Unsupervised Lesion Detection via Image Restoration with a Normative Prior

Unsupervised lesion detection is a challenging problem that requires accurately estimating normative distributions of healthy anatomy and detecting lesions as outliers without training examples. Recently, this problem has received increased attention from the research community following the advances in unsupervised learning with deep learning. Such advances allow the estimation of high-dimensional distributions, such as normative distributions, with higher accuracy than previous methods.The main approach of the recently proposed methods is to learn a latent-variable model parameterized with networks to approximate the normative distribution using example images showing healthy anatomy, perform prior-projection, i.e. reconstruct the image with lesions using the latent-variable model, and determine lesions based on the differences between the reconstructed and original images. While being promising, the prior-projection step often leads to a large number of false positives. In this work, we approach unsupervised lesion detection as an image restoration problem and propose a probabilistic model that uses a network-based prior as the normative distribution and detect lesions pixel-wise using MAP estimation. The probabilistic model punishes large deviations between restored and original images, reducing false positives in pixel-wise detections. Experiments with gliomas and stroke lesions in brain MRI using publicly available datasets show that the proposed approach outperforms the state-of-the-art unsupervised methods by a substantial margin, +0.13 (AUC), for both glioma and stroke detection. Extensive model analysis confirms the effectiveness of MAP-based image restoration.Comment: Extended version of 'Unsupervised Lesion Detection via Image Restoration with a Normative Prior' (MIDL2019

Stability of Phase-modulated Quantum Key Distribution System

Phase drift and random fluctuation of interference visibility in double unbalanced M-Z QKD system are observed and distinguished. It has been found that the interference visibilities are influenced deeply by the disturbance of transmission fiber. Theory analysis shows that the fluctuation is derived from the envioronmental disturbance on polarization characteristic of fiber, especially including transmission fiber. Finally, stability conditions of one-way anti-disturbed M-Z QKD system are given out, which provides a theoretical guide in pragmatic anti-disturbed QKD.Comment: 9 pages, 3 figue

Analogue to multiple electromagnetically induced transparency in all-optical drop-filter systems

We theoretically study a parallel optical configuration which includes N periodically coupled whispering-gallery-mode resonators. The model shows an obvious effect which has a direct analogy with the phenomenon of multiple electromagnetically induced transparency in quantum systems. The numerical simulations illuminate that the frequency transparency windows are sharp and highly transparent. We also briefly discuss the experimental feasibility of the current scheme in two practical systems, microrings and microdisks.Comment: 4 pages, 4 figure

Intrinsic-Stabilization Uni-Directional Quantum Key Distribution Between Beijing and Tianjin

Quantum key distribution provides unconditional security for communication. Unfortunately, current experiment schemes are not suitable for long-distance fiber transmission because of instability or backscattering. We present a uni-directional intrinsic-stabilization scheme that is based on Michelson-Faraday interferometers, in which reflectors are replaced with 90 degree Faraday mirrors. With the scheme, key exchange from Beijing to Tianjin over 125 kilometers with an average error rate is below 6% has been achieved and its limited distance exceeds 150 kilometers. Experimental result shows the system is insensitive to environment and can run over day and night without any break even in the noise workshop.Comment: 7 pages,4 figure

Prenatal genetic diagnosis associated with fetal ventricular septal defect: an assessment based on chromosomal microarray analysis and exome sequencing

Objective: In the study, we investigated the genetic etiology of the ventricular septal defect (VSD) and comprehensively evaluated the diagnosis rate of prenatal chromosomal microarray analysis (CMA) and exome sequencing (ES) for VSD to provide evidence for genetic counseling.Methods: We carried out chromosomal microarray analysis (CMA) on 468 fetuses with VSD and exome sequencing (ES) on 51 fetuses.Results: In our cohort, 68 (14.5%) VSD fetuses received a genetic diagnosis, including 61 (13.03%, 61/468) cases with chromosomal abnormalities and seven (13.7%, 7/51) cases with gene sequence variants. The detection rate of total pathogenic and likely pathogenic gene variations in the non-isolated VSD group (61/335, 18.2%, 55 by QF-PCR/karyotype/CMA + 6 by ES) was significantly higher than that in the isolated VSD group (7/133, 5.3%, 6 by QF-PCR/karyotype/CMA + 1 by ES, p = 0.000). The most common copy number variation (CNV) was 22q11.2 microdeletion syndrome. Additionally, we found six previously unreported variants, which expanded the variation spectrum of VSD-related genes.Conclusion: In this study, CNVs and sequence variants were found in 13.03% and 13.7% of cases, respectively. ES can be recommended for fetuses with VSD without chromosome abnormalities and pathogenic CNVs, especially those that are combined with other ultrasound abnormalities