Head Trauma

Saliency-guided deep learning network for automatic tumor bed volume delineation in post-operative breast irradiation.

Efficient, reliable and reproducible target volume delineation is a key step in the effective planning of breast radiotherapy. However, post-operative breast target delineation is challenging as the contrast between the tumor bed volume (TBV) and normal breast tissue is relatively low in CT images. In this study, we propose to mimic the marker-guidance procedure in manual target delineation. We de...

Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.

Muscle fat infiltration (MFI) has been widely reported across cervical spine disorders. The quantification of MFI requires time-consuming and rater-dependent manual segmentation techniques. A convolutional neural network (CNN) model was trained to segment seven cervical spine muscle groups (left and right muscles segmented separately, 14 muscles total) from Dixon MRI scans (n = 17, 17 scans < 2 we...

A geometry-guided deep learning technique for CBCT reconstruction.

Although deep learning (DL) technique has been successfully used for computed tomography (CT) reconstruction, its implementation on cone-beam CT (CBCT...

Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic ...

Deep Learning-Guided Fiberoptic Raman Spectroscopy Enables Real-Time Diagnosis and Assessment of Nasopharyngeal Carcinoma and Post-treatment Efficacy during Endoscopy.

In this work, we develop a deep learning-guided fiberoptic Raman diagnostic platform to assess its ability of real-time nasopharyngeal carcinoma (NPC...

DeepEMhancer: a deep learning solution for cryo-EM volume post-processing.

Cryo-EM maps are valuable sources of information for protein structure modeling. However, due to the loss of contrast at high frequencies, they genera...

Deep Learning-Based Magnetic Resonance Imaging Image Features for Diagnosis of Anterior Cruciate Ligament Injury.

To study and explore the adoption value of magnetic resonance imaging (MRI) in the diagnosis of anterior cruciate ligament (ACL) injuries, a multimoda...

Optimization and Simulation of Enterprise Management Resource Scheduling Based on the Radial Basis Function (RBF) Neural Network.

In the human resource system of modern enterprises, human-post matching big data occupies an important irreplaceable position. With the deepening of t...

Phenotyping the Spectrum of Traumatic Brain Injury: A Review and Pathway to Standardization.

It is widely appreciated that the spectrum of traumatic brain injury (TBI), mild through severe, contains distinct clinical presentations, variably re...

Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning.

Delayed graft function (DGF) is a strong risk factor for development of interstitial fibrosis and tubular atrophy (IFTA) in kidney transplants. Quanti...

A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy.

In post-operative radiotherapy for prostate cancer, precisely contouring the clinical target volume (CTV) to be irradiated is challenging, because the...

Ketofol as an Anesthetic Agent in Patients With Isolated Moderate to Severe Traumatic Brain Injury: A Prospective, Randomized Double-blind Controlled Trial.

BACKGROUND: The effects of ketofol (propofol and ketamine admixture) on systemic hemodynamics and outcomes in patients undergoing emergency decompress...

Using artificial intelligence and longitudinal location data to differentiate persons who develop posttraumatic stress disorder following childhood trauma.

Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is...

Extraperitoneal versus transperitoneal approach for robot-assisted radical prostatectomy: a contemporary systematic review and meta-analysis.

We aim to evaluate the differences in peri-operative characteristics, surgical complications, and oncological and functional control between the extra...

Outcomes and complications of patients undergoing Salter's innominate osteotomies for hip dysplasia: a systematic review of comparative studies.

The purpose of this systematic review is to assess outcomes and complications of patients undergoing Salter's innominate osteotomies (SIOs) for the co...

Calibrated uncertainty estimation for interpretable proton computed tomography image correction using Bayesian deep learning.

Integrated-type proton computed tomography (pCT) measures proton stopping power ratio (SPR) images for proton therapy treatment planning, but its imag...

Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Smartphones can be used to passively assess and monitor patients' speech impairments caused by ailments such as Parkinson's disease, Traumatic Brain ...

Synthesizing CT images from MR images with deep learning: model generalization for different datasets through transfer learning.

Replacing CT imaging with MR imaging for MR-only radiotherapy has sparked the interest of many scientists and is being increasingly adopted in radiati...

Clinical Enhancement in AI-Based Post-processed Fast-Scan Low-Dose CBCT for Head and Neck Adaptive Radiotherapy.

To assess image quality and uncertainty in organ-at-risk segmentation on cone beam computed tomography (CBCT) enhanced by deep-learning convolutional...

Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury.

Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes...