Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Artifact- and content-specific quality assessment for MRI with image
  rulers   In clinical practice MR images are often first seen by radiologists long
after the scan. If image quality is inadequate either patients have to return
for an additional scan, or a suboptimal interpretation is rendered. An
automatic image quality assessment (IQA) would enable real-time remediation.
Existing IQA works for MRI give only a general quality score, agnostic to the
cause of and solution to low-quality scans. Furthermore, radiologists' image
quality requirements vary with the scan type and diagnostic task. Therefore,
the same score may have different implications for different scans. We propose
a framework with multi-task CNN model trained with calibrated labels and
inferenced with image rulers. Labels calibrated by human inputs follow a
well-defined and efficient labeling task. Image rulers address varying quality
standards and provide a concrete way of interpreting raw scores from the CNN.
The model supports assessments of two of the most common artifacts in MRI:
noise and motion. It achieves accuracies of around 90%, 6% better than the best
previous method examined, and 3% better than human experts on noise assessment.
Our experiments show that label calibration, image rulers, and multi-task
training improve the model's performance and generalizability.

28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
23
The categories of this paper are: solv-int
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga