Landmark-free, parametric hypothesis tests regarding two-dimensional contour shapes using coherent point drift registration and statistical parametric mapping

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Statistical Parametric Mapping

1. INTRODUCTION This chapter is about making regionally specific inferences in neuroimaging. These inferences may be about differences expressed when comparing one group of subjects to another or, within subjects, over a sequence of observations. They may pertain to structural differences (e.g. in voxel-based morphometry-Ashburner and Friston 2000) or neurophysiological indices of brain functio...

متن کامل

Benchmarking Non-Parametric Statistical Tests

Although non-parametric tests have already been proposed for that purpose, statistical significance tests for non-standard measures (different from the classification error) are less often used in the literature. This paper is an attempt at empirically verifying how these tests compare with more classical tests, on various conditions. More precisely, using a very large dataset to estimate the w...

متن کامل

3D non-rigid registration using color: Color Coherent Point Drift

Research into object deformations using computer vision techniques has been under intense study in recent years. A widely used technique is 3D non-rigid registration to estimate the transformation between two instances of a deforming structure. Despite many previous developments on this topic, it remains a challenging problem. In this paper we propose a novel approach to non-rigid registration ...

متن کامل

Nonrigid free-form registration using landmark-based statistical deformation models

In this paper, we propose an image registration algorithm named statistically-based FFD registration (SFFD). This registration method is a modification of a well-known free-form deformations (FFD) approach. Our framework dramatically reduces the number of parameters to optimise and only needs to perform a single-resolution optimisation to account for coarse and fine local displacements, in cont...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: PeerJ Computer Science

سال: 2021

ISSN: 2376-5992

DOI: 10.7717/peerj-cs.542