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DA-GAN: Learning Structured Noise Removal In Ultrasound Volume Projection Imaging For Enhanced Spine Segmentation
Zixun Huang;Rui Zhao;Frank H. F. Leung;Kin-Man Lam;Sai Ho Ling;Juan Lyu;Sunetra Banerjee;Timothy Tin-Yan Lee;De Yang;Yong-Ping Zheng
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
Ultrasound volume projection imaging (VPI) has shown to be appealing from a clinical perspective, because of its harmlessness, flexibility, and efficiency in scoliosis assessment. However, the limitations in hardware devices degrade the resultant image content with strong structured noise. Owing to the unavailability of reference data and the unpredictable degradation model, VPI image recovery is ...Show More
Convolutional Neural Networks-Based Lung Nodule Classification: A Surrogate-Assisted Evolutionary Algorithm for Hyperparameter Optimization
Miao Zhang;Huiqi Li;Shirui Pan;Juan Lyu;Steve Ling;Steven Su
This article investigates deep neural networks (DNNs)-based lung nodule classification with hyperparameter optimization. Hyperparameter optimization in DNNs is a computationally expensive problem, and a surrogate-assisted evolutionary algorithm has been recently introduced to automatically search for optimal hyperparameter configurations of DNNs, by applying computationally efficient surrogate mod...Show More
Bone Feature Segmentation in Ultrasound Spine Image with Robustness to Speckle and Regular Occlusion Noise
Zixun Huang;Li-Wen Wang;Frank H. F. Leung;Sunetra Banerjee;De Yang;Timothy Lee;Juan Lyu;Sai Ho Ling;Yong-Ping Zheng
2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Year: 2020 | Conference Paper |
Cited by: Papers (12)
3D ultrasound imaging shows great promise for scoliosis diagnosis thanks to its low-costing, radiation-free and real-time characteristics. The key to accessing scoliosis by ultrasound imaging is to accurately segment the bone area and measure the scoliosis degree based on the symmetry of the bone features. The ultrasound images tend to contain many speckles and regular occlusion noise which is dif...Show More
Automatic Segmentation of 3D Ultrasound Spine Curvature Using Convolutional Neural Network
Sunetra Banerjee;Sai Ho Ling;Juan Lyu;Steven Su;Yong-Ping Zheng
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Year: 2020 | Conference Paper |
Cited by: Papers (4)
Scoliosis is a 3D spinal deformation where the spine takes a lateral curvature, which generates an angle in a coronal plane. For periodic detection of scoliosis, safe and economic imaging modality is needed as continuous exposure to radiative imaging may cause cancer. 3D ultrasound imaging is a cost-effective and radiation-free imaging modality which gives volume projection image. Identification o...Show More
Classification of EEG Motor Imagery Tasks Using Convolution Neural Networks
Sai Ho Ling;Henry Makgawinata;Fernando Huerta Monsivais;Andre dos Santos Goncalves Lourenco;Juan Lyu;Rifai Chai
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2019 | Conference Paper |
Cited by: Papers (5)
Electroencephalograph (EEG) is a highly nonlinear data and very difficult to be classified. The EEG signal is commonly used in the area of Brain-Computer Interface (BCI). The signal can be used as an operative command for directional movements for a powered wheelchair to assist people with disability in performing the daily activity.In this paper, we aim to classify Electroencephalograph EEG signa...Show More
3D Ultrasound Spine Image Selection Using Convolution Learning-to-Rank Algorithm
Juan Lyu;Sai Ho Ling;Sunetra Banerjee;Jenny J.Y. Zheng;Ka-Lee Lai;De Yang;Yong-Ping Zheng;Steven Su
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
3D Ultrasound imaging has become an important means of scoliosis assessment as it is a real-time, cost-effective and radiation-free imaging technique. However, the coronal images from different depths of a 3D ultrasound image have different imaging definitions. So there is a need to select the coronal image that would give the best image definition. Also, manual selection of coronal images is time...Show More
Lung Nodule Classification using A Novel Two-stage Convolutional Neural Networks Structure’
Yang An;Tianren Hu;Jiaqi Wang;Juan Lyu;Sunetra Banerjee;Sai Ho Ling
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2019 | Conference Paper |
Cited by: Papers (5)
Lung cancer is one of the most fatal cancers in the world. If the lung cancer can be diagnosed at an early stage, the survival rate of patients post treatment increases dramatically. Computed Tomography (CT) diagram is an effective tool to detect lung cancer. In this paper, we proposed a novel two-stage convolution neural network (2S-CNN) to classify the lung CT images. The structure is composed o...Show More
Using Multi-level Convolutional Neural Network for Classification of Lung Nodules on CT images
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2018 | Conference Paper |
Cited by: Papers (34)
Lung cancer is one of the four major cancers in the world. Accurate diagnosing of lung cancer in the early stage plays an important role to increase the survival rate. Computed Tomography (CT)is an effective method to help the doctor to detect the lung cancer. In this paper, we developed a multi-level convolutional neural network (ML-CNN)to investigate the problem of lung nodule malignancy classif...Show More
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