AIMC Topic: Tomography, X-Ray Computed

Clear Filters Showing 3201 to 3210 of 5128 articles

Quantitative evaluation of chronically obstructed kidneys from noncontrast computed tomography based on deep learning.

European journal of radiology
OBJECTIVE: To quantitatively report renal parenchymal volume (RPV), renal sinus volume (RSV), and renal parenchymal density (RPD) for chronically obstructed kidneys from noncontrast computed tomography (NCCT).

Chest X-ray image phase features for improved diagnosis of COVID-19 using convolutional neural network.

International journal of computer assisted radiology and surgery
PURPOSE: Recently, the outbreak of the novel coronavirus disease 2019 (COVID-19) pandemic has seriously endangered human health and life. In fighting against COVID-19, effective diagnosis of infected patient is critical for preventing the spread of d...

True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation.

European journal of nuclear medicine and molecular imaging
PURPOSE: While sampled or short-frame realizations have shown the potential power of deep learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose cases is lacking. Therefore, we evaluated deep learning enhancement u...

3D multi-scale deep convolutional neural networks for pulmonary nodule detection.

PloS one
With the rapid development of big data and artificial intelligence technology, computer-aided pulmonary nodule detection based on deep learning has achieved some successes. However, the sizes of pulmonary nodules vary greatly, and the pulmonary nodul...

Lung cancer histology classification from CT images based on radiomics and deep learning models.

Medical & biological engineering & computing
Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are frequent reported cases of non-small cell lung cancer (NSCLC), responsible for a large fraction of cancer deaths worldwide. In this study, we aim to investigate the potential of NSCLC histolog...

Utility of deep learning for the diagnosis of otosclerosis on temporal bone CT.

European radiology
OBJECTIVE: Diagnosis of otosclerosis on temporal bone CT images is often difficult because the imaging findings are frequently subtle. Our aim was to assess the utility of deep learning analysis in diagnosing otosclerosis on temporal bone CT images.

Automated Lateral Ventricular and Cranial Vault Volume Measurements in 13,851 Patients Using Deep Learning Algorithms.

World neurosurgery
BACKGROUND: No large dataset-derived standard has been established for normal or pathologic human cerebral ventricular and cranial vault volumes. Automated volumetric measurements could be used to assist in diagnosis and follow-up of hydrocephalus or...

Accurately Differentiating Between Patients With COVID-19, Patients With Other Viral Infections, and Healthy Individuals: Multimodal Late Fusion Learning Approach.

Journal of medical Internet research
BACKGROUND: Effectively identifying patients with COVID-19 using nonpolymerase chain reaction biomedical data is critical for achieving optimal clinical outcomes. Currently, there is a lack of comprehensive understanding in various biomedical feature...