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Spine

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Automatic segmentation of vertebrae in 3D CT images using adaptive fast 3D pulse coupled neural networks.

Australasian physical & engineering sciences in medicine
Two systems are presented for segmentation of vertebrae in a 3D computed tomography (CT) image. The first method extracts seven features from each voxel and uses a multi-layer perceptron neural network (MLPNN) to classify the voxel as vertebrae or ba...

A machine learning pipeline for internal anatomical landmark embedding based on a patient surface model.

International journal of computer assisted radiology and surgery
PURPOSE: With the recent introduction of fully assisting scanner technologies by Siemens Healthineers (Erlangen, Germany), a patient surface model was introduced to the diagnostic imaging device market. Such a patient representation can be used to au...

Estimating the Temperature of Heat-exposed Bone via Machine Learning Analysis of SCI Color Values: A Pilot Study.

Journal of forensic sciences
Determining maximum heating temperatures of burnt bones is a long-standing problem in forensic science and archaeology. In this pilot study, controlled experiments were used to heat 14 fleshed and defleshed pig vertebrae (wet bones) and archaeologica...

A new approach for safe planning transfer using semi-automatically adjustable instrument guides.

The international journal of medical robotics + computer assisted surgery : MRCAS
Accurate planning transfer is a prerequisite for successful operative care. For different applications, diverse computer-assisted systems have been developed and clinically evaluated. This paper presents the implementation and evaluation of a new mod...

Spine morphology and energetics: how principles from nature apply to robotics.

Bioinspiration & biomimetics
Inspired by the locomotive advantages that an articulated spine enables in quadrupedal animals, we explore and quantify the energetic effect that an articulated spine has in legged robots. We compare two model instances of a conceptual planar quadrup...

Convolution neural networks for real-time needle detection and localization in 2D ultrasound.

International journal of computer assisted radiology and surgery
PURPOSE: We propose a framework for automatic and accurate detection of steeply inserted needles in 2D ultrasound data using convolution neural networks. We demonstrate its application in needle trajectory estimation and tip localization.

Self-learning computers for surgical planning and prediction of postoperative alignment.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: In past decades, the role of sagittal alignment has been widely demonstrated in the setting of spinal conditions. As several parameters can be affected, identifying the driver of the deformity is the cornerstone of a successful treatment app...