Synchronous Occurrence of Primary Neoplasms in the Uterus with Squamous Cell Carcinoma of the Cervix and Adenocarcinoma of the Endometrium

SummaryObjectiveSynchronous primary malignant neoplasms of the uterus are uncommon. Patients with synchronous cervical and endometrial cancers are even rarer. We describe a case of cervical squamous cell carcinoma and endometrial endometrioid adenocarcinoma occurring simultaneously in a 47-year-old woman presenting with massive menstrual bleeding. The concept of synchronous primary malignancies of the genital tract is also reviewed in this report.Case ReportA 47-year-old overtly obese female presented with menometrorrhagia of over 6 months' duration. Pelvic examination detected a large cervix but apparently normal externals. Magnetic resonance imaging revealed a mass over the cervical region and endometrial lesions in the uterine cavity. Surgical exploration disclosed a cervical tumor and erosion of the endometrium. The pathologic findings were compatible with synchronous occurrence of primary neoplasms in the uterus with squamous cell carcinoma of the cervix and adenocarcinoma of the endometrium.ConclusionSynchronous genital tract neoplasms are rare but cause more clinical problems than a single neoplasm. It is practical to pay more attention to the differential diagnosis of primary and metastatic tumors. The second primary cancer that occurs in an individual with endometrial cancer may offer an opportunity for early detection. The prognosis for a patient with synchronous gynecologic malignancies does not seem to be worse

Vid2Curve: Simultaneous Camera Motion Estimation and Thin Structure Reconstruction from an RGB Video

Thin structures, such as wire-frame sculptures, fences, cables, power lines, and tree branches, are common in the real world. It is extremely challenging to acquire their 3D digital models using traditional image-based or depth-based reconstruction methods because thin structures often lack distinct point features and have severe self-occlusion. We propose the first approach that simultaneously estimates camera motion and reconstructs the geometry of complex 3D thin structures in high quality from a color video captured by a handheld camera. Specifically, we present a new curve-based approach to estimate accurate camera poses by establishing correspondences between featureless thin objects in the foreground in consecutive video frames, without requiring visual texture in the background scene to lock on. Enabled by this effective curve-based camera pose estimation strategy, we develop an iterative optimization method with tailored measures on geometry, topology as well as self-occlusion handling for reconstructing 3D thin structures. Extensive validations on a variety of thin structures show that our method achieves accurate camera pose estimation and faithful reconstruction of 3D thin structures with complex shape and topology at a level that has not been attained by other existing reconstruction methods.Comment: Accepted by SIGGRAPH 202

Scale-aware Black-and-White Abstraction of 3D Shapes

Flat design is a modern style of graphics design that minimizes the number of design attributes required to convey 3D shapes. This approach suits design contexts requiring simplicity and efficiency, such as mobile computing devices. This 'less-is-more' design inspiration has posed significant challenges in practice since it selects from a restricted range of design elements (e.g., color and resolution) to represent complex shapes. In this work, we investigate a means of computationally generating a specialized 2D flat representation - image formed by black-and-white patches - from 3D shapes.We present a novel framework that automatically abstracts 3D man-made shapes into 2D binary images at multiple scales. Based on a set of identified design principles related to the inference of geometry and structure, our framework jointly analyzes the input 3D shape and its counterpart 2D representation, followed by executing a carefully devised layout optimization algorithm. The robustness and effectiveness of our method are demonstrated by testing it on a wide variety of man-made shapes and comparing the results with baseline methods via a pilot user study. We further present two practical applications that are likely to benefit from our work.</p

Sampling Neural Radiance Fields for Refractive Objects

Recently, differentiable volume rendering in neural radiance fields (NeRF) has gained a lot of popularity, and its variants have attained many impressive results. However, existing methods usually assume the scene is a homogeneous volume so that a ray is cast along the straight path. In this work, the scene is instead a heterogeneous volume with a piecewise-constant refractive index, where the path will be curved if it intersects the different refractive indices. For novel view synthesis of refractive objects, our NeRF-based framework aims to optimize the radiance fields of bounded volume and boundary from multi-view posed images with refractive object silhouettes. To tackle this challenging problem, the refractive index of a scene is reconstructed from silhouettes. Given the refractive index, we extend the stratified and hierarchical sampling techniques in NeRF to allow drawing samples along a curved path tracked by the Eikonal equation. The results indicate that our framework outperforms the state-of-the-art method both quantitatively and qualitatively, demonstrating better performance on the perceptual similarity metric and an apparent improvement in the rendering quality on several synthetic and real scenes.Comment: SIGGRAPH Asia 2022 Technical Communications. 4 pages, 4 figures, 1 table. Project: https://alexkeroro86.github.io/SampleNeRFRO/ Code: https://github.com/alexkeroro86/SampleNeRFR

A Deep Learning Approach to Radar-based QPE

In this study, we propose a volume-to-point framework for quantitative precipitation estimation (QPE) based on the Quantitative Precipitation Estimation and Segregation Using Multiple Sensor (QPESUMS) Mosaic Radar data set. With a data volume consisting of the time series of gridded radar reflectivities over the Taiwan area, we used machine learning algorithms to establish a statistical model for QPE in weather stations. The model extracts spatial and temporal features from the input data volume and then associates these features with the location-specific precipitations. In contrast to QPE methods based on the Z-R relation, we leverage the machine learning algorithms to automatically detect the evolution and movement of weather systems and associate these patterns to a location with specific topographic attributes. Specifically, we evaluated this framework with the hourly precipitation data of 45 weather stations in Taipei during 2013-2016. In comparison to the operational QPE scheme used by the Central Weather Bureau, the volume-to-point framework performed comparably well in general cases and excelled in detecting heavy-rainfall events. By using the current results as the reference benchmark, the proposed method can integrate the heterogeneous data sources and potentially improve the forecast in extreme precipitation scenarios.Comment: 22 pages, 11 figures. Published in Earth and Space Scienc

A 5-Month-Old Infant with Right Scrotum Swelling

Case presentation:A five-month-old male infant (gestational age 28 weeks, birthweight 1020 gm) with posthemorrhagic hydrocephalus subsequent to prematurity had a left sided ventriculoperitoneal shunt 3 months after birth. Frontal radiography of the chest and abdomen check-up after operation are shown in figure 1. He was referred to our emergency department with a history of right scrotal swelling for several days. Physical examination, he appeared malnourished. He was afebrile. The right scrotum was found to be distended. Bilateral testicles were palpable on both sides. There were no features of shunt malfunction. A complete blood cell count showed the following: leukocyte count, 7900/mm3; segmented neutrophils, 65%; hemoglobin level of 9.3 mg/dL; hematocrit, 25.9%; and platelet, 190000/uL. Other laboratory studies included: glucose, 92 mg/dL; serum urea nitrogen, 10 mg/dL; serum creatinine, 0.2 mg/dL; sodium, 140 mEq/L; potassium, 3.9 mEq/L; C-reactive protein, 2.9mg/L; and prothrombin time with an international normalized ratio of 1.2. His abdomen x-ray is shown in figure 2.