InstaGraM: Instance-level Graph Modeling for Vectorized HD Map Learning

Inferring traffic object such as lane information is of foremost importance for deployment of autonomous driving. Previous approaches focus on offline construction of HD map inferred with GPS localization, which is insufficient for globally scalable autonomous driving. To alleviate these issues, we propose online HD map learning framework that detects HD map elements from onboard sensor observations. We represent the map elements as a graph; we propose InstaGraM, instance-level graph modeling of HD map that brings accurate and fast end-to-end vectorized HD map learning. Along with the graph modeling strategy, we propose end-to-end neural network composed of three stages: a unified BEV feature extraction, map graph component detection, and association via graph neural networks. Comprehensive experiments on public open dataset show that our proposed network outperforms previous models by up to 13.7 mAP with up to 33.8X faster computation time.Comment: Workshop on Vision-Centric Autonomous Driving (VCAD) at Conference on Computer Vision and Pattern Recognition (CVPR) 202

CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception

Autonomous driving requires an accurate and fast 3D perception system that includes 3D object detection, tracking, and segmentation. Although recent low-cost camera-based approaches have shown promising results, they are susceptible to poor illumination or bad weather conditions and have a large localization error. Hence, fusing camera with low-cost radar, which provides precise long-range measurement and operates reliably in all environments, is promising but has not yet been thoroughly investigated. In this paper, we propose Camera Radar Net (CRN), a novel camera-radar fusion framework that generates a semantically rich and spatially accurate bird's-eye-view (BEV) feature map for various tasks. To overcome the lack of spatial information in an image, we transform perspective view image features to BEV with the help of sparse but accurate radar points. We further aggregate image and radar feature maps in BEV using multi-modal deformable attention designed to tackle the spatial misalignment between inputs. CRN with real-time setting operates at 20 FPS while achieving comparable performance to LiDAR detectors on nuScenes, and even outperforms at a far distance on 100m setting. Moreover, CRN with offline setting yields 62.4% NDS, 57.5% mAP on nuScenes test set and ranks first among all camera and camera-radar 3D object detectors.Comment: IEEE/CVF International Conference on Computer Vision (ICCV'23

NEGATIVE STRAIN IN THE SOLEUS POSTERIOR APONEUROSIS DURING HUMAN VOLUNTARY ISOMETRIC CONTRACTION

Aponeurosis in a pennate muscle has been modelled as an in-series structure (3) with homogeneous elasticity along the length of the muscle. Therefore, one can readily assume that muscle and aponeurosis sustain forces in the same proportion and thus, aponeurosis strain (L/L0) is homogeneous. This study aimed to investigate force-elongation (strain) characteristics of aponeurosis in in-vivo human soleus during voluntary contraction

Quantitative analysis of high-resolution microendoscopic images for diagnosis of neoplasia in patients with Barrett’s esophagus

Background and Aims: Previous studies show that microendoscopic images can be interpreted visually to identify the presence of neoplasia in patients with Barrett’s esophagus (BE), but this approach is subjective and requires clinical expertise. This study describes an approach for quantitative image analysis of microendoscopic images to identify neoplastic lesions in patients with BE. Methods: Images were acquired from 230 sites from 58 patients by using a fiberoptic high-resolution microendoscope during standard endoscopic procedures. Images were analyzed by a fully automated image processing algorithm, which automatically selected a region of interest and calculated quantitative image features. Image features were used to develop an algorithm to identify the presence of neoplasia; results were compared with a histopathology diagnosis. Results: A sequential classification algorithm that used image features related to glandular and cellular morphology resulted in a sensitivity of 84% and a specificity of 85%. Applying the algorithm to an independent validation set resulted in a sensitivity of 88% and a specificity of 85%. Conclusions: This pilot study demonstrates that automated analysis of microendoscopic images can provide an objective, quantitative framework to assist clinicians in evaluating esophageal lesions from patients with BE. (Clinical trial registration number: NCT01384227 and NCT02018367.

On the effect of linear feedback and parametric pumping on a resonators frequency stability

Resonant sensors based on Micro- and Nano-Electro Mechanical Systems (M/NEMS) are ubiquitous in many sensing applications due to their outstanding performance capabilities, which are directly proportional to the quality factor (Q) of the devices. We address here a recurrent question in the field: do dynamical techniques that modify the effective Q (namely parametric pumping and direct drive velocity feedback) affect the performance of said sensors? We develop analytical models of both cases, while remaining in the linear regime, and introduce noise in the system from two separate sources: thermomechanical and amplifier (read-out) noise. We observe that parametric pumping enhances the quality factor in the amplitude response, but worsens it in the phase response on the resonator. In the case of feedback, we find that Q is enhanced in both cases. Then, we establish a solution for the noisy problem with direct drive and parametric pumping simultaneously. We also find that, in the case when thermomechanical noise dominates, no benefit can be obtained from neither artificial Q-enhancement technique. However, in the case when amplifier noise dominates, we surprisingly observe that a significant advantage can only be achieved using parametric pumping in the squeezing region

Quantitative Analysis of High-Resolution Microendoscopic Images for Diagnosis of Esophageal Squamous Cell Carcinomaﾠ

