Bigradient Phase Referencing

We propose bigradient phase referencing (BPR), a new radio-observation technique, and report its performance using the Japanese very-long-baseline-interferometry network (JVN). In this method, a weak source is detected by phase-referencing using a primary calibrator, in order to play a role as a secondary calibrator for phase-referencing to a weak target. We will be given the opportunity to select a calibrator from lots of milli-Jansky sources, one of which may be located at the position closer to the target. With such a smaller separation, high-quality phase-referencing can be achieved. Furthermore, a subsequent more-sophisticated calibration can relocate array's focus to a hypothetical point much closer to the target; a higher quality of phase referencing is available. Our demonstrative observations with strong radio sources have proved the capabilities of BPR in terms of image dynamic ranges and astrometric reproducibility. The image dynamic range on a target has been improved with a factor of about six compared to that of normal phase-referencing; the resultant position difference of target's emission between two epochs was only 62+-50 micro-arcsecond, even with less than 2300-km baselines at 8.4 GHz and fast-switching of a target-calibrator pair of a 2.1-degree separation.Comment: 10 pages, 4 figures, accepted for publication in PAS

Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets

In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to multispectral images. Satellite images have been widely utilized for various purposes, such as natural environment monitoring (pollution, forest or rivers), transportation improvement and prompt emergency response to disasters. However, the obscurity caused by clouds makes it unstable to monitor the situation on the ground with the visible light camera. Images captured by a longer wavelength are introduced to reduce the effects of clouds. Synthetic Aperture Radar (SAR) is such an example that improves visibility even the clouds exist. On the other hand, the spatial resolution decreases as the wavelength increases. Furthermore, the images captured by long wavelengths differs considerably from those captured by visible light in terms of their appearance. Therefore, we propose a network that can remove clouds and generate visible light images from the multispectral images taken as inputs. This is achieved by extending the input channels of cGANs to be compatible with multispectral images. The networks are trained to output images that are close to the ground truth using the images synthesized with clouds over the ground truth as inputs. In the available dataset, the proportion of images of the forest or the sea is very high, which will introduce bias in the training dataset if uniformly sampled from the original dataset. Thus, we utilize the t-Distributed Stochastic Neighbor Embedding (t-SNE) to improve the problem of bias in the training dataset. Finally, we confirm the feasibility of the proposed network on the dataset of four bands images, which include three visible light bands and one near-infrared (NIR) band

Astrometry of H2_{2}O Masers in Nearby Star-Forming Regions with VERA --- IV. L1448C

We have carried out multi-epoch VLBI observations with VERA (VLBI Exploration of Radio Astrometry) of the 22~GHz H$_{2}$O masers associated with a Class 0 protostar L1448C in the Perseus molecular cloud. The maser features trace the base of collimated bipolar jet driven by one of the infrared counter parts of L1448C named as L1448C(N) or L1448-mm A. We detected possible evidences for apparent acceleration and precession of the jet according to the three-dimensional velocity structure. Based on the phase-referencing VLBI astrometry, we have successfully detected an annual parallax of the H$_{2}$O maser in L1448C to be 4.31$\pm$0.33~milliarcseconds (mas) which corresponds to a distance of 232$\pm$18~pc from the Sun. The present result is in good agreement with that of another H$_{2}$O maser source NGC~1333 SVS13A in the Perseus molecular cloud, 235~pc. It is also consistent with the photometric distance, 220~pc. Thus, the distance to the western part of the Perseus molecular cloud complex would be constrained to be about 235~pc rather than the larger value, 300~pc, previously reported.Comment: 15 pages, 5 figures, accepted for publication in PAS

子宮内膜症関連卵巣癌と隆起性病変を有する良性卵巣内膜症を鑑別する因子の検討

PURPOSE: Mural nodules and papillary projections can be seen in benign ovarian endometriosis (OE) and malignant transformation of OE (endometriosis-associated ovarian cancer [EAOC]), which can pose a challenging diagnostic dilemma to clinicians. We identify the preoperative imaging characteristics helpful to the differential diagnosis between benign OE with mural nodules and EAOC. MATERIALS AND METHODS: This was a retrospective study of 82 patients who were diagnosed pathologically to have OE with mural nodules (n = 42) and malignant transformations of these tumors (n = 40) at the Nara Medical University Hospital from January 2008 to January 2015. All patients were assessed with contrast-enhanced magnetic resonance imaging (MRI) before surgery. Patient demographics, and clinical and pathologic features were analyzed to detect the significant differences between the two groups. RESULTS: Histological examinations of resected OE tissue specimens revealed that a majority (78.6%) of the mural nodular lesions were retracted blood clots. We found that the patients with malignant mural nodules, when compared to those with benign nodules, were older, had larger cyst diameters and larger mural nodule sizes, and were more likely to exhibit a taller than wider lesion. They were also more likely to present with various signal intensities on T1-weighted images (T1WI), high-signal intensity on T2-weighted images (T2WI), a lower proportion of shading on T2WI, and were more likely to show an anterior location of the cyst. In the multivariate logistic regression analysis, "Height" (>1.5 cm) and "Height-Width ratio (HWR)" (>0.9) of mural nodules, maximum diameter of the cyst (>7.9 cm), and age at diagnosis (>43 years) were independent predictors to distinguish EAOC from OE with mural nodules. CONCLUSION: The "Height" and "HWR" of the mural nodules in the cyst may yield a novel potential diagnostic factor for differentiating EAOC from benign OE with mural nodules.博士（医学）・乙第1415号・平成30年3月15日©2017 Japanese Society for Magnetic Resonance in Medicine This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives International License. https://creativecommons.org/licenses/by-nc-nd/4.0/