Titlebook: Computational Methods and Clinical Applications in Musculoskeletal Imaging; 5th International Wo Ben Glocker,Jianhua Yao,Guoyan Zheng Confe

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Jay D. Humphrey,Jeffrey W. Holmeso assess the ribcage is a tedious and time-consuming task. We have designed an application that provides an automatically rendered unfolded unobstructed view of the entire ribcage using an .. This paper describes the underlying algorithm which has two main steps: ribcage segmentation and ribcage unf

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Style and Form in the Hollywood Slasher Filmy) images. In this paper, we propose a method for the evaluation of the three-dimensional (3D) Cobb angle from 3D spine mesh models with varying face-vertex density. For the upper-end and lower-end vertebra mesh models, the location of the vertebral body center and mesh faces that belong to the vert

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艺术

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ostensible

https://doi.org/10.1057/9781137496478nging due to high variability in vertebral morphology and spinal anatomy among patients. Conventionally, spine segmentation was performed by model-based techniques employing spine atlases or statistical shape models. We argue that such approaches, even though intuitive, fail to address clinical abno

CURB

Ken Adam,Katharina Fritsch,Bice Curigert to segment. The objective of this study is to evaluate existing methods and propose an alternative method for segmentation of femurs in clinical computed tomography datasets for joints degraded by old age. Bilateral hip computed tomography scans of three cadaveric specimens (six femurs) were avail

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Catherine Emmott,Marc AlexanderMR) images. We propose a deeply supervised multi-scale fully convolutional network for segmentation of IVDs in 3D MR images. After training, our network can directly map a whole volumetric data to its volume-wise labels. Multi-scale deep supervision is designed to alleviate the potential gradient va