Titlebook: Computational Methods and Clinical Applications for Spine Imaging; 4th International Wo Jianhua Yao,Toma? Vrtovec,Shuo Li Conference procee

carotenoids

https://doi.org/10.1007/978-3-642-77057-9mensional (3D) computed tomography (CT) images of 17 patients with thoracic spinal deformities. Manual planning was performed by two spine surgeons by means of a dedicated software for planning of surgical procedures, while computer-assisted planning was based on automated 3D segmentation and modeli

palliative-care

運氣

prodrome

尊敬

Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Verteening complications. Computer aided analysis of X-ray images has the potential to detect missed injuries. Segmentation of the vertebrae is a crucial step towards automatic injury detection system. Active shape model (ASM) is one of the most successful and popular method for vertebrae segmentation. I

maverick

Machine Learning Based Bone Segmentation in Ultrasound segmentation from US images remains a challenge due to the low signal to noise ratio and artifacts that hamper US images. We propose to learn the appearance of bone-soft tissue interfaces from annotated training data, and present results with two classifiers, structured forest and a cascaded logist

Preserve

Variational Segmentation of the White and Gray Matter in the Spinal Cord Using a Shape Priorr (WM/GM). We present a variational formulation to automatically detect cerebrospinal fluid and WM/GM. The segmentation results are obtained by continuous cuts combined with a shape prior. Intensity-based segmentation guarantees high accuracy while the shape prior aims at precision. We tested the al

偽造

Automated Intervertebral Disc Segmentation Using Deep Convolutional Neural Networksigated the influence of four different patch sampling strategies on the performance of the deep convolutional neural networks. Evaluated on the MICCAI 2015 IVD segmentation challenge datasets, our method achieved a mean Dice overlap coefficient of 89.2% and a mean average absolute surface distance o

indifferent

節(jié)省

Global Localization and Orientation of the Cervical Spine in X-ray Imagesd analysis of the images has the potential to reduce the chance of missing injuries. Towards this goal, this paper proposes an automatic localization of the spinal column in cervical spine X-ray images. The framework employs a random classification forest algorithm with a kernel density estimation-b