Broadband and large-aperture metasurface edge encoders for incoherent infrared radiation.

The prevalence of computer vision systems necessitates hardware-based approaches to relieve the high computational demand of deep neural networks in resource-limited applications. One solution would be to off-load low-level image feature extraction, such as edge detection, from the digital network to the analog imaging system. To that end, this work demonstrates incoherent, broadband, low-noise optical edge detection of real-world scenes by combining the wavefront shaping of a 24-mm aperture metasurface with a refractive lens. An inverse design approach is used to optimize the metasurface for Laplacian-based edge detection across the 7.5- to 13.5-µm LWIR imaging band, allowing for facile integration with uncooled microbolometer-based LWIR imagers to encode edge information. A polarization multiplexed approach leveraging a birefringent metasurface is also demonstrated as a single-aperture implementation. This work could be applied to improve computer vision capabilities of resource-constrained systems by leveraging optical preprocessing to alleviate the computational requirements for high-accuracy image segmentation and classification.

Digital Modeling on Large Kernel Metamaterial Neural Network.

Deep neural networks (DNNs) utilized recently are physically deployed with computational units (e.g., CPUs and GPUs). Such a design might lead to a heavy computational burden, significant latency, and intensive power consumption, which are critical limitations in applications such as the Internet of Things (IoT), edge computing, and the usage of drones. Recent advances in optical computational units (e.g., metamaterial) have shed light on energy-free and light-speed neural networks. However, the digital design of the metamaterial neural network (MNN) is fundamentally limited by its physical limitations, such as precision, noise, and bandwidth during fabrication. Moreover, the unique advantages of MNN's (e.g., light-speed computation) are not fully explored via standard 3×3 convolution kernels. In this paper, we propose a novel large kernel metamaterial neural network (LMNN) that maximizes the digital capacity of the state-of-the-art (SOTA) MNN with model re-parametrization and network compression, while also considering the optical limitation explicitly. The new digital learning scheme can maximize the learning capacity of MNN while modeling the physical restrictions of meta-optic. With the proposed LMNN, the computation cost of the convolutional front-end can be offloaded into fabricated optical hardware. The experimental results on two publicly available datasets demonstrate that the optimized hybrid design improved classification accuracy while reducing computational latency. The development of the proposed LMNN is a promising step towards the ultimate goal of energy-free and light-speed AI.

Does proximity of positive prostate biopsy core to capsular margin help predict side-specific extracapsular extension at prostatectomy?

INTRODUCTION: To determine whether quantifying the proximity of positive prostate biopsy cores to the capsular edge may aid in identifying patients at risk for extracapsular extension (ECE) at the time of radical prostatectomy (RP). MATERIALS AND METHODS: We reviewed a single-surgeon experience of 429 systematic transrectal prostate biopsies from 2010-2014. Marking ink was applied to the capsular edge ex vivo following specimen acquisition, and the proximity of cancer to the stained capsular edge was measured. Primary outcome was ECE at RP. Demographics, PSA, DRE findings, Gleason score, core location and involvement, and RP pathology were recorded. Predictors of ECE were identified using multivariable logistic regression. Receiver operating characteristic (ROC) analyses were performed to assess the predictive value of variables alone and in combination. RESULTS: One hundred and one patients who underwent staining during biopsy received RP (202 hemiprostates). Thirty-three patients (40 hemiprostates) exhibited ECE. There were 343 positive stained biopsy cores. Mean proximity of carcinoma to capsule was 4.7 mm. On univariable analysis, proximity of positive core ≤ 1 mm to capsule was predictive of side-specific ECE (OR 2.86, p = 0.013), though significance was lost in multivariable models. Area under the curve (AUC) for proximity was 0.571 alone and 0.804 in combination with PSA, cT stage, and total biopsy Gleason score. CONCLUSION: Proximity of positive biopsy core to capsular margin may supply additional information in predicting ECE but requires validation in a larger cohort. Implementation of a staining technique at the time of systematic biopsy may be helpful in counseling patients and determining utility of nerve-sparing approaches.

Fine needle aspiration of parapharyngeal space adult rhabdomyoma: a case report.

BACKGROUND: Rhabdomyomas are rare benign tumors of striated muscle and include cardiac and extracardiac types. Extracardiac rhabdomyomas are divided in three subtypes (adult, fetal, genital). The adult type is usually found in the head and neck regions of elderly persons. Misinterpretations in initial diagnosis of adult rhabdomyomas on fine needle aspiration have been reported. CASE: A 64-year-old man presented with gurgling and difficulty swallowing for approximately 3 months. Computed tomography and magnetic resonance imaging showed a 5.8-cm solid mass located in the right parapharyngeal space. Fine needle aspiration smears were cellular, showing cohesive clusters of cells with scattered individual cells. Cells had abundant eosinophilic glassy cytoplasm, peripherally placed round nuclei, and prominent nucleoli. Many traversing vessels were noted, but cross-striations were not seen. The cell block demonstrated clusters of cells with abundant eosinophilic granular cytoplasm, some with clear and/or vacuolated cytoplasm, and possible cross-striations. Tumor cells were positive for desmin. The lesion closely resembled normal muscle tissue. Electron microscopy showed many cells containing actin and myosin filaments with Z-band material. CONCLUSION: Correct diagnosis can be achieved with a combination of awareness of the lesion, familiarity with the characteristic cytologic features, and application of appropriate immunohistochemistry markers. Classic electron microscopic findings can support the diagnosis.