Voxel2Hemodynamics: An End-to-end Deep Learning Method for Predicting Coronary Artery Hemodynamics

no code implementations • 30 May 2023 • Ziyu Ni, Linda Wei, Lijian Xu, Simon Yu, Qing Xia, Hongsheng Li, Shaoting Zhang

In this work, we proposed an end-to-end deep learning framework, which could predict the coronary artery hemodynamics from CCTA images.

Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network

no code implementations • 7 May 2023 • Xiaoyu Yang, Lijian Xu, Simon Yu, Qing Xia, Hongsheng Li, Shaoting Zhang

3) A dataset named CCA-200 is collected, consisting of 200 CCTA images with coronary artery disease.

Segmentation

Synergistic Redundancy: Towards Verifiable Safety for Autonomous Vehicles

no code implementations • 4 Sep 2022 • Ayoosh Bansal, Simon Yu, Hunmin Kim, Bo Li, Naira Hovakimyan, Marco Caccamo, Lui Sha

The synergistic safety layer uses only verifiable and logically analyzable software to fulfill its tasks.

Autonomous Driving

Verifiable Obstacle Detection

1 code implementation • 30 Aug 2022 • Ayoosh Bansal, Hunmin Kim, Simon Yu, Bo Li, Naira Hovakimyan, Marco Caccamo, Lui Sha

Perception of obstacles remains a critical safety concern for autonomous vehicles.

Autonomous Driving

LiDAR Cluster First and Camera Inference Later: A New Perspective Towards Autonomous Driving

no code implementations • 18 Nov 2021 • Jiyang Chen, Simon Yu, Rohan Tabish, Ayoosh Bansal, Shengzhong Liu, Tarek Abdelzaher, Lui Sha

Object detection in state-of-the-art Autonomous Vehicles (AV) framework relies heavily on deep neural networks.

Autonomous Driving Novel Object Detection +3