Neighbourhood Approximation Forests
نویسندگان
چکیده
Methods that leverage neighbourhood structures in high-dimensional image spaces have recently attracted attention. These approaches extract information from a new image using its "neighbours" in the image space equipped with an application-specific distance. Finding the neighbourhood of a given image is challenging due to large dataset sizes and costly distance evaluations. Furthermore, automatic neighbourhood search for a new image is currently not possible when the distance is based on ground truth annotations. In this article we present a general and efficient solution to these problems. "neighbourhood approximation forests" (NAF) is a supervised learning algorithm that approximates the neighbourhood structure resulting from an arbitrary distance. As NAF uses only image intensities to infer neighbours it can also be applied to distances based on ground truth annotations. We demonstrate NAF in two scenarios: (i) choosing neighbours with respect to a deformation-based distance, and (ii) age prediction from brain MRI. The experiments show NAF's approximation quality, computational advantages and use in different contexts.
منابع مشابه
Neighbourhood approximation using randomized forests
Leveraging available annotated data is an essential component of many modern methods for medical image analysis. In particular, approaches making use of the "neighbourhood" structure between images for this purpose have shown significant potential. Such techniques achieve high accuracy in analysing an image by propagating information from its immediate "neighbours" within an annotated database....
متن کاملMyocardial Infarct Localization Using Neighbourhood Approximation Forests
This paper presents a machine-learning algorithm for the automatic localization of myocardial infarct in the left ventricle. Our method constructs neighbourhood approximation forests, which are trained with previously diagnosed 4D cardiac sequences. We introduce a new set of features that simultaneously exploit information from the shape and motion of the myocardial wall along the cardiac cycle...
متن کاملApproximating Euclidean circles by neighbourhood sequences in a hexagonal grid
In this paper the nodes of the hexagonal grid are used as points. There are 3 types of neighbours on this grid, therefore neighbourhood sequences contain values 1, 2, 3. The grid is coordinatized by three coordinates in a symmetric way. Digital circles are classified based on digital distances using neighbourhood sequences. They can be triangle, hexagon, enneagon and dodecagon. Their corners an...
متن کاملContextual land-cover classification: incorporating spatial dependence in land-cover classification models using random forests and the Getis statistic
This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to da...
متن کاملFast Approximation of the “Neighbourhood” Function for Massive Graphs
The neighbourhood function, N (h), is the number of pairs of nodes that are within distance h. The neighbourhood function provides useful information for graphs such as the structure of XML documents, OODBs, Web graphs, telephone (caller-callee) records, citation graphs, to name a few. It is very expensive to compute the neighbourhood function exactly on large graphs. Instead, we propose an alg...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
دوره 15 Pt 3 شماره
صفحات -
تاریخ انتشار 2012