AIMC Topic: Skull

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Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks.

Artificial intelligence in medicine
Manual annotation is considered to be the "gold standard" in medical imaging analysis. However, medical imaging datasets that include expert manual segmentation are scarce as this step is time-consuming, and therefore expensive. Moreover, single-rate...

Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images-Application in Brain Proton Therapy.

International journal of radiation oncology, biology, physics
PURPOSE: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground...

Robotic laser osteotomy through penscriptive structured light visual servoing.

International journal of computer assisted radiology and surgery
PURPOSE: Planning osteotomies is a task that surgeons do as part of standard surgical workflow. This task, however, becomes more difficult and less intuitive when a robot is tasked with performing the osteotomy. In this study, we aim to provide a new...

Craniobot: A computer numerical controlled robot for cranial microsurgeries.

Scientific reports
Over the last few decades, a plethora of tools has been developed for neuroscientists to interface with the brain. Implementing these tools requires precisely removing sections of the skull to access the brain. These delicate cranial microsurgical pr...

Artificial intelligence for sex determination of skeletal remains: Application of a deep learning artificial neural network to human skulls.

Journal of forensic and legal medicine
A deep learning artificial neural network was adapted to the task of sex determination of skeletal remains. The neural network was trained on images of 900 skulls virtually reconstructed from hospital CT scans. When tested on previously unseen images...

Machine learning for detecting moyamoya disease in plain skull radiography using a convolutional neural network.

EBioMedicine
BACKGROUND: Recently, innovative attempts have been made to identify moyamoya disease (MMD) by focusing on the morphological differences in the head of MMD patients. Following the recent revolution in the development of deep learning (DL) algorithms,...

CT image segmentation of bone for medical additive manufacturing using a convolutional neural network.

Computers in biology and medicine
BACKGROUND: The most tedious and time-consuming task in medical additive manufacturing (AM) is image segmentation. The aim of the present study was to develop and train a convolutional neural network (CNN) for bone segmentation in computed tomography...

Inferring locomotor behaviours in Miocene New World monkeys using finite element analysis, geometric morphometrics and machine-learning classification techniques applied to talar morphology.

Journal of the Royal Society, Interface
The talus is one of the most commonly preserved post-cranial elements in the platyrrhine fossil record. Talar morphology can provide information about postural adaptations because it is the anatomical structure responsible for transmitting body mass ...

Automated deep-neural-network surveillance of cranial images for acute neurologic events.

Nature medicine
Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcomes and preserving neurologic function-'time is brain'. Although these disorders are often recognizabl...

Sex Determination of 3D Skull Based on a Novel Unsupervised Learning Method.

Computational and mathematical methods in medicine
In law enforcement investigation cases, sex determination from skull morphology is one of the important steps in establishing the identity of an individual from unidentified human skeleton. To our knowledge, existing studies of sex determination of t...