Or Ordentlich,Gizem Tabak,Pavan Kumar Hanumolu et al.
Or Ordentlich et al.
Systems that capture and process analog signals must first acquire them through an analog-to-digital converter. While subsequent digital processing can remove statistical correlations present in the acquired data, the dynamic range of the c...
J-MoDL: Joint Model-Based Deep Learning for Optimized Sampling and Reconstruction [0.03%]
用于优化采样和重建的联合模型深度学习(J-MoDL)
Hemant Kumar Aggarwal,Mathews Jacob
Hemant Kumar Aggarwal
Modern MRI schemes, which rely on compressed sensing or deep learning algorithms to recover MRI data from undersampled multichannel Fourier measurements, are widely used to reduce the scan time. The image quality of these approaches is heav...
A Domain Enriched Deep Learning Approach to Classify Atherosclerosis using Intravascular Ultrasound Imaging [0.03%]
基于内血管超声影像的动脉粥样硬化分类的领域增强深度学习方法
Max L Olender,Lambros S Athanasiou,Lampros K Michalis et al.
Max L Olender et al.
Intravascular ultrasound (IVUS) imaging is widely used for diagnostic imaging in interventional cardiology. The detection and quantification of atherosclerosis from acquired images is typically performed manually by medical experts or by vi...
Adaptive constrained independent vector analysis: An effective solution for analysis of large-scale medical imaging data [0.03%]
自适应约束独立向量分析：大规模医学影像数据分析的有效解决方案
Suchita Bhinge,Qunfang Long,Vince D Calhoun et al.
Suchita Bhinge et al.
There is a growing need for flexible methods for the analysis of large-scale functional magnetic resonance imaging (fMRI) data for the estimation of global signatures that summarize the population while preserving individual-specific traits...
Automatic Assessment of Speech Impairment in Cantonese-speaking People with Aphasia [0.03%]
粤语失语症患者的言语流畅度自动评估模型研究
Ying Qin,Tan Lee,Anthony Pak Hin Kong
Ying Qin
Aphasia is a common type of acquired language impairment resulting from dysfunction in specific brain regions. Analysis of narrative spontaneous speech, e.g., story-telling, is an essential component of standardized clinical assessment on p...
Distributed Differentially-Private Algorithms for Matrix and Tensor Factorization [0.03%]
分布式矩阵和张量分解的差分隐私算法
Hafiz Imtiaz,Anand D Sarwate
Hafiz Imtiaz
In many signal processing and machine learning applications, datasets containing private information are held at different locations, requiring the development of distributed privacy-preserving algorithms. Tensor and matrix factorizations a...
Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain [0.03%]
利用多模态感知进行移动医疗的一例慢性疼痛案例分析
Min S Hane Aung,Faisal Alquaddoomi,Cheng-Kang Hsieh et al.
Min S Hane Aung et al.
Active and passive mobile sensing has garnered much attention in recent years. In this paper, we focus on chronic pain measurement and management as a case application to exemplify the state of the art. We present a consolidated discussion ...
Localizing Sources of Brain Disease Progression with Network Diffusion Model [0.03%]
基于网络扩散模型的脑疾病进展源头定位方法
Chenhui Hu,Xue Hua,Jun Ying et al.
Chenhui Hu et al.
Pinpointing the sources of dementia is crucial to the effective treatment of neurodegenerative diseases. In this paper, we propose a diffusion model with impulsive sources over the brain connectivity network to model the progression of brai...
Transmodal Learning of Functional Networks for Alzheimer's Disease Prediction [0.03%]
跨模式功能网络学习的阿尔茨海默病预测方法研究
Mehdi Rahim,Bertrand Thirion,Claude Comtat et al.
Mehdi Rahim et al.
Functional connectivity describes neural activity from resting-state functional magnetic resonance imaging (rs-fMRI). This noninvasive modality is a promising imaging biomarker of neurodegenerative diseases, such as Alzheimer's disease (AD)...
Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling [0.03%]
统一的子空间模型下的单模态和跨模态脑网络盲源分离框架
Rogers F Silva,Sergey M Plis,Jing Sui et al.
Rogers F Silva et al.
In the past decade, numerous advances in the study of the human brain were fostered by successful applications of blind source separation (BSS) methods to a wide range of imaging modalities. The main focus has been on extracting "networks" ...