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ct-slice-localization

ct-slice-localization

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Author: F. Graf, H.-P. Kriegel, M. Schubert, S. Poelsterl, A. Cavallaro Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Relative+location+of+CT+slices+on+axial+axis) - 2011 Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) Relative location of CT slices on axial axis Data Set The dataset consists of 384 features extracted from CT images. The class variable is numeric and denotes the relative location of the CT slice on the axial axis of the human body. The data was retrieved from a set of 53500 CT images from 74 different patients (43 male, 31 female). Each CT slice is described by two histograms in polar space. The first histogram describes the location of bone structures in the image, the second the location of air inclusions inside of the body. Both histograms are concatenated to form the final feature vector. Bins that are outside of the image are marked with the value -0.25. The class variable (relative location of an image on the axial axis) was constructed by manually annotating up to 10 different distinct landmarks in each CT Volume with known location. The location of slices in between landmarks was interpolated. ### Attribute information 1. patientId: Each ID identifies a different patient 2. - 241.: Histogram describing bone structures 242. - 385.: Histogram describing air inclusions 386. reference: Relative location of the image on the axial axis (class value). Values are in the range [0; 180] where 0 denotes the top of the head and 180 the soles of the feet.

386 features

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19 properties

53500
Number of instances (rows) of the dataset.
386
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
386
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.
0.01
Number of attributes divided by the number of instances.
100
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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