Statistical Shape Models: Understanding and Mastering Variation in Anatomy | SpringerLinklink.springer.com/chapter/10.1007/978-3-030-19385-0_5 一. 统计形状模型(SSMs)是一种几何模型,它以一种非常紧凑的方式描述了一组语义相似的对象。ssm代表了一系列三维物体的平均形状以及它们在形状上的变化。ssm的创...
Statistical shape models (SSMs) are widely used in medical image segmentation. However, traditional SSM methods suffer from the High-Dimension-Low-Sample-Size (HDLSS) problem in modelling. In this work, we extend the state-of-the-art multi-resolution SSM approach from two dimension (2D) to ...
Yokota F, Okada T, Takao M, Sugano N, Tada Y, Tomiyama N, Sato Y. Automated ct segmentation of diseased hip using hierarchical and conditional statistical shape models. In: Medical Image Computing and Computer-Assisted Intervention. Berlin, Heidelberg: Springer; 2013. p. 190-7....
In this paper, we integrated statistical shape models (SSM), able to represent the individual morphology of the trochlea by means of a set of parameters and stacked sparse autoencoder (SSPA) networks, which exploit the parameters to discriminate among different levels of abnormalities.Pietro...
For orthopaedic reconstruction, the prediction of missing parts allows for the accurate restoration of joint kinematics in the musculoskeletal system [35]. A method widely used in the literature is the prediction of missing bone parts using statistical shape models (SSM) [1,27,31,34,37,49]. Ab...
However, existing deep learning models still have limitations and require established/optimized shape models for training. We propose Mesh2SSM, a new approach that leverages unsupervised, permutation-invariant representation learning to estimate how to deform a template point cloud to subject-specific ...
This study proposes a new liver segmentation method based on a sparse a priori statistical shape model (SP-SSM). First, mark points are selected in the liver a priori model and the original image. Then, the a priori shape and its mark points are used to obtain a dictionary for the liver...
3D Statistical Shape and Appearance Models (SSM and SAM) were established, and 80 principal component (PC) modes were extracted from the SSM and SAM as the candidate features. The bone strength of each case was also calculated as the candidate feature using finite element analysis (FEA). Suppo...
The validation and comparison are done using different statistical shape models (SSM) built using the point distribution model (PDM), velocity fields and ... Bartomiej W. Papie,BJ Matuszewski,LK Shark,... - 《Pattern Recognition & Image Analysis》 被引量: 5发表: 2013年 Characterizing Anatomic...
DeepSSM: A Deep Learning Framework for Statistical Shape Modeling from Raw Images Statistical shape modeling is an important tool to characterize variation in anatomical morphology. Typical shapes of interest are measured using 3D imaging and a subsequent pipeline of registration, segmentation, and some...