Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors   Tumor detection in biomedical imaging is a time-consuming process for medical
professionals and is not without errors. Thus in recent decades, researchers
have developed algorithmic techniques for image processing using a wide variety
of mathematical methods, such as statistical modeling, variational techniques,
and machine learning. In this paper, we propose a semi-automatic method for
liver segmentation of 2D CT scans into three labels denoting healthy, vessel,
or tumor tissue based on graph cuts. First, we create a feature vector for each
pixel in a novel way that consists of the 59 intensity values in the time
series data and propose a simplified perimeter cost term in the energy
functional. We normalize the data and perimeter terms in the functional to
expedite the graph cut without having to optimize the scaling parameter
$\lambda$. In place of a training process, predetermined tissue means are
computed based on sample regions identified by expert radiologists. The
proposed method also has the advantage of being relatively simple to implement
computationally. It was evaluated against the ground truth on a clinical CT
dataset of 10 tumors and yielded segmentations with a mean Dice similarity
coefficient (DSC) of .77 and mean volume overlap error (VOE) of 36.7%. The
average processing time was 1.25 minutes per slice.

16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess