Unified deep learning model for predicting fundus fluorescein angiography image from fundus structure image

The prediction of fundus fluorescein angiography(FFA)images from fundus structural images is a cutting-edge research topic in ophthalmological image processing.Prediction comprises estimating FFA from fundus camera imaging,single-phase FFA from scanning laser ophthalmoscopy(SLO),and three-phase FFA also from SLO.Although many deep learning models are available,a single model can only perform one or two of these prediction tasks.To accomplish three prediction tasks using a unified method,we propose a unified deep learning model for predicting FFA images from fundus structure images using a supervised generative adversarial network.The three prediction tasks are processed as follows:data preparation,network training under FFA supervision,and FFA image prediction from fundus structure images on a test set.By comparing the FFA images predicted by our model,pix2pix,and CycleGAN,we demonstrate the remarkable progress achieved by our proposal.The high performance of our model is validated in terms of the peak signal-to-noise ratio,structural similarity index,and mean squared error.

In vivo tracking of human adipose-derived stem cells labeled with ferumoxytol in rats with middle cerebral artery occlusion by magnetic resonance imaging

Ferumoxytol, an iron replacement product, is a new type of superparamagnetic iron oxide ap- proved by the US Food and Drug Administration. Herein, we assessed the feasibility of tracking transplanted human adipose-derived stem cells labeled with ferumoxytol in middle cerebral artery occlusion-injured rats by 3.0 T MRI in vivo. 1 × 104 human adipose-derived stem cells labeled with ferumoxytol-heparin-protamine were transplanted into the brains of rats with middle cerebral artery occlusion. Neurologic impairment was scored at 1, 7, 14, and 28 days after transplantation. T2-weighted imaging and enhanced susceptibility-weighted angiography were used to observe transplanted cells. Results of imaging tests were compared with results of Prussian blue staining. The modified neurologic impairment scores were significantly lower in rats transplanted with cells at all time points except I day post-transplantation compared with rats without transplantation. Regions with hypointense signals on T2-weighted and enhanced susceptibility-weighted angiography images corresponded with areas stained by Prussian blue, suggesting the presence of superparamagnetic iron oxide particles within the engrafted cells. Enhanced susceptibility-weighted angiography image exhibited better sensitivity and contrast in tracing ferumoxytol-heparin-protamine-labeled human adipose-derived stem ceils compared with T2-weighted imaging in routine MRI.

Role of 3DCT in laparoscopic total gastrectomy with spleen-preserving splenic lymph node dissection

AIM: To investigate whether computed tomography with 3D imaging (3DCT) can reduce the risks associated with laparoscopic surgery.

A comparison of cross-correlation-based and phasecorrelation-based image registration algorithms for optical coherence tomographic angiography

A large field of view is in high demand for disease diagnosis in clinical applications of optical coherence tomography(OCT)and OCT angiography(OCTA)imaging.Due to limits on the optical scanning range,the scanning speed,or the data processing speed,only a relatively small region could be acquired and processed for most of the current clinical OCT systems at one time and could generate a mosaic image of multiple adjacent small-region images with registration algorithms for disease analysis.In this work,we investigated performing cross-correlation(instead of phase-correlation)in the workflow of the Fourier–Mellin transform(FMT)method(called dual-cross-correlation-based translation and rotation registration,DCCTRR)for calculating translation and orientation offsets and compared its performance to the FMT method used on OCTA images alignment.Both phantom and in vivo experiments were implemented for comparisons,and the results quantitatively demonstrate that DCCTRR can align OCTA images with a lower overlap rate,which could improve the scanning efficiency of large-scale imaging in clinical applications.