Background & Aims: High-resolution microendoscopy is an optical imaging technique with the potential to improve the accuracy of endoscopic screening for esophageal squamous neoplasia. Although these microscopic images can be interpreted readily by trained personnel, quantitative image analysis software could facilitate the use of this technology in low-resource settings. In this study, we developed and evaluated quantitative image analysis criteria for the evaluation of neoplastic and non-neoplastic squamous esophageal mucosa. Methods: We performed an image analysis of 177 patients undergoing standard upper endoscopy for screening or surveillance of esophageal squamous neoplasia, using high-resolution microendoscopy, at 2 hospitals in China and at 1 hospital in the United States from May 2010 to October 2012. Biopsy specimens were collected from imaged sites (n = 375), and a consensus diagnosis was provided by 2 expert gastrointestinal pathologists and used as the standard. Results: Quantitative information from the high-resolution images was used to develop an algorithm to identify high-grade squamous dysplasia or invasive squamous cell cancer, based on histopathology findings. Optimal performance was obtained using the mean nuclear area as the basis for classification, resulting in sensitivities and specificities of 93% and 92% in the training set, 87% and 97% in the test set, and 84% and 95% in an independent validation set, respectively. Conclusions: High-resolution microendoscopy with quantitative image analysis can aid in the identification of esophageal squamous neoplasia. Use of software-based image guides may overcome issues of training and expertise in low-resource settings, allowing for widespread use of these optical biopsy technologies

Low-Cost High-Resolution Microendoscopy for the Detection of Esophageal Squamous Cell Neoplasia: An International Trial

Background & Aims: Esophageal squamous cell neoplasia has a high mortality rate as a result of late detection. In high-risk regions such as China, screening is performed by Lugol’s chromoendoscopy (LCE). LCE has low specificity, resulting in unnecessary tissue biopsy with a subsequent increase in procedure cost and risk. The purpose of this study was to evaluate the accuracy of a novel, low-cost, high-resolution microendoscope (HRME) as an adjunct to LCE. Methods: In this prospective trial, 147 consecutive high-risk patients were enrolled from 2 US and 2 Chinese tertiary centers. Three expert and 4 novice endoscopists performed white-light endoscopy followed by LCE and HRME. All optical images were compared with the gold standard of histopathology. Results: By using a per-biopsy analysis, the sensitivity of LCE vs LCE + HRME was 96% vs 91% (P = .0832), specificity was 48% vs 88% (P < .001), positive predictive value was 22% vs 45% (P < .0001), negative predictive value was 98% vs 98% (P = .3551), and overall accuracy was 57% vs 90% (P < .001), respectively. By using a per-patient analysis, the sensitivity of LCE vs LCE + HRME was 100% vs 95% (P = .16), specificity was 29% vs 79% (P < .001), positive predictive value was 32% vs 60%, 100% vs 98%, and accuracy was 47% vs 83% (P < .001). With the use of HRME, 136 biopsies (60%; 95% confidence interval, 53%–66%) could have been spared, and 55 patients (48%; 95% confidence interval, 38%–57%) could have been spared any biopsy. Conclusions: In this trial, HRME improved the accuracy of LCE for esophageal squamous cell neoplasia screening and surveillance. HRME may be a cost-effective optical biopsy adjunct to LCE, potentially reducing unnecessary biopsies and facilitating real-time decision making in globally underserved regions. ClinicalTrials.gov, NCT 01384708

A Fiber-Optic Fluorescence Microscope Using a Consumer-Grade Digital Camera for In Vivo Cellular Imaging

BACKGROUND: Early detection is an essential component of cancer management. Unfortunately, visual examination can often be unreliable, and many settings lack the financial capital and infrastructure to operate PET, CT, and MRI systems. Moreover, the infrastructure and expense associated with surgical biopsy and microscopy are a challenge to establishing cancer screening/early detection programs in low-resource settings. Improvements in performance and declining costs have led to the availability of optoelectronic components, which can be used to develop low-cost diagnostic imaging devices for use at the point-of-care. Here, we demonstrate a fiber-optic fluorescence microscope using a consumer-grade camera for in vivo cellular imaging. METHODS: The fiber-optic fluorescence microscope includes an LED light, an objective lens, a fiber-optic bundle, and a consumer-grade digital camera. The system was used to image an oral cancer cell line labeled with 0.01% proflavine. A human tissue specimen was imaged following surgical resection, enabling dysplastic and cancerous regions to be evaluated. The oral mucosa of a healthy human subject was imaged in vivo, following topical application of 0.01% proflavine. FINDINGS: The fiber-optic microscope resolved individual nuclei in all specimens and tissues imaged. This capability allowed qualitative and quantitative differences between normal and precancerous or cancerous tissues to be identified. The optical efficiency of the system permitted imaging of the human oral mucosa in real time. CONCLUSION: Our results indicate this device as a useful tool to assist in the identification of early neoplastic changes in epithelial tissues. This portable, inexpensive unit may be particularly appropriate for use at the point-of-care in low-resource settings

A comparison study of ionic polymer-metal composites (IPMCs) fabricated with Nafion and other ion exchange membranes

Ionic polymer-metal composites (IPMCs) have been and still are one of the best candidates with great potential to be used as actuators and sensors particularly in bioengineering where the environmental conditions are in an aqueous medium. Each component of an IPMC is important. However, the ion exchange membrane should be more emphasized because it is where ions migrate when electrical stimulation is applied and eventually it produces deformation of the IPMC. So far, the most commonly used ion exchange membrane is Nafion and many studies have been conducted with it for IPMC applications. There are a number of other commercially available ion exchange membranes now, but only a few studies have been done on those membranes to be used in IPMC applications. In this study, four commercially available membranes, (1) Nafion N115 (DuPont), (2) CMI7000S (Membranes International Inc.), (3) F-14100 (fumatech), (4) GEFC-700 (Golden Energy Fuel Cell) were selected and fabricated in IPMCs and their potentials as actuators were examined by conducting various characterizations such as water uptake, ion exchange capacity, SEM, DSC, blocking force and bending displacement. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use onl