Search Results - "IEEE transactions on biomedical engineering"

Domain Adaptation for Medical Image Analysis: A Survey by Guan, Hao, Liu, Mingxia

“…Machine learning techniques used in computer-aided medical image analysis usually suffer from the domain shift problem caused by different distributions…”
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Medical Image Synthesis with Deep Convolutional Adversarial Networks by Nie, Dong, Trullo, Roger, Lian, Jun, Wang, Li, Petitjean, Caroline, Ruan, Su, Wang, Qian, Shen, Dinggang

“…Medical imaging plays a critical role in various clinical applications. However, due to multiple considerations such as cost and radiation dose, the…”
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Algorithmic Principles of Remote PPG by Wang, Wenjin, den Brinker, Albertus C., Stuijk, Sander, de Haan, Gerard

“…This paper introduces a mathematical model that incorporates the pertinent optical and physiological properties of skin reflections with the objective to…”
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SleepTransformer: Automatic Sleep Staging With Interpretability and Uncertainty Quantification by Phan, Huy, Mikkelsen, Kaare, Chen, Oliver Y., Koch, Philipp, Mertins, Alfred, De Vos, Maarten

“…Background: Black-box skepticism is one of the main hindrances impeding deep-learning-based automatic sleep scoring from being used in clinical environments…”
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Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks by Kiranyaz, Serkan, Ince, Turker, Gabbouj, Moncef

“…Goal: This paper presents a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system. Methods: An adaptive…”
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Evaluation of Artifact Subspace Reconstruction for Automatic Artifact Components Removal in Multi-Channel EEG Recordings by Chang, Chi-Yuan, Hsu, Sheng-Hsiou, Pion-Tonachini, Luca, Jung, Tzyy-Ping

“…Objective: Artifact subspace reconstruction (ASR) is an automatic, online-capable, component-based method that can effectively remove transient or…”
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A Dataset for Breast Cancer Histopathological Image Classification by Spanhol, Fabio A., Oliveira, Luiz S., Petitjean, Caroline, Heutte, Laurent

“…Today, medical image analysis papers require solid experiments to prove the usefulness of proposed methods. However, experiments are often performed on data…”
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Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks by Lee, Dongwook, Yoo, Jaejun, Tak, Sungho, Ye, Jong Chul

“…Objective: Accelerated magnetic resonance (MR) image acquisition with compressed sensing (CS) and parallel imaging is a powerful method to reduce MR imaging…”
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Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait by Rajagopal, Apoorva, Dembia, Christopher L., DeMers, Matthew S., Delp, Denny D., Hicks, Jennifer L., Delp, Scott L.

“…Objective: Musculoskeletal models provide a noninvasive means to study human movement and predict the effects of interventions on gait. Our goal was to create…”
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Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach by He, He, Wu, Dongrui

“…Objective: This paper targets a major challenge in developing practical electroencephalogram (EEG)-based brain-computer interfaces (BCIs): how to cope with…”
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EEG Based Emotion Recognition by Combining Functional Connectivity Network and Local Activations by Li, Peiyang, Zhang, Yangsong, Xu, Peng, Liu, Huan, Si, Yajing, Li, Cunbo, Li, Fali, Zhu, Xuyang, Huang, Xiaoye, Zeng, Ying, Yao, Dezhong

“…Objective: Spectral power analysis plays a predominant role in electroencephalogram-based emotional recognition. It can reflect activity differences among…”
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Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation by Yan, Zengqiang, Yang, Xin, Cheng, Kwang-Ting

“…Objective: Deep learning based methods for retinal vessel segmentation are usually trained based on pixel-wise losses, which treat all vessel pixels with equal…”
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Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection by Dou, Qi, Chen, Hao, Yu, Lequan, Qin, Jing, Heng, Pheng-Ann

“…Objective: False positive reduction is one of the most crucial components in an automated pulmonary nodule detection system, which plays an important role in…”
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A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images by Orlando, Jose Ignacio, Prokofyeva, Elena, Blaschko, Matthew B.

“…Goal: In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively…”
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Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data by Lee, Changhee, Yoon, Jinsung, Schaar, Mihaela van der

“…Currently available risk prediction methods are limited in their ability to deal with complex, heterogeneous, and longitudinal data such as that available in…”
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Cuffless Blood Pressure Estimation Algorithms for Continuous Health-Care Monitoring by Kachuee, Mohammad, Kiani, Mohammad Mahdi, Mohammadzade, Hoda, Shabany, Mahdi

“…Goal: Continuous blood pressure (BP) monitoring can provide invaluable information about individuals' health conditions. However, BP is conventionally measured…”
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Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features by Yu, Zhen, Jiang, Xudong, Zhou, Feng, Qin, Jing, Ni, Dong, Chen, Siping, Lei, Baiying, Wang, Tianfu

“…In this paper, we present a novel framework for dermoscopy image recognition via both a deep learning method and a local descriptor encoding strategy…”
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A Multivariate Approach for Patient-Specific EEG Seizure Detection Using Empirical Wavelet Transform by Bhattacharyya, Abhijit, Pachori, Ram Bilas

“…Objective: This paper investigates the multivariate oscillatory nature of electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure…”
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A Review of Low-Intensity Pulsed Ultrasound for Therapeutic Applications by Jiang, Xiaoxue, Savchenko, Oleksandra, Li, Yufeng, Qi, Shiang, Yang, Tianlin, Zhang, Wei, Chen, Jie

“…Ultrasound therapy has a long history of novel applications in medicine. Compared to high-intensity ultrasound used for tissue heating, low-intensity…”
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Transfer Learning: A Riemannian Geometry Framework With Applications to Brain-Computer Interfaces by Zanini, Paolo, Congedo, Marco, Jutten, Christian, Said, Salem, Berthoumieu, Yannick

“…Objective: This paper tackles the problem of transfer learning in the context of electroencephalogram (EEG)-based brain-computer interface (BCI)…”
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