AIMC Topic: Head

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Combining deep learning with 3D stereophotogrammetry for craniosynostosis diagnosis.

Scientific reports
Craniosynostosis is a condition in which cranial sutures fuse prematurely, causing problems in normal brain and skull growth in infants. To limit the extent of cosmetic and functional problems, swift diagnosis is needed. The goal of this study is to ...

C-arm CT imaging with the extended line-ellipse-line trajectory: first implementation on a state-of-the-art robotic angiography system.

Physics in medicine and biology
Three-dimensional cone-beam imaging has become valuable in interventional radiology. Currently, this tool, referred to as C-arm CT, employs a circular short-scan for data acquisition, which limits the axial volume coverage and yields unavoidable cone...

Controlling a robotic arm for functional tasks using a wireless head-joystick: A case study of a child with congenital absence of upper and lower limbs.

PloS one
Children with movement impairments needing assistive devices for activities of daily living often require novel methods for controlling these devices. Body-machine interfaces, which rely on body movements, are particularly well-suited for children as...

Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods.

Medical physics
Radiotherapy (RT) is one of the basic treatment modalities for cancer of the head and neck (H&N), which requires a precise spatial description of the target volumes and organs at risk (OARs) to deliver a highly conformal radiation dose to the tumor c...

Evaluation of mental workload during automobile driving using one-class support vector machine with eye movement data.

Applied ergonomics
The aim of this study is to investigate the usefulness of the anomaly detection method by one-class support vector machine (OCSVM) for the evaluation of mental workload (MWL) during automobile driving. Twelve students (six males and six females) part...

Spatio-temporal visual attention modelling of standard biometry plane-finding navigation.

Medical image analysis
We present a novel multi-task neural network called Temporal SonoEyeNet (TSEN) with a primary task to describe the visual navigation process of sonographers by learning to generate visual attention maps of ultrasound images around standard biometry p...

Identifying psychosis spectrum youth using support vector machines and cerebral blood perfusion as measured by arterial spin labeled fMRI.

NeuroImage. Clinical
Altered cerebral blood flow (CBF), as measured by arterial spin labelling (ASL), has been observed in several psychiatric conditions, but is a generally underutilized MRI technique, especially in the study of psychosis spectrum (PS) symptoms. We aime...

Comparison of deep learning models for natural language processing-based classification of non-English head CT reports.

Neuroradiology
PURPOSE: Natural language processing (NLP) can be used for automatic flagging of radiology reports. We assessed deep learning models for classifying non-English head CT reports.

Learning-based estimation of dielectric properties and tissue density in head models for personalized radio-frequency dosimetry.

Physics in medicine and biology
Radio-frequency dosimetry is an important process in assessments for human exposure safety and for compliance of related products. Recently, computational human models generated from medical images have often been used for such assessment, especially...