87 citations · 809 across the 93 of their papers we have counts for
17 papers · 1 filter
Myocardial Segmentation of Cardiac MRI Sequences with Temporal Consistency for Coronary Artery Disease Diagnosis
Yutian Chen, Xiaowei Xu, Dewen Zeng +6
Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis is usually based on manual myocardial segmentation of Magnetic Resonance Imaging (MRI) s…
When Machine Learning Meets Quantum Computers: A Case Study
Weiwen Jiang, Jinjun Xiong, Yiyu Shi
Along with the development of AI democratization, the machine learning approach, in particular neural networks, has been applied to wide-range applications. In different applicatio…
Do Noises Bother Human and Neural Networks In the Same Way? A Medical Image Analysis Perspective
Shao-Cheng Wen, Yu-Jen Chen, Zihao Liu +7
Deep learning had already demonstrated its power in medical images, including denoising, classification, segmentation, etc. All these applications are proposed to automatically ana…
Personalized Deep Learning for Ventricular Arrhythmias Detection on Medical IoT Systems
Zhenge Jia, Zhepeng Wang, Feng Hong +3
Life-threatening ventricular arrhythmias (VA) are the leading cause of sudden cardiac death (SCD), which is the most significant cause of natural death in the US. The implantable c…
Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation
Dewen Zeng, Weiwen Jiang, Tianchen Wang +6
Real-time cardiac magnetic resonance imaging (MRI) plays an increasingly important role in guiding various cardiac interventions. In order to provide better visual assistance, the…
ICA-UNet: ICA Inspired Statistical UNet for Real-time 3D Cardiac Cine MRI Segmentation
Tianchen Wang, Xiaowei Xu, Jinjun Xiong +5
Real-time cine magnetic resonance imaging (MRI) plays an increasingly important role in various cardiac interventions. In order to enable fast and accurate visual assistance, the t…
Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start
Weiwen Jiang, Lei Yang, Sakyasingha Dasgupta +2
Hardware and neural architecture co-search that automatically generates Artificial Intelligence (AI) solutions from a given dataset is promising to promote AI democratization; howe…
BUNET: Blind Medical Image Segmentation Based on Secure UNET
Song Bian, Xiaowei Xu, Weiwen Jiang +2
The strict security requirements placed on medical records by various privacy regulations become major obstacles in the age of big data. To ensure efficient machine learning as a s…
DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation
Shunjie Dong, Jinlong Zhao, Maojun Zhang +5
Automatic segmentation of cardiac magnetic resonance imaging (MRI) facilitates efficient and accurate volume measurement in clinical applications. However, due to anisotropic resol…
MS-NAS: Multi-Scale Neural Architecture Search for Medical Image Segmentation
Xingang Yan, Weiwen Jiang, Yiyu Shi +1
The recent breakthroughs of Neural Architecture Search (NAS) have motivated various applications in medical image segmentation. However, most existing work either simply rely on hy…
Enabling On-Device CNN Training by Self-Supervised Instance Filtering and Error Map Pruning
Yawen Wu, Zhepeng Wang, Yiyu Shi +1
This work aims to enable on-device training of convolutional neural networks (CNNs) by reducing the computation cost at training time. CNN models are usually trained on high-perfor…
A Co-Design Framework of Neural Networks and Quantum Circuits Towards Quantum Advantage
Weiwen Jiang, Jinjun Xiong, Yiyu Shi
Despite the pursuit of quantum advantages in various applications, the power of quantum computers in neural network computations has mostly remained unknown, primarily due to a mis…
Intermittent Inference with Nonuniformly Compressed Multi-Exit Neural Network for Energy Harvesting Powered Devices
Yawen Wu, Zhepeng Wang, Zhenge Jia +2
This work aims to enable persistent, event-driven sensing and decision capabilities for energy-harvesting (EH)-powered devices by deploying lightweight DNNs onto EH-powered devices…
ENSEI: Efficient Secure Inference via Frequency-Domain Homomorphic Convolution for Privacy-Preserving Visual Recognition
Song Bian, Tianchen Wang, Masayuki Hiromoto +2
In this work, we propose ENSEI, a secure inference (SI) framework based on the frequency-domain secure convolution (FDSC) protocol for the efficient execution of privacy-preserving…
Multi-Cycle-Consistent Adversarial Networks for CT Image Denoising
Jinglan Liu, Yukun Ding, Jinjun Xiong +6
CT image denoising can be treated as an image-to-image translation task where the goal is to learn the transform between a source domain (noisy images) and a target domain …
NASS: Optimizing Secure Inference via Neural Architecture Search
Song Bian, Weiwen Jiang, Qing Lu +2
Due to increasing privacy concerns, neural network (NN) based secure inference (SI) schemes that simultaneously hide the client inputs and server models attract major research inte…
Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks
Lei Yang, Zheyu Yan, Meng Li +6
Neural Architecture Search (NAS) has demonstrated its power on various AI accelerating platforms such as Field Programmable Gate Arrays (FPGAs) and Graphic Processing Units (GPUs).…