![]() Robovan’s design is based on Jiangling’s battery electric vehicle model, equipped with WeRide’s full-stack software and hardware solutions. Presented October 12, 2019.WeRide launches first L4 self-driving cargo vanĬhinese autonomous driving technology developer WeRide launched its first L4-level self-driving cargo van yesterday and announced that it will work with Jiangling Motors, a major Chinese automobile manufacturer, and ZTO Express, a leading express delivery company in China, to drive mass production and the commercialization of the newly unveiled WeRide Robovan. Liu X: Deep learning analysis for automatic lung nodule detection. Liu is employed in a leadership position by LinkDoc Technology, where he holds stock and ownership interests, and has received research funding and travel and accommodation expenses.ġ. ■ĭISCLOSURE: Funding for this study was provided by LinkDoc Technology. ![]() “The proposed computer-aided diagnosis system offers a fast and convenient approach for assisting the diagnosis of lung nodule pathologies, and it is beneficial to relate our research to the current framework of lung cancer diagnosis,” Dr. Each detected lesion was labeled by its bounding box and then analyzed through an image-processing algorithm to generate diagnostic assisting features, including longest and shortest diameter, volume, and largest cross-section area, as well as its density type (calcified, solid, partial solid, and ground-glass opacity). ![]() The researchers found that the resulting detection system yielded a free-response receiver operating characteristic of 0.4663, recall of 82.46%, and precision of 36.06% for 5-mm to 30-mm nodules. ![]() After preprocessing, a pretrained residual neural network framework was transferred to develop a robust detection system that could detect the possible lung lesion locations with corresponding probabilities. The obtained CT images were randomly selected and split to construct training, validation, and test data sets. Lung nodule annotation was then performed by two experienced radiologists and further assessed by four senior associate chief physicians. The data collected included 3,956 lung CT series with multiple lung nodules from 15 class A hospitals in China, 1,155 lung CT scans from the publicly available Lung Nodule Analysis 2016 data sets, and CT scans from the data sets of the Kaggle Data Science Bowl 2017. ![]() Liu and investigators employed deep-learning analysis for lesion detection in patients and performed image-processing techniques to generate quantitative morphology features for assisting lesion diagnosis. Although the early detection and treatment of lung cancer improve survival outcome, the accurate identification and characterization of small lung nodules are challenging. Worldwide, among men and women combined, lung cancer is the most commonly diagnosed and deadliest cancer, with approximately 2,093,876 new cases diagnosed in 2018 and 1,761,007 deaths reported. ![]()
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