Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Longitudinal Image Registration with Temporal-order and
  Subject-specificity Discrimination   Morphological analysis of longitudinal MR images plays a key role in
monitoring disease progression for prostate cancer patients, who are placed
under an active surveillance program. In this paper, we describe a
learning-based image registration algorithm to quantify changes on regions of
interest between a pair of images from the same patient, acquired at two
different time points. Combining intensity-based similarity and gland
segmentation as weak supervision, the population-data-trained registration
networks significantly lowered the target registration errors (TREs) on holdout
patient data, compared with those before registration and those from an
iterative registration algorithm. Furthermore, this work provides a
quantitative analysis on several longitudinal-data-sampling strategies and, in
turn, we propose a novel regularisation method based on maximum mean
discrepancy, between differently-sampled training image pairs. Based on 216 3D
MR images from 86 patients, we report a mean TRE of 5.6 mm and show
statistically significant differences between the different training data
sampling strategies.

5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
16
The categories of this paper are: stat