AIMC Topic: Deep Learning

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Enhancing music recognition using deep learning-powered source separation technology for cochlear implant users.

The Journal of the Acoustical Society of America
Cochlear implant (CI) is currently the vital technological device for assisting deaf patients in hearing sounds and greatly enhances their sound listening appreciation. Unfortunately, it performs poorly for music listening because of the insufficient...

Deep-learning-based reconstruction of undersampled MRI to reduce scan times: a multicentre, retrospective, cohort study.

The Lancet. Oncology
BACKGROUND: The extended acquisition times required for MRI limit its availability in resource-constrained settings. Consequently, accelerating MRI by undersampling k-space data, which is necessary to reconstruct an image, has been a long-standing bu...

Denoising Multiphase Functional Cardiac CT Angiography Using Deep Learning and Synthetic Data.

Radiology. Artificial intelligence
Coronary CT angiography is increasingly used for cardiac diagnosis. Dose modulation techniques can reduce radiation dose, but resulting functional images are noisy and challenging for functional analysis. This retrospective study describes and evalua...

Multicenter Evaluation of a Weakly Supervised Deep Learning Model for Lymph Node Diagnosis in Rectal Cancer at MRI.

Radiology. Artificial intelligence
Purpose To develop a Weakly supervISed model DevelOpment fraMework (WISDOM) model to construct a lymph node (LN) diagnosis model for patients with rectal cancer (RC) that uses preoperative MRI data coupled with postoperative patient-level pathologic ...

Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT.

Radiology. Artificial intelligence
Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstructi...

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning.

Brain : a journal of neurology
Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's ...

Deep learning-based automatic scoring models for the disease activity of rheumatoid arthritis based on multimodal ultrasound images.

Rheumatology (Oxford, England)
OBJECTIVES: We aimed to investigate the value of deep learning (DL) models based on multimodal ultrasonographic (US) images to quantify RA activity.

Deep Learning-Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality.

Investigative radiology
OBJECTIVES: The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning-based kernel adaptation on long-term mortality.

Facial age recognition based on deep manifold learning.

Mathematical biosciences and engineering : MBE
Facial age recognition has been widely used in real-world applications. Most of current facial age recognition methods use deep learning to extract facial features to identify age. However, due to the high dimension features of faces, deep learning m...