x-rays to irradiate nanophosphors (NPs) in imaged region, XLOT can achieve better imaging depth and higher imaging sensitivity than the widely used optical molecular tomographic imaging techniques, e.g., bioluminescence tomography (BLT) or fluorescence molecular tomography (FMT). However, compared with the anatomical imaging techniques, e.g., x-ray computed tomography (XCT), XLOT has the disadvantage of low spatial resolution limited to millimeters. To overcome the limitation, recently, many efforts have been dedicated to optimize the data acquisition schemes and improve reconstruction methods. Nevertheless, challenges remain in XLOT due to the light scattering in biological tissues and the severely ill-condition and ill-posed of the inverse problem of XLOT. To improve the spatial resolution of XLOT, inspired by super-resolution localization optical microscopy, in this work, we propose a novel imaging method, termed as SR-XLOT, which is achieved by locating the position of NPs in each frame by using the single emitter localization methods (e.g., Gaussian fitting method). After reconstructing the positions of NPs in each frame, a super-resolution XLOT image can be generated by superimposing the identified positions of NPs from all frames into one image. To evaluate the performance of the proposed SR-XLOT method, a series of numerical simulation experiments were performed. The experimental results indicate that when using SR-XLOT method, the spatial resolution of XLOT can be significantly improved, compared with the conventional reconstruction methods. As a result, the method makes it possible to implement a super-resolution XLOT imaging, which is attractive for medical diagnostic and drug research.
Ultrasound (US) is one of the major medical imaging models and has been widely applied in clinical practice. However, the spatial resolution of US is limited to approximately half-wavelength of sound wave. To address this problem, super-resolution ultrasound (SR-US) imaging technique based on single molecule localization has been proposed, which can achieve a ten-fold resolution improvement compared with the conventional US imaging techniques. But, the temporal resolution of SR-US is low. Inspired by super-resolution optical microscopy, recently, a super-resolution optical fluctuation imaging (SOFI) method has been applied in SR-US to improve temporal resolution. However, in the previous work, SOFI is used to process B-mode US sequence (i.e., the image domain), which may affect the obtained imaging performance of SR-US. To further improve the spatial resolution of SR-US, in this work, we propose an alternative method, termed as RF-SOFI, where SOFI is used to process data in radio-frequency (RF) domain. Further, to reduce data acquisition time, here, US data are acquired by plane wave (PW) scan. To evaluate the performance of the proposed RF-SOFI method, numerical simulation experiments were performed. The results indicate that compared to the previous reported SOFI method (i.e., SOFI applied in image domain), the imaging performance of SR-US can be improved by using RF-SOFI (i.e., SOFI applied in RF domain). As a result, RF-SOFI provides the potential in fast SR-US imaging.