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BackgroundApparent diffusion coefficients (ADCs) obtained with diffusion-weighted imaging (DWI) are highly valuable for the detection and staging of prostate cancer and for assessing the response to treatment. However, DWI suffers from significant anatomic distortions and susceptibility artifacts, resulting in reduced accuracy and reproducibility of the ADC calculations. The current methods for improving the DWI quality are heavily dependent on software, hardware, and additional scan time. Therefore, their clinical application is limited. An accelerated ADC generation method that maintains calculation accuracy and repeatability without heavy dependence on magnetic resonance imaging scanners is of great clinical value.ObjectivesWe aimed to establish and evaluate a supervised learning framework for synthesizing ADC images using generative adversarial networks.MethodsThis prospective study included 200 patients with suspected prostate cancer (training set: 150 patients; test set #1: 50 patients) and 10 healthy volunteers (test set #2) who underwent both full field-of-view (FOV) diffusion-weighted imaging (f-DWI) and zoomed-FOV DWI (z-DWI) with b-values of 50, 1,000, and 1,500 s/mm2. ADC values based on f-DWI and z-DWI (f-ADC and z-ADC) were calculated. Herein we propose an ADC synthesis method based on generative adversarial networks that uses f-DWI with a single b-value to generate synthesized ADC (s-ADC) values using z-ADC as a reference. The image quality of the s-ADC sets was evaluated using the peak signal-to-noise ratio (PSNR), root mean squared error (RMSE), structural similarity (SSIM), and feature similarity (FSIM). The distortions of each ADC set were evaluated using the T2-weighted image reference. The calculation reproducibility of the different ADC sets was compared using the intraclass correlation coefficient. The tumor detection and classification abilities of each ADC set were evaluated using a receiver operating characteristic curve analysis and a Spearman correlation coefficient.ResultsThe s-ADCb1000 had a significantly lower RMSE score and higher PSNR, SSIM, and FSIM scores than the s-ADCb50 and s-ADCb1500 (all P < 0.001). Both z-ADC and s-ADCb1000 had less distortion and better quantitative ADC value reproducibility for all the evaluated tissues, and they demonstrated better tumor detection and classification performance than f-ADC.ConclusionThe deep learning algorithm might be a feasible method for generating ADC maps, as an alternative to z-ADC maps, without depending on hardware systems and additional scan time requirements.

iffusion-weighted imaging (DWI) is a key component of multiparametric MRI in the detection and characterization of prostate cancer (1). Compared with standardb-value (800-1000 sec/mm 2 ) DWI, high-b-value (.1000 sec/mm 2 ) DWI enables detection of small changes in diffusion because of better contrast between malignant and background tissue (2). According to the Prostate Imaging Reporting and Data System version 2, higher b values (1400 to 2000 sec/mm 2 ) are considered to result in better image quality for differentiating between these tissue types (3). However, there is currently no widely accepted optimal high b value because such a b value depends on the magnetic field strength, software, and hardware.High-b-value DWI is technically challenging to obtain in clinical practice; acquired DWI frequently suffers from poor in-plane spatial resolution, distortion, and artifacts. Moreover, an increase in the b value is generally accompanied by a significant reduction in the signal-to-noise ratio and requires a prolonged acquisition time (4-6). To overcome these shortcomings, calculated DWI and zoomed field of view (FOV) DWI technology have been introduced. In calculated DWI, high-b-value images are calculated based on acquired DWI sets with lower b values through voxel-byvoxel extrapolation of the fitted signal decay curves (7). Calculated DWI is potentially less prone to producing artifacts because the longer echo times required to accommodate the strong gradient pulses needed for highb-value acquisitions are avoided, but the image quality of calculated DWI with high b values still relies on the image quality of the DWI with lower b values. Zoomed FOV DWI excites a small FOV that covers only the region of interest and consequently increases the in-plane resolution and reduces the geometric distortion artifacts (8,9). However, zoomed FOV DWI techniques depend on the gradient performance, radiofrequency design, and software platform (5,10-14), and their clinical application remains limited.

We investigate the phase coherence between a seed laser and a laser amplified by a tapered semiconductor amplifier (TSA) when the seed laser is either continuous wave (CW) or pulsed. The phase fluctuations in the time domain are employed to describe the degradation of phase coherence induced by a TSA. The amplified laser is measured to be approximately 99.98% coherent with the seed, when the CW or pulsed laser is seeded, at different supplying currents of the TSA. Furthermore, the phase coherence is measured when the seed laser is modulated. The results reveal that the phase coherence degradations induced by the TSA remain the same for a seed laser with and without modulation, when different supplying currents of the TSA are applied.

Microstructure optical fiber materials has many virtues: small momofilament diameter, soft and flexible, high resolution, which make it have many broad application prospects in different fields, such as: high definition imaging equipment, industrial automation dectection, military and aerospace, etc. The materials of core, cladding and acid-soluble glasses were prepared, which had good physical and chemical matching on the base of three layers coaxial micro-structure. The double clad flexible fiber micostructure and spectral performances were tested. The experiments obtained high quality image transfer fiber, of which monofilament diametre is 10μm ± 0.1μm, resolution is 52.5LP/mm, transmittance is 42.6%/m. Experimental results showed that the preparation process broke through the traditional techniques and achieved the structure innovation, which had some reference value to improve the optical properties of image instruments.