Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Computer Vision Pipeline for Automated Determination of Cardiac
  Structure and Function and Detection of Disease by Two-Dimensional
  Echocardiography   Automated cardiac image interpretation has the potential to transform
clinical practice in multiple ways including enabling low-cost serial
assessment of cardiac function in the primary care and rural setting. We
hypothesized that advances in computer vision could enable building a fully
automated, scalable analysis pipeline for echocardiogram (echo) interpretation.
Our approach entailed: 1) preprocessing; 2) convolutional neural networks (CNN)
for view identification, image segmentation, and phasing of the cardiac cycle;
3) quantification of chamber volumes and left ventricular mass; 4) particle
tracking to compute longitudinal strain; and 5) targeted disease detection.
CNNs accurately identified views (e.g. 99% for apical 4-chamber) and segmented
individual cardiac chambers. Cardiac structure measurements agreed with study
report values (e.g. mean absolute deviations (MAD) of 7.7 mL/kg/m2 for left
ventricular diastolic volume index, 2918 studies). We computed automated
ejection fraction and longitudinal strain measurements (within 2 cohorts),
which agreed with commercial software-derived values [for ejection fraction,
MAD=5.3%, N=3101 studies; for strain, MAD=1.5% (n=197) and 1.6% (n=110)], and
demonstrated applicability to serial monitoring of breast cancer patients for
trastuzumab cardiotoxicity. Overall, we found that, compared to manual
measurements, automated measurements had superior performance across seven
internal consistency metrics with an average increase in the Spearman
correlation coefficient of 0.05 (p=0.02). Finally, we developed disease
detection algorithms for hypertrophic cardiomyopathy and cardiac amyloidosis,
with C-statistics of 0.93 and 0.84, respectively. Our pipeline lays the
groundwork for using automated interpretation to support point-of-care handheld
cardiac ultrasound and large-scale analysis of the millions of echos archived
within healthcare systems.

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The categories of this paper are: nucl-th
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The categories of this paper are: hep-lat
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The categories of this paper are: q-bio
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The categories of this paper are: alg-geom
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The categories of this paper are: chem-ph
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The categories of this paper are: adap-org
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The categories of this paper are: atom-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: nlin
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The categories of this paper are: math-ph
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The categories of this paper are: hep-th
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The categories of this paper are: ao-sci
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The categories of this paper are: cond-mat
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The categories of this paper are: comp-gas
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The categories of this paper are: eess