Search

Objective: The study aimed to investigate the clinical outcomes of fetuses diagnosed with isolated mega cisterna magna in utero. Methods: A multicenter retrospective cohort study was conducted across 18 university hospitals from 2010 to 2019. Cases diagnosed with isolated mega cisterna magna, defined as a cisterna magna >10 mm with a normal cerebellar vermis and no cystic dilation of the fourth ventricle, were included. Cases with other central nervous system (CNS) anomalies, extra–central nervous system anomalies, chromosomal abnormalities, or congenital infections were excluded. Maternal demographics, prenatal findings, delivery outcomes, and postnatal outcomes were analyzed. Results: The mean gestational age at initial diagnosis was 28.6 ± 3.9 weeks, and the mean anteroposterior diameter of the cisterna magna was 12.5 ± 3.2 mm. Of the 71 cases initially assessed, 48 (67.6%) showed self-regression in utero. Postnatally, 13 cases (18.3%) had persistent isolated mega cisterna magna, whereas 10 cases (14.1%) were diagnosed with other central nervous system anomalies. Among the persistent isolated mega cisterna magna cases, one child exhibited delayed neurodevelopment. There was a higher incidence of isolated mega cisterna magna in male fetuses, which exhibited a significantly larger mean cisterna magna diameter compared with female fetuses (P =.045). Conclusion: Male fetuses exhibited a higher incidence of isolated mega cisterna magna compared with female fetuses and had larger anteroposterior diameters of the cisterna magna. The study demonstrated favorable neurodevelopmental outcomes associated with isolated mega cisterna magna, with self-regression observed in two-thirds of the cases. However, consecutive prenatal and postnatal evaluations for additional central nervous system or extra–central nervous system malformations need to be performed, considering the differences between prenatal and postnatal diagnoses. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel computational integral-imaging reconstruction (CIIR)-based three-dimensional (3-D) image correlator system for the recognition of 3-D volumetric objects by employing a 3-D reference object. That is, a number of plane object images (POIs) computationally reconstructed from the 3-D reference object are used for the 3-D volumetric target recognition. In other words, simultaneous 3-D image correlations between two sets of target and reference POIs, which are depth-dependently reconstructed by using the CIIR method, are performed for effective recognition of 3-D volumetric objects in the proposed system. Successful experiments with this CIIR-based 3-D image correlator confirmed the feasibility of the proposed method. [c] 2009 Optical Society of America OCIS codes: 100.3008, 110.6880, 100.6890.

In this paper we propose a new approach for fast generation of computer-generated holograms (CGHs) of a 3D object by using the run-length encoding (RLE) and the novel look-up table (N-LUT) methods. With the RLE method, spatially redundant data of a 3D object are extracted and regrouped into the N-point redundancy map according to the number of the adjacent object points having the same 3D value. Based on this redundancy map, N-point principle fringe patterns (PFPs) are newly calculated by using the 1-point PFP of the N-LUT, and the CGH pattern for the 3D object is generated with these N-point PFPs. In this approach, object points to be involved in calculation of the CGH pattern can be dramatically reduced and, as a result, an increase of computational speed can be obtained. Some experiments with a test 3D object are carried out and the results are compared to those of the conventional methods. OCIS codes: 090.1760, 090.5694, 050.1940, 100.6890.

Even though there are many types of methods to generate CGH (computer-generated hologram) patterns of three-dimensional (3D) objects, most of them have been applied to still images but not to video images due to their computational complexity in applications of 3D video holograms. A new method for fast computation of CGH patterns for 3D video images is proposed by combined use of data compression and lookup table techniques. Temporally redundant data of the 3D video images are removed with the differential pulse code modulation (DPCM) algorithm, and then the CGH patterns for these compressed videos are generated with the novel lookup table (N-LUT) technique. To confirm the feasibility of the proposed method, some experiments with test 3D videos are carried out, and the results are comparatively discussed with the conventional methods in terms of the number of object points and computation time. OCIS codes: 090.1760, 090.5694, 050.1940, 100.6890.

We have implemented experimental code to compute a compensated phase-added stereogram (CPAS), which was proposed in a previous paper, on a graphic processing unit (GPU). In this paper, we show an acceleration method for CPAS computation by means of the GPU and compare the computation time between CPU-based and GPU-based calculations, which are programmed in our laboratories. In addition, we demonstrate their reconstructed images. As a result, we could achieve a performance gain of a factor of over 33 compared with a CPU-based computing environment and digital holograms can be displayed at 30 frames per second with 15,000 points. OCIS codes: 090.1760, 090.5694.

We present a novel approach for generating three-dimensional (3-D) integral images from a fringe pattern of 3-D objects. A recorded hologram of 3-D objects is segmented into a number of subholograms. Then, different views of 3-D objects are reconstructed from them because each subhologram has its own perspective of 3-D objects in the recording process. These locally reconstructed images can be rearranged as the same subimage array of the conventional integral-imaging system and transformed into virtually picked-up elemental images of 3-D objects. From this newly generated elemental image array, 3D images could easily be reconstructed by using a white light. Experiments with a 3-D test object have been performed and the results have been presented. OCIS codes: 090.1760, 090.2870, 100.6890.

A novel approach to extract the depth data of 3D objects in space by using the computational integral imaging reconstruction (CIIR) technique is proposed. With elemental images of 3D objects captured by the CCD camera through a pinhole array, depth-dependent object images can be reconstructed on the output plane by the CIIR technique. Only the images reconstructed on the output planes where 3D objects were located are clearly focused; so the depth data of 3D objects in space can be extracted by discriminating these focused output images from the others by using an image separation technique. A feasibility test of the proposed CIIR-based depth extraction method is carried out, and its results are discussed as well. OCIS codes: 110.0110, 110.6880, 100.6890.

Several approaches for increasing the speed in computation of the digital holograms of three-dimensional objects have been presented with applications to real-time display of holographic images. Among them, a look-up table (LUT) approach, in which the precalculated principal fringe patterns for all possible image points of the object are provided, has gained a large speed increase in generation of computer-generated holograms. But the greatest drawback of this method is the enormous memory size of the LUT. A novel approach to dramatically reduce the size of the conventional LUT, still keeping its advantage of fast computational speed, is proposed, which is called here a novel LUT (N-LUT) method. A three-dimensional object can be treated as a set of image planes discretely sliced in the z direction, in which each image plane having a fixed depth is approximated as some collection of self-luminous object points of light. In the proposed method, only the fringe patterns of the center points on each image plane are precalculated, called principal fringe patterns (PFPs) and stored in the LUT. Then, the fringe patterns for other object points on each image plane can be obtained by simply shifting this precalculated PFP according to the displaced values from the center to those points and adding them together. Some experimental results reveal that the computational speed and the required memory size of the proposed approach are found to be 69.5 times faster than that of the ray-tracing method and 744 times smaller than that of the conventional LUT method, respectively. OCIS codes: 090.1760, 090.5694, 050.1940, 100.6890.

A computational integral imaging reconstruction technique can reconstruct a set of plane images of three-dimensional (3-D) objects along the output plane, in which only the plane object image (POD reconstructed on the right planes where the objects were positioned is highly focused, whereas the other POIs reconstructed away from these planes are unfocused and blurred. In fact, these blurred POIs act as additional noises to other object images reconstructed on different output planes, so that the resolution of reconstructed object images should be considerably deteriorated. In this paper, a novel approach is proposed to effectively reduce the blurred images occurring in the focused POIs by employing a blur metric. From the estimated blur metric of each reconstructed POI, the right output planes where the objects were located can be detected. In addition, with an estimated blur metric, focused POIs can be adaptively eroded by a simple gray level erosion operation because it reduces regional expansion caused by the blur effect. The gray values of the eroded POIs are then finally remapped by referencing the original POIs. Some experiments revealed an average increase of 1.95 dB in the peak signal-to-noise ratio in the remapped POIs compared with that of the originally reconstructed POIs, and that the original forms of the object images in the remapped POIs could be preserved even after they had gone through an erosion operation. This feasibility test of the proposed scheme finally suggests a possibility of its application to robust detection and recognition of 3-D objects in a scene. OCIS codes: 110.0110, 110.6880, 100.6890.

A novel method of using stereoscopic video images to synthesize the computer-generated hologram (CGH) patterns of a real 3D object is proposed. Stereoscopic video images of a real 3D object are captured by a 3D camera system. Disparity maps between the captured stereo image pairs are estimated and from these estimated maps the depth data for each pixel of the object can be extracted on a frame basis. By using these depth data and original color images, hologram patterns of a real object can be computationally generated. In experiments, stereoscopic video images of a real 3D object, a wooden rhinoceros doll, are captured by using the Wasol 3D adapter system and its depth data are extracted from them. Then, CGH patterns of 1280 pixels x 1024 pixels are generated with these depth-annotated images of the wooden rhinoceros doll, and the CGH patterns are experimentally displayed via a holographic display system. OCIS codes: 090.1760, 090.2870, 100.6890.

A new integral imaging (II) system that can magnify 3D reconstructed images by employing an intermediate-view reconstruction technique (IVRT) is proposed in which the number of the elemental images obtained from a one-step pickup process can be computationally increased by use of an IVRT without mechanical movement and a long multistep pickup process. To show the feasibility of the proposed II system, some optical experiments on the magnification of 3D reconstructed images with a real 3D object have been carried out and results are presented. OCIS codes: 110.6880, 110.4190.