Human Breast Shape Analysis using PCA
نویسندگان
چکیده
This paper introduces a parametric space to describe the shape of human breasts. The parameter space has been obtained from a sample of about 40 patient’s MRI taken in prone position. The data have been cleaned from noise and disturbances and has been dimensionally reduced using Principal Component Analysis. If two references relative to extremal shapes (one of a reconstructed breast and one of a severely aged breast) are taken, all the other shapes span a continuum space that provides an objective way to classify and describe the variability observed in the common clinical practice
منابع مشابه
A Comparative Study on Body Shape of the Genus Alburnus (Rafinesque, 1820) in Iran, Using Geometric Morphometric Analysis
Geometric morphometric method was used to examine body shape variations among all the seven valid species of the genus Alburnus in Iran. In total 409 specimens of A. chalcoides, A. filippii, A. atropatenae, A. caeruleus, A. mossulensis, A. hohenackeri and A. zagrosensis were collected from Babolrud, Baleqlu-Chai, Miriseh, Sarabeleh, Gamasiyab, Mahabad-Chai Rivers and the Gandoman lagoon, respec...
متن کاملComparing Principal and Independent Modes of Variation in 3D Human Torso Shape Using PCA and ICA
We analyse 3D human torso data using Principal Components Analysis (PCA) and Independent Components Analysis (ICA) and compare their respective principal and independent modes of variation. Both PCA and ICA have been used to analyse variations in observed data for different applications. PCA offers a means of capturing the significant variations present in a data sample while ICA is useful in i...
متن کاملHuman Figure Segmentation Using Independent Component Analysis
In this paper, we present a Statistical Shape Model for Human Figure Segmentation in gait sequences. Point Distribution Models (PDM) generally use Principal Component analysis (PCA) to describe the main directions of variation in the training set. However, PCA assumes a number of restrictions on the data that do not always hold. In this work, we explore the potential of Independent Component An...
متن کاملA comparison of two computer-based face identification systems with human perceptions of faces
The performance of two different computer systems for representing faces was compared with human ratings of similarity and distinctiveness, and human memory performance, on a specific set of face images. The systems compared were a graph-matching system (Lades M, Vorbrüggen JC, Buhmann J, Lage J, von der Malsburg C, Würtz RP, Konen W. IEEE., Trans Comput 1993;42:300-311.) and coding based on pr...
متن کاملFace processing: human perception and principal components analysis.
Principal components analysis (PCA) of face images is here related to subjects' performance on the same images. In two experiments subjects were shown a set of faces and asked to rate them for distinctiveness. They were subsequently shown a superset of faces and asked to identify those that had appeared originally. Replicating previous work, we found that hits and false positives (FPs) did not ...
متن کامل