AIMC Topic: Deep Learning

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Deep learning phase error correction for cerebrovascular 4D flow MRI.

Scientific reports
Background phase errors in 4D Flow MRI may negatively impact blood flow quantification. In this study, we assessed their impact on cerebrovascular flow volume measurements, evaluated the benefit of manual image-based correction, and assessed the pote...

Detection of ADHD from EEG signals using new hybrid decomposition and deep learning techniques.

Journal of neural engineering
Attention deficit hyperactivity disorder (ADHD) is considered one of the most common psychiatric disorders in childhood. The incidence of this disease in the community draws an increasing graph from the past to the present. While the ADHD diagnosis i...

Estimation of Lower Extremity Joint Moments and 3D Ground Reaction Forces Using IMU Sensors in Multiple Walking Conditions: A Deep Learning Approach.

IEEE journal of biomedical and health informatics
Human kinetics, specifically joint moments and ground reaction forces (GRFs) can provide important clinical information and can be used to control assistive devices. Traditionally, collection of kinetics is mostly limited to the lab environment becau...

VLTENet: A Deep-Learning-Based Vertebra Localization and Tilt Estimation Network for Automatic Cobb Angle Estimation.

IEEE journal of biomedical and health informatics
Scoliosis diagnosis and assessment rely upon Cobb angle estimation from X-ray images of the spine. Recently, automated scoliosis assessment has been greatly improved using deep learning methods. However, in such methods, the Cobb angle is usually pre...

Redefining Lobe-Wise Ground-Glass Opacity in COVID-19 Through Deep Learning and its Correlation With Biochemical Parameters.

IEEE journal of biomedical and health informatics
During COVID-19 pandemic qRT-PCR, CT scans and biochemical parameters were studied to understand the patients' physiological changes and disease progression. There is a lack of clear understanding of the correlation of lung inflammation with biochemi...

A Comprehensive Survey of Deep Learning Techniques in Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Protein function prediction is a major challenge in the field of bioinformatics which aims at predicting the functions performed by a known protein. Many protein data forms like protein sequences, protein structures, protein-protein interaction netwo...

DeepCGP: A Deep Learning Method to Compress Genome-Wide Polymorphisms for Predicting Phenotype of Rice.

IEEE/ACM transactions on computational biology and bioinformatics
Genomic selection (GS) is expected to accelerate plant and animal breeding. During the last decade, genome-wide polymorphism data have increased, which has raised concerns about storage cost and computational time. Several individual studies have att...

Deep Learning Accelerated Image Reconstruction of Fluid-Attenuated Inversion Recovery Sequence in Brain Imaging: Reduction of Acquisition Time and Improvement of Image Quality.

Academic radiology
RATIONALE AND OBJECTIVES: Fluid-attenuated inversion recovery (FLAIR) imaging is playing an increasingly significant role in the detection of brain metastases with a concomitant increase in the number of magnetic resonance imaging (MRI) examinations....

A single stage knowledge distillation network for brain tumor segmentation on limited MR image modalities.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Precisely segmenting brain tumors using multimodal Magnetic Resonance Imaging (MRI) is an essential task for early diagnosis, disease monitoring, and surgical planning. Unfortunately, the complete four image modalities utili...

Noise power spectrum properties of deep learning-based reconstruction and iterative reconstruction algorithms: Phantom and clinical study.

European journal of radiology
PURPOSE: To compare the noise power spectrum (NPS) properties and perform a qualitative analysis of hybrid iterative reconstruction (IR), model-based IR (MBIR), and deep learning-based reconstruction (DLR) at a similar noise level in clinical study a